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Luc Bauwens

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Michel Lubrano & Luc Bauwens & Alan Kirman & Camelia Protopopescu, 2003. "Ranking Economics Departments in Europe: A Statistical Approach," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1367-1401, December.

    Mentioned in:

    1. > Economics Profession > Ranking in Economics > Ranking Institutions

Working papers

  1. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2022. "We modeled long memory with just one lag!," LIDAM Discussion Papers CORE 2022016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. del Barrio Castro, Tomas & Escribano, Alvaro & Sibbertsen, Philipp, 2024. "Modeling and Forecasting the Long Memory of Cyclical Trends in Paleoclimate Data," Hannover Economic Papers (HEP) dp-722, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    2. Shikta Sing & Supun Chandrasena & Yue Shi & Abdullah Alhussain & Claude DIEBOLT & Martin Enilov & Tapas Mishra, 2024. "A Learning Model with Memory in the Financial Markets," Working Papers 06-24, Association Française de Cliométrie (AFC).
    3. Anna Mikusheva & Mikkel S{o}lvsten, 2023. "Linear Regression with Weak Exogeneity," Papers 2308.08958, arXiv.org, revised Jan 2024.

  2. L. Bauwens & E. Otranto, 2020. "Modelling Realized Covariance Matrices: a Class of Hadamard Exponential Models," Working Paper CRENoS 202007, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2025. "The Role of Uncertainty in Forecasting Realized Covariance of US State-Level Stock Returns: A Reverse-MIDAS Approach," Working Papers 202501, University of Pretoria, Department of Economics.

  3. Maciej Augustyniak & Luc Bauwens & Arnaud Dufays, 2019. "A new approach: the factorial hidden Markov volatility model," LIDAM Reprints CORE 3066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    2. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.

  4. Bauwens, Luc & Xu, Yongdeng, 2019. "DCC and DECO-HEAVY: a multivariate GARCH model based on realized variances and correlations," Cardiff Economics Working Papers E2019/5, Cardiff University, Cardiff Business School, Economics Section, revised Aug 2021.

    Cited by:

    1. Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Energy Economics, Elsevier, vol. 136(C).
    2. Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024. "Asymmetric Models for Realized Covariances," LIDAM Discussion Papers ISBA 2024022, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.

  5. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with A New Approach to Nonlinear Filtering," CREATES Research Papers 2018-30, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Hauzenberger, Niko & Pfarrhofer, Michael & Rossini, Luca, 2025. "Sparse time-varying parameter VECMs with an application to modeling electricity prices," International Journal of Forecasting, Elsevier, vol. 41(1), pages 361-376.
    2. Yang, Yuhong, 2000. "Combining Different Procedures for Adaptive Regression," Journal of Multivariate Analysis, Elsevier, vol. 74(1), pages 135-161, July.

  6. L. Bauwens & E. Otranto, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    2. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    3. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Mariagrazia Fallanca & Antonio Fabio Forgione & Edoardo Otranto, 2021. "Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach," JRFM, MDPI, vol. 14(1), pages 1-15, January.

  7. AUGUSTYNIAK, Maciej & BAUWENS, Luc & DUFAYS, Arnaud, 2016. "A New Approach to Volatility Modeling : The High-Dimensional Markov Model," LIDAM Discussion Papers CORE 2016042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.

  8. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Discussion Papers CORE 2016001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    2. BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    4. Xin Jin & John M. Maheu & Qiao Yang, 2019. "Bayesian parametric and semiparametric factor models for large realized covariance matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
    5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    6. Jian, Zhihong & Deng, Pingjun & Zhu, Zhican, 2018. "High-dimensional covariance forecasting based on principal component analysis of high-frequency data," Economic Modelling, Elsevier, vol. 75(C), pages 422-431.
    7. Javed, Farrukh & Loperfido, Nicola & Mazur, Stepan, 2020. "Edgeworth Expansions for Multivariate Random Sums," Working Papers 2020:9, Örebro University, School of Business.
    8. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    9. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    10. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    11. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.
    12. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    13. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    14. Qifa Xu & Junqing Zuo & Cuixia Jiang & Yaoyao He, 2021. "A large constrained time‐varying portfolio selection model with DCC‐MIDAS: Evidence from Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3417-3435, July.
    15. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    16. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).

  9. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    2. Vogler, Jan & Golosnoy, Vasyl, 2023. "Unrestricted maximum likelihood estimation of multivariate realized volatility models," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1063-1074.
    3. Jan Patrick Hartkopf, 2023. "Composite forecasting of vast-dimensional realized covariance matrices using factor state-space models," Empirical Economics, Springer, vol. 64(1), pages 393-436, January.
    4. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    5. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    6. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    7. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).

  10. Luc Bauwens & Edoardo Otranto, 2016. "Modeling the dependence of conditional correlations on market volatility," LIDAM Reprints CORE 2924, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," LIDAM Reprints CORE 3128, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    3. Zacharias Psaradakis & Martin Sola, 2017. "Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities," Birkbeck Working Papers in Economics and Finance 1702, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    5. Shumi Akhtar & Farida Akhtar & Maria Jahromi & Kose John, 2023. "Volatility linkages and value gains from diversifying with Islamic assets," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(8), pages 1495-1528, October.
    6. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    7. Bauwens, Luc & Otranto, Edoardo, 2023. "Realized Covariance Models with Time-varying Parameters and Spillover Effects," LIDAM Discussion Papers CORE 2023019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Gao, Lingbo & Ye, Wuyi & Guo, Ranran, 2022. "Jointly forecasting the value-at-risk and expected shortfall of Bitcoin with a regime-switching CAViaR model," Finance Research Letters, Elsevier, vol. 48(C).
    9. Mariagrazia Fallanca & Antonio Fabio Forgione & Edoardo Otranto, 2021. "Do the Determinants of Non-Performing Loans Have a Different Effect over Time? A Conditional Correlation Approach," JRFM, MDPI, vol. 14(1), pages 1-15, January.
    10. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    11. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    12. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    13. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    14. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    15. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.
    16. Zhang, Hongwei & Zhao, Xinyi & Gao, Wang & Niu, Zibo, 2023. "The role of higher moments in predicting China's oil futures volatility: Evidence from machine learning models," Journal of Commodity Markets, Elsevier, vol. 32(C).
    17. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    18. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    19. Niu, Zibo & Demirer, Riza & Suleman, Muhammad Tahir & Zhang, Hongwei & Zhu, Xuehong, 2024. "Do industries predict stock market volatility? Evidence from machine learning models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).

  11. Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," LIDAM Discussion Papers CORE 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jean HINDRIKS & Yukihiro NISHIMURA, 2016. "Equilibrium Leadership in Tax Competiton Models with Capital Ownership: A Rejoinder," LIDAM Reprints CORE 2758, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Mengheng Li & Ivan Mendieta-Munoz, 2019. "The multivariate simultaneous unobserved components model and identification via heteroskedasticity," Working Paper Series 2019/08, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    3. Didier Nibbering, 2023. "A High-dimensional Multinomial Logit Model," Monash Econometrics and Business Statistics Working Papers 19/23, Monash University, Department of Econometrics and Business Statistics.
    4. Maheu, John M & Song, Yong, 2017. "An Efficient Bayesian Approach to Multiple Structural Change in Multivariate Time Series," MPRA Paper 79211, University Library of Munich, Germany.
    5. Hwu Shih-Tang & Kim Chang-Jin, 2024. "Markov-Switching Models with Unknown Error Distributions: Identification and Inference Within the Bayesian Framework," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 177-199, April.
    6. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    7. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    8. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
    9. DESCHAMPS, Philippe J., 2016. "Bayesian Semiparametric Forecasts of Real Interest Rate Data," LIDAM Discussion Papers CORE 2016050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Vrins, F. & Jeanblanc, M., 2015. "The [phi]-Martingale," LIDAM Discussion Papers CORE 2015022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    13. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    14. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
    15. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    16. Graziano Moramarco, 2025. "Regime‐Switching Density Forecasts Using Economists' Scenarios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 833-845, March.
    17. Didier Nibbering & Richard Paap & Michel van der Wel, 2016. "A Bayesian Infinite Hidden Markov Vector Autoregressive Model," Tinbergen Institute Discussion Papers 16-107/III, Tinbergen Institute, revised 13 Oct 2017.
    18. Balandraud, Eric & Queyranne, Maurice & Tardella, Fabio, 2015. "Largest minimally inversion-complete and pair-complete sets of permutations," LIDAM Discussion Papers CORE 2015009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019. "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 811-843, October.
    20. Didier Nibbering, 2024. "A high‐dimensional multinomial logit model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 481-497, April.
    21. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.

  12. BAUWENS, Luc & KOOP, Gary & KOROBILIS, Dimitris & ROMBOUTS, Jeroen, 2015. "The Contribution of Structural Break Models to Forecating Macroeconomic Series," LIDAM Reprints CORE 2651, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    3. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    4. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    6. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    7. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    8. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    9. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    10. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    11. David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024. "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1155-1168, October.
    12. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    13. Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
    14. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
    15. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    16. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    17. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    18. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    19. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    20. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    21. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    22. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    23. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    24. Eo, Yunjong, 2015. "Structural Changes in Inflation Dynamics: Multiple Breaks at Different Dates for Different Parameters," Working Papers 2015-18, University of Sydney, School of Economics, revised Nov 2015.
    25. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    26. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    27. Kirsten Thompson & Reneé van Eyden & Rangan Gupta, 2015. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(3), pages 486-501, May.
    28. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    29. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    30. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    31. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    32. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    33. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    34. Arnaud Dufays & Jeroen V. K. Rombouts, 2019. "Sparse Change-point HAR Models for Realized Variance," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 857-880, September.
    35. Artem Prokhorov & Peter Radchenko & Alexander Semenov & Anton Skrobotov, 2024. "Change-Point Detection in Time Series Using Mixed Integer Programming," Papers 2408.05665, arXiv.org.
    36. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    37. Anwen Yin, 2024. "Predictive model averaging with parameter instability and heteroskedasticity," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 418-442, April.
    38. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    39. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
    40. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    41. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    42. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    43. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    44. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    45. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    46. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    47. Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
    48. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    49. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    50. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    51. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    52. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    53. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  13. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2014. "Forecasting comparison of long term component dynamic models for realized covariance matrices," LIDAM Discussion Papers CORE 2014053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. BRAIONE, Manuela, 2016. "A time-varying long run HEAVY model," LIDAM Discussion Papers CORE 2016002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting realized covariances using HAR-type models," Papers 2412.10791, arXiv.org.
    5. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    6. Xin Jin & John M. Maheu & Qiao Yang, 2019. "Bayesian parametric and semiparametric factor models for large realized covariance matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
    7. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    8. Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
    9. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting Realized Covariances Using HAR-Type Models," Graz Economics Papers 2024-20, University of Graz, Department of Economics.
    10. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    11. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    12. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Gribisch, Bastian & Hartkopf, Jan Patrick, 2023. "Modeling realized covariance measures with heterogeneous liquidity: A generalized matrix-variate Wishart state-space model," Journal of Econometrics, Elsevier, vol. 235(1), pages 43-64.
    14. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    15. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    16. Hartkopf, Jan Patrick & Reh, Laura, 2023. "Challenging golden standards in EWMA smoothing parameter calibration based on realized covariance measures," Finance Research Letters, Elsevier, vol. 56(C).
    17. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.

  14. BAUWENS, Luc & GRIGORYEVA, Lyudmila & ORTEGA, Juan-Pablo, 2014. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," LIDAM Discussion Papers CORE 2014012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," LIDAM Reprints CORE 3128, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    3. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    4. Shang, Han Lin & Kearney, Fearghal, 2022. "Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1025-1049.
    5. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    6. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    7. Gian Piero Aielli & Davide Pirino, 2023. "Funding Liquidity and Stocks’ Market Liquidity: Structural Estimation From High-Frequency Data," CEIS Research Paper 568, Tor Vergata University, CEIS, revised 28 Nov 2023.
    8. Grigoryeva, Lyudmila & Ortega, Juan-Pablo & Peresetsky, Anatoly, 2018. "Volatility forecasting using global stochastic financial trends extracted from non-synchronous data," Econometrics and Statistics, Elsevier, vol. 5(C), pages 67-82.
    9. Gu, Huaying & Liu, Zhixue & Weng, Yingliang, 2017. "Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 460-472.

  15. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
    3. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. Frédy Valé Manuel Pokou & Jules Sadefo Kamdem & François Benhmad, 2023. "Empirical Performance of an ESG Assets Portfolio from US Market," Post-Print hal-04312348, HAL.
    5. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    6. Guglielmo Maria Caporale & Woo-Young Kang & Fabio Spagnolo & Nicola Spagnolo, 2019. "Non-Linearities, Cyber Attacks and Cryptocurrencies," CESifo Working Paper Series 7692, CESifo.
    7. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2021. "Disagreement on sunspots and soybeans futures price," Economic Modelling, Elsevier, vol. 95(C), pages 385-393.
    8. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    9. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.
    10. Guglielmo Maria Caporale & Timur Zekokh, 2018. "Modelling Volatility of Cryptocurrencies Using Markov-Switching Garch Models," CESifo Working Paper Series 7167, CESifo.
    11. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    12. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    13. Nick James & Roman Marchant & Richard Gerlach & Sally Cripps, 2019. "Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series," Papers 1902.03350, arXiv.org.
    14. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    15. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    16. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    17. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    18. Thabani Ndlovu & Delson Chikobvu, 2023. "A Wavelet-Decomposed WD-ARMA-GARCH-EVT Model Approach to Comparing the Riskiness of the BitCoin and South African Rand Exchange Rates," Data, MDPI, vol. 8(7), pages 1-24, July.
    19. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    20. Huang, Yirong & Luo, Yi, 2024. "Forecasting conditional volatility based on hybrid GARCH-type models with long memory, regime switching, leverage effect and heavy-tail: Further evidence from equity market," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    21. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    22. BenSaïda, Ahmed, 2015. "The frequency of regime switching in financial market volatility," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 63-79.

  16. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. P. Bertuccelli & M. Mucciardi & E. Otranto, 2014. "Spatial Effects in Dynamic Conditional Correlations," Working Paper CRENoS 201406, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Jean-David Fermanian & Hassan Malongo, 2013. "On the Stationarity of Dynamic Conditional Correlation Models," Working Papers 2013-26, Center for Research in Economics and Statistics.
    3. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. François Maniquet & Massimo Morelli, 2015. "Approval quorums dominate participation quorums," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 45(1), pages 1-27, June.
    6. Jean J. Gabszewicz & Skerdilajda Zanaj, 2015. "(Un)stable vertical collusive agreements," Canadian Journal of Economics, Canadian Economics Association, vol. 48(3), pages 924-939, August.
    7. MAULEON, Ana & MOLIS, Elena & VANNETELBOSCH , Vincent J & VERGOTE, Wouter, 2014. "Dominance invariant one-to-one matching problems," LIDAM Reprints CORE 2638, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    9. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    10. Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2016. "Volatility Dependent Dynamic Equicorrelation," NCER Working Paper Series 111, National Centre for Econometric Research.
    11. Benjamin Poignard & Jean-Davis Fermanian, 2014. "Dynamic Asset Correlations Based on Vines," Working Papers 2014-46, Center for Research in Economics and Statistics.
    12. Dudek, Jérémy, 2013. "Illiquidité, contagion et risque systémique," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/13236 edited by Le Fol, Gaëlle.
    13. Becker, Christoph & Schmidt, Wolfgang M., 2015. "How past market movements affect correlation and volatility," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 78-107.
    14. Jean-David Fermanian & Hassan Malongo, 2014. "On the stationarity of Dynamic Conditional Correlation models," Papers 1405.6905, arXiv.org, revised Mar 2016.

  17. Bauwens, Luc & Hafner, Christian & Pierret, Diane, 2013. "Modelling multivariate volatility of electricity futures," LIDAM Reprints ISBA 2013030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    3. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    4. Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.

  18. BAUWENS, Luc & STORTI, Giuseppe, 2012. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Discussion Papers CORE 2012028, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    3. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. CREMER, Helmuth & PESTIEAU, Pierre & PONTHIERE, Grégory, 2012. "The economics of long-term care: a survey," LIDAM Reprints CORE 2466, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  19. BAUWENS, Luc & STORTI, Giuseppe & VIOLANTE, Francesco, 2012. "Dynamic conditional correlation models for realized covariance matrices," LIDAM Discussion Papers CORE 2012060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    2. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    3. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    4. Weigand, Roland, 2014. "Matrix Box-Cox Models for Multivariate Realized Volatility," University of Regensburg Working Papers in Business, Economics and Management Information Systems 478, University of Regensburg, Department of Economics.
    5. Bastian Gribisch, 2018. "A latent dynamic factor approach to forecasting multivariate stock market volatility," Empirical Economics, Springer, vol. 55(2), pages 621-651, September.
    6. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    7. Tobias Hartl & Roland Weigand, 2018. "Multivariate Fractional Components Analysis," Papers 1812.09149, arXiv.org, revised Jan 2019.
    8. Ostap Okhrin & Anastasija Tetereva, 2017. "The Realized Hierarchical Archimedean Copula in Risk Modelling," Econometrics, MDPI, vol. 5(2), pages 1-31, June.
    9. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    10. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    11. Ilya Archakov & Peter Reinhard Hansen, 2020. "A New Parametrization of Correlation Matrices," Papers 2012.02395, arXiv.org.
    12. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    13. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    14. Amendola, Alessandra & Braione, Manuela & Candila, Vincenzo & Storti, Giuseppe, 2020. "A Model Confidence Set approach to the combination of multivariate volatility forecasts," International Journal of Forecasting, Elsevier, vol. 36(3), pages 873-891.
    15. BAUWENS Luc, & XU Yongdeng,, 2019. "DCC-HEAVY: A multivariate GARCH model based on realized variances and correlations," LIDAM Discussion Papers CORE 2019025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. BAUWENS, Luc & STORTI, Giuseppe, 2013. "Computationally efficient inference procedures for vast dimensional realized covariance models," LIDAM Reprints CORE 2469, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Gribisch, Bastian & Hartkopf, Jan Patrick & Liesenfeld, Roman, 2020. "Factor state–space models for high-dimensional realized covariance matrices of asset returns," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 1-20.
    18. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 383-417.
    19. Harry Vander Elst & David Veredas, 2017. "Smoothing it Out: Empirical and Simulation Results for Disentangled Realized Covariances," Journal of Financial Econometrics, Oxford University Press, vol. 15(1), pages 106-138.

  20. WANG, Shin-Huei & BAUWENS, Luc & HSIAO, Cheng, 2012. "Forecasting long memory processes subject to structural breaks," LIDAM Discussion Papers CORE 2012048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    3. Erdenebat Bataa & Marwan Izzeldin & Denise Osborn, 2015. "Changes in the global oil market," Working Papers 75761696, Lancaster University Management School, Economics Department.
    4. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
    5. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    6. Caporin, Massimiliano & Velo, Gabriel G., 2015. "Realized range volatility forecasting: Dynamic features and predictive variables," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 98-112.
    7. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    8. Luo, Jiawen & Demirer, Riza & Gupta, Rangan & Ji, Qiang, 2022. "Forecasting oil and gold volatilities with sentiment indicators under structural breaks," Energy Economics, Elsevier, vol. 105(C).
    9. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    10. Gong, Xu & Lin, Boqiang, 2018. "Structural changes and out-of-sample prediction of realized range-based variance in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 27-39.
    11. Asai, Manabu & Chang, Chia-Lin & McAleer, Michael, 2022. "Realized matrix-exponential stochastic volatility with asymmetry, long memory and higher-moment spillovers," Journal of Econometrics, Elsevier, vol. 227(1), pages 285-304.

  21. Bauwens, Luc & Hafner, Christian M. & Pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," SFB 649 Discussion Papers 2011-063, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    3. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    4. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    5. Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019. "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    6. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Bocart, Fabian Y. R. P. & Hafner, Christian M., 2011. "Econometric analysis of volatile art markets," SFB 649 Discussion Papers 2011-071, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting realized covariances using HAR-type models," Papers 2412.10791, arXiv.org.
    9. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    10. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    11. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    12. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    13. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    14. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    15. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    17. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    18. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    19. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    20. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    21. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting Realized Covariances Using HAR-Type Models," Graz Economics Papers 2024-20, University of Graz, Department of Economics.
    22. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    23. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    24. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    26. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    27. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    29. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    30. Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2013. "Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants," Energy Policy, Elsevier, vol. 59(C), pages 143-160.
    31. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    32. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    33. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    35. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    36. Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    37. Francisco Ortiz Arango & Alma Nelly Montiel Guzmán, 2017. "Transmission of future prices of corn of the Chicago Board of Trade to the Mexican spot market," Contaduría y Administración, Accounting and Management, vol. 62(3), pages 941-957, Julio-Sep.
    38. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    39. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    40. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    41. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    42. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    43. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  22. BAUWENS, Luc & KOROBILIS, Dimitris, 2011. "Bayesian methods," LIDAM Discussion Papers CORE 2011061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.

  23. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen Rombouts, 2011. "A Comparison of Forecasting Procedures For Macroeconomic Series: The Contribution of Structural Break Models," CIRANO Working Papers 2011s-13, CIRANO.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Wensheng Kang & Jing Wang, 2018. "Oil shocks, policy uncertainty and earnings surprises," Review of Quantitative Finance and Accounting, Springer, vol. 51(2), pages 375-388, August.
    3. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    4. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Timmermann, Allan & Pettenuzzo, Davide, 2016. "Forecasting Macroeconomic Variables under Model Instability," CEPR Discussion Papers 11355, C.E.P.R. Discussion Papers.
    6. Gary Koop & Dimitris Korobilis, 2018. "Forecasting with High-Dimensional Panel VARs," Working Paper series 18-20, Rimini Centre for Economic Analysis.
    7. Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
    8. Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
    9. Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
    10. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2021. "Point and density forecasting of macroeconomic and financial uncertainties of the USA," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 700-707, July.
    11. David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024. "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1155-1168, October.
    12. Kirsten Thompson & Renee Van Eyden & Rangan Gupta, 2015. "Identifying an index of financial conditions for South Africa," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 32(2), pages 256-274, June.
    13. Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
    14. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
    15. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    16. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
    17. Todd E. Clark & Taeyoung Doh, 2011. "A Bayesian evaluation of alternative models of trend inflation," Working Papers (Old Series) 1134, Federal Reserve Bank of Cleveland.
    18. Niko Hauzenberger, 2020. "Flexible Mixture Priors for Large Time-varying Parameter Models," Papers 2006.10088, arXiv.org, revised Nov 2020.
    19. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    20. Hou, Chenghan, 2017. "Infinite hidden markov switching VARs with application to macroeconomic forecast," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1025-1043.
    21. Dufays, Arnaud & Rombouts, Jeroen V.K., 2020. "Relevant parameter changes in structural break models," Journal of Econometrics, Elsevier, vol. 217(1), pages 46-78.
    22. Korobilis, D, 2017. "Forecasting with many predictors using message passing algorithms," Essex Finance Centre Working Papers 19565, University of Essex, Essex Business School.
    23. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    24. Nonejad, Nima, 2017. "Forecasting aggregate stock market volatility using financial and macroeconomic predictors: Which models forecast best, when and why?," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 131-154.
    25. Eo, Yunjong, 2015. "Structural Changes in Inflation Dynamics: Multiple Breaks at Different Dates for Different Parameters," Working Papers 2015-18, University of Sydney, School of Economics, revised Nov 2015.
    26. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    27. KOROBILIS, Dimitris, 2011. "VAR forecasting using Bayesian variable selection," LIDAM Discussion Papers CORE 2011022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Kirsten Thompson & Reneé van Eyden & Rangan Gupta, 2015. "Testing the Out-of-Sample Forecasting Ability of a Financial Conditions Index for South Africa," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(3), pages 486-501, May.
    29. Ewing, Bradley T. & Kang, Wensheng & Ratti, Ronald A., 2018. "The dynamic effects of oil supply shocks on the US stock market returns of upstream oil and gas companies," Energy Economics, Elsevier, vol. 72(C), pages 505-516.
    30. Arnaud Dufays & Zhuo Li & Jeroen V.K. Rombouts & Yong Song, 2021. "Sparse change‐point VAR models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 703-727, September.
    31. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
    32. Franz Ruch & Mehmet Balcilar Author-Name-First Mehmet & Mampho P. Modise & Rangan Gupta, 2015. "Forecasting Core Inflation: The Case of South Africa," Working Papers 15-08, Eastern Mediterranean University, Department of Economics.
    33. Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    34. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
    35. Arnaud Dufays & Jeroen V. K. Rombouts, 2019. "Sparse Change-point HAR Models for Realized Variance," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 857-880, September.
    36. Artem Prokhorov & Peter Radchenko & Alexander Semenov & Anton Skrobotov, 2024. "Change-Point Detection in Time Series Using Mixed Integer Programming," Papers 2408.05665, arXiv.org.
    37. Chen, Ji & Yang, Xinglin & Liu, Xiliang, 2022. "Learning, disagreement and inflation forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    38. Anwen Yin, 2024. "Predictive model averaging with parameter instability and heteroskedasticity," Bulletin of Economic Research, Wiley Blackwell, vol. 76(2), pages 418-442, April.
    39. Jiawen Luo & Shengjie Fu & Oguzhan Cepni & Rangan Gupta, 2024. "Climate Risks and Forecastability of US Inflation: Evidence from Dynamic Quantile Model Averaging," Working Papers 202420, University of Pretoria, Department of Economics.
    40. Nonejad Nima, 2015. "Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(5), pages 561-584, December.
    41. Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms, 2023. "Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms," Papers 2303.01887, arXiv.org, revised May 2024.
    42. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    43. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
    44. Pierre L. Siklos, 2020. "Looking into the Rear-View Mirror: Lessons from Japan for the Eurozone and the U.S?," IMES Discussion Paper Series 20-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    45. Hauzenberger, Niko, 2021. "Flexible Mixture Priors for Large Time-varying Parameter Models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 87-108.
    46. Czinkota, Thomas, 2012. "Das Halteproblem bei Strukturbrüchen in Finanzmarktzeitreihen [The Halting Problem applied to Structural Breaks in Financial Time Series]," MPRA Paper 37072, University Library of Munich, Germany.
    47. Kascha, Christian & Trenkler, Carsten, 2015. "Forecasting VARs, model selection, and shrinkage," Working Papers 15-07, University of Mannheim, Department of Economics.
    48. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    49. Elena Afanasyeva, 2020. "Can Forecast Errors Predict Financial Crises? Exploring the Properties of a New Multivariate Credit Gap," Finance and Economics Discussion Series 2020-045, Board of Governors of the Federal Reserve System (U.S.).
    50. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    51. Stephen McKnight & Alexander Mihailov & Fabio Rumler, 2018. "NKPC-Based Inflation Forecasts with a Time-Varying Trend," Serie documentos de trabajo del Centro de Estudios Económicos 2018-05, El Colegio de México, Centro de Estudios Económicos.
    52. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    53. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2020. "Point and Density Forecasting of Macroeconomic and Financial Uncertainties of the United States," Working Papers 202058, University of Pretoria, Department of Economics.
    54. Hossein Hassani & Zara Ghodsi & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting Home Sales in the Four Census Regions and the Aggregate US Economy Using Singular Spectrum Analysis," Working Papers 201482, University of Pretoria, Department of Economics.
    55. Dimitrios P. Louzis, 2016. "Macroeconomic forecasting and structural changes in steady states," Working Papers 204, Bank of Greece.

  24. Bauwens, L. & Hafner, C. & Pierret, D., 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers ISBA 2011013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    3. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    4. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    5. Xiao, Binqing & Yang, Ye & Peng, Xuerong & Fang, Libing, 2019. "Measuring the connectedness of European electricity markets using the network topology of variance decompositions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    6. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Bocart, Fabian Y. R. P. & Hafner, Christian M., 2011. "Econometric analysis of volatile art markets," SFB 649 Discussion Papers 2011-071, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting realized covariances using HAR-type models," Papers 2412.10791, arXiv.org.
    9. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    10. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    11. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    12. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    13. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    14. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    15. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    17. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    18. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    19. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    20. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    21. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting Realized Covariances Using HAR-Type Models," Graz Economics Papers 2024-20, University of Graz, Department of Economics.
    22. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2020. "Large Time-Varying Volatility Models for Electricity Prices," Working Papers No 05/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    23. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    24. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    25. Tsukuda, Yoshihiko & Shimada, Junji & Miyakoshi, Tatsuyoshi, 2017. "Bond market integration in East Asia: Multivariate GARCH with dynamic conditional correlations approach," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 193-213.
    26. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    27. Myšičková, Alena & Song, Song & Majer, Piotr & Mohr, Peter N. C. & Heekeren, Hauke R. & Härdle, Wolfgang Karl, 2011. "Risk patterns and correlated brain activities: Multidimensional statistical analysis of fMRI data with application to risk patterns," SFB 649 Discussion Papers 2011-085, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    28. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    29. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    30. Palzer, Andreas & Westner, Günther & Madlener, Reinhard, 2013. "Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants," Energy Policy, Elsevier, vol. 59(C), pages 143-160.
    31. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    32. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    33. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    34. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    35. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    36. Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    37. Francisco Ortiz Arango & Alma Nelly Montiel Guzmán, 2017. "Transmission of future prices of corn of the Chicago Board of Trade to the Mexican spot market," Contaduría y Administración, Accounting and Management, vol. 62(3), pages 941-957, Julio-Sep.
    38. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    39. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    40. Asger Lunde & Kasper V. Olesen, 2014. "Modeling and Forecasting the Distribution of Energy Forward Returns - Evidence from the Nordic Power Exchange," CREATES Research Papers 2013-19, Department of Economics and Business Economics, Aarhus University.
    41. Fiszeder, Piotr & Fałdziński, Marcin, 2019. "Improving forecasts with the co-range dynamic conditional correlation model," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    42. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    43. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  25. Luc Luc & Arnaud Dufays & Jeroen V.K. Rombouts, 2011. "Marginal Likelihood for Markov-switching and Change-point Garch Models," CREATES Research Papers 2011-41, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    2. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    3. Bauwens, Luc & Carpantier, Jean-François & Dufays, Arnaud, 2015. "Autoregressive moving average infinite hidden markov-switching models," LIDAM Discussion Papers CORE 2015007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    5. Gustavo Cabrera González, 2019. "Modeling and Projection of the Mexican Exchange Rate (Peso/Dollar): a Bayesian Approach for Model Selection," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(2), pages 203-219, Abril-Jun.
    6. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    7. Karanasos, Menelaos & Paraskevopoulos, Alexandros G. & Menla Ali, Faek & Karoglou, Michail & Yfanti, Stavroula, 2014. "Modelling stock volatilities during financial crises: A time varying coefficient approach," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 113-128.
    8. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    9. Xiaoping Zhan & Tiefeng Ma & Shuangzhe Liu & Kunio Shimizu, 2018. "Markov-Switching Linked Autoregressive Model for Non-continuous Wind Direction Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 410-425, September.
    10. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    11. David Ardia & Arnaud Dufays & Carlos Ordás Criado, 2024. "Linking Frequentist and Bayesian Change-Point Methods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(4), pages 1155-1168, October.
    12. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    13. Arnaud Dufays, 2015. "Evolutionary Sequential Monte Carlo Samplers for Change-point Models," Cahiers de recherche 1518, CIRPEE.
    14. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    15. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    16. Gerrit Reher & Bernd Wilfling, 2016. "A nesting framework for Markov-switching GARCH modelling with an application to the German stock market," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 411-426, March.
    17. Monica Billio & Maddalena Cavicchioli, 2013. "�Markov Switching Models for Volatility: Filtering, Approximation and Duality�," Working Papers 2013:24, Department of Economics, University of Venice "Ca' Foscari".
    18. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Jin, Xin & Maheu, John M. & Yang, Qiao, 2022. "Infinite Markov pooling of predictive distributions," Journal of Econometrics, Elsevier, vol. 228(2), pages 302-321.
    20. Seuk Wai Phoong & Seuk Yen Phoong & Shi Ling Khek, 2022. "Systematic Literature Review With Bibliometric Analysis on Markov Switching Model: Methods and Applications," SAGE Open, , vol. 12(2), pages 21582440221, April.
    21. Nima Nonejad, 2019. "Modeling Persistence and Parameter Instability in Historical Crude Oil Price Data Using a Gibbs Sampling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1687-1710, April.
    22. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    23. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," LIDAM Discussion Papers CORE 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    24. Maciej Augustyniak & Mathieu Boudreault & Manuel Morales, 2018. "Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 165-188, March.
    25. Monica Billio & Lorenzo Frattarolo & Hayette Gatfaoui & Philippe de Peretti, 2016. "Clustering in Dynamic Causal Networks as a Measure of Systemic Risk on the Euro Zone," Documents de travail du Centre d'Economie de la Sorbonne 16046r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Sep 2016.
    26. Menelaos Karanasos & Alexandros Paraskevopoulos & Faek Menla Ali & Michail Karoglou & Stavroula Yfanti, 2014. "Modelling Returns and Volatilities During Financial Crises: a Time Varying Coefficient Approach," Papers 1403.7179, arXiv.org.
    27. Wee, Damien C.H. & Chen, Feng & Dunsmuir, William T.M., 2022. "Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo," Econometrics and Statistics, Elsevier, vol. 21(C), pages 50-68.
    28. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    29. Collet, Jerome & Ielpo, Florian, 2018. "Sector spillovers in credit markets," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 267-278.
    30. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Aknouche Abdelhakim & Demmouche Nacer & Dimitrakopoulos Stefanos & Touche Nassim, 2020. "Bayesian analysis of periodic asymmetric power GARCH models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-24, September.
    32. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    33. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    34. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    35. Arnaud Dufays & Maciej Augustyniak & Luc Bauwens, 2016. "A new approach to volatility modeling: the High-Dimensional Markov model," Cahiers de recherche 1609, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    36. D’Amato, Valeria & Levantesi, Susanna & Piscopo, Gabriella, 2022. "Deep learning in predicting cryptocurrency volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    37. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    38. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    39. Donggyu Kim & Minseok Shin, 2023. "Volatility models for stylized facts of high‐frequency financial data," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(3), pages 262-279, May.
    40. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    41. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    42. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    43. Aknouche, Abdelhakim & Demmouche, Nacer & Touche, Nassim, 2018. "Bayesian MCMC analysis of periodic asymmetric power GARCH models," MPRA Paper 91136, University Library of Munich, Germany.
    44. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    45. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.
    46. Griffin, Jim E. & Mitrodima, Gelly, 2020. "A Bayesian quantile time series model for asset returns," LSE Research Online Documents on Economics 105610, London School of Economics and Political Science, LSE Library.

  26. Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric estimation with generated covariates," SFB 649 Discussion Papers 2011-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Roberto Casarin & Chia-Lin Chang & Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez Amaral, 2011. "Risk Management of Risk Under the Basel Accord: A Bayesian Approach to Forecasting Value-at-Risk of VIX Futures," Working Papers in Economics 11/26, University of Canterbury, Department of Economics and Finance.
    3. Serge Darolles & Christian Francq & Sébastien Laurent, 2017. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590471, HAL.
    4. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    6. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    7. Bocart, Fabian Y. R. P. & Hafner, Christian M., 2011. "Econometric analysis of volatile art markets," SFB 649 Discussion Papers 2011-071, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    9. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    10. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate Rotated ARCH Models," Economics Papers 2012-W01, Economics Group, Nuffield College, University of Oxford.
    11. Hautsch, Nikolaus & Schaumburg, Julia & Schienle, Melanie, 2011. "Financial network systemic risk contributions," SFB 649 Discussion Papers 2011-072, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Kurose, Yuta & Omori, Yasuhiro, 2016. "Dynamic equicorrelation stochastic volatility," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 795-813.
    13. Chia-Lin Chang & Juan-à ngel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2011. "The Rise and Fall of S&P500 Variance Futures," KIER Working Papers 795, Kyoto University, Institute of Economic Research.
    14. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    15. Cheridito, Patrick & Horst, Ulrich & Kupper, Michael & Pirvu, Traian A., 2011. "Equilibrium pricing in incomplete markets under translation invariant preferences," SFB 649 Discussion Papers 2011-083, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Horst, Ulrich & Kupper, Michael & Macrina, Andrea & Mainberger, Christoph, 2011. "Continuous equilibrium under base preferences and attainable initial endowments," SFB 649 Discussion Papers 2011-082, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    18. Fiocco, Raffaele, 2011. "Competition and regulation in a differentiated good market," SFB 649 Discussion Papers 2011-084, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    19. Heyne, Gregor & Kupper, Michael & Mainberger, Christoph, 2011. "Minimal supersolutions of BSDEs with lower semicontinuous generations," SFB 649 Discussion Papers 2011-067, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Liu, Wei-han, 2016. "A re-examination of maturity effect of energy futures price from the perspective of stochastic volatility," Energy Economics, Elsevier, vol. 56(C), pages 351-362.
    21. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.
    23. Yaya, OlaOluwa S. & Tumala, Mohammed M. & Udomboso, Christopher G., 2016. "Volatility persistence and returns spillovers between oil and gold prices: Analysis before and after the global financial crisis," Resources Policy, Elsevier, vol. 49(C), pages 273-281.
    24. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2012. "Intra-daily volatility spillovers between the US and German stock markets," Economics Working Papers 2012-06, Christian-Albrechts-University of Kiel, Department of Economics.
    25. Tischer, Sven & Hildebrandt, Lutz, 2011. "Linking corporate reputation and shareholder value using the publication of reputation rankings," SFB 649 Discussion Papers 2011-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    26. Schneider, Dorothee, 2011. "The labor share: A review of theory and evidence," SFB 649 Discussion Papers 2011-069, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  27. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Arnaud Dufays, 2014. "On the conjugacy of off-line and on-line Sequential Monte Carlo Samplers," Working Paper Research 263, National Bank of Belgium.
    2. Arnaud Dufays, 2015. "Evolutionary Sequential Monte Carlo Samplers for Change-point Models," Cahiers de recherche 1518, CIRPEE.
    3. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    4. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  28. BAUWENS, Luc & ROMBOUTS, Jeroen, 2009. "On marginal likelihood computation in change-point models," LIDAM Discussion Papers CORE 2009061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian vector autoregressions," LSE Research Online Documents on Economics 87393, London School of Economics and Political Science, LSE Library.
    2. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    3. Gebrenegus Ghilagaber & Parfait Munezero, 2020. "Bayesian change-point modelling of the effects of 3-points-for-a-win rule in football," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(2), pages 248-264, January.
    4. Catherine Doz & Laurent Ferrara & Pierre-Alain Pionnier, 2020. "Business cycle dynamics after the Great Recession: An Extended Markov-Switching Dynamic Factor Model," Working Papers halshs-02443364, HAL.
    5. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Gründler, Daniel, 2023. "Expectations, structural breaks and the recent surge in inflation," Economics Letters, Elsevier, vol. 233(C).
    7. van den Hout, Ardo & Muniz-Terrera, Graciela & Matthews, Fiona E., 2013. "Change point models for cognitive tests using semi-parametric maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 684-698.
    8. Soosung Hwang & Alexandre Rubesam, 2015. "The disappearance of momentum," The European Journal of Finance, Taylor & Francis Journals, vol. 21(7), pages 584-607, May.
    9. Francesco Zanetti & Philip Liu & Haroon Mumtaz and Konstantinos Theodoridis, 2017. "Changing Macroeconomic Dynamics at the Zero Lower Bound," Economics Series Working Papers 824, University of Oxford, Department of Economics.
    10. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.
    11. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.

  29. BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen V.K., 2007. "Theory and inference for a Markov switching GARCH model," LIDAM Discussion Papers CORE 2007055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    2. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    3. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Accolley, Delali, 2021. "Some Markov-Switching Models for the Toronto Stock Exchange," MPRA Paper 108072, University Library of Munich, Germany.
    5. Gelman, Sergey & Wilfling, Bernd, 2009. "Markov-switching in target stocks during takeover bids," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 745-758, December.
    6. Martin T. Bohl & Badye Essid & Pierre L. Siklos, 2011. "Do Short Selling Restrictions Destabilize Stock Markets? Lessons from Taiwan," Working Papers 112011, Hong Kong Institute for Monetary Research.
    7. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    8. Shen, Zhiwei & Ritter, Matthias, 2015. "Forecasting volatility of wind power production," SFB 649 Discussion Papers 2015-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Monica Billio & Roberto Casarin & Anthony Osuntuyi, 2012. "Efficient Gibbs Sampling for Markov Switching GARCH Models," Working Papers 2012:35, Department of Economics, University of Venice "Ca' Foscari".
    10. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    11. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    12. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    13. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Luca De Angelis & Leonard J. Paas, 2013. "A dynamic analysis of stock markets using a hidden Markov model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1682-1700, August.
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    16. Xiaochun Liu, 2017. "An integrated macro‐financial risk‐based approach to the stressed capital requirement," Review of Financial Economics, John Wiley & Sons, vol. 34(1), pages 86-98, September.
    17. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
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    25. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
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    27. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    28. Ojea Ferreiro, Javier, 2020. "Disentangling the role of the exchange rate in oil-related scenarios for the European stock market," Energy Economics, Elsevier, vol. 89(C).
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    30. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Werner Kristjanpoller & Kevin Michell & Cristian Llanos & Marcel C. Minutolo, 2025. "Incorporating causal notions to forecasting time series: a case study," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-22, December.
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    35. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    36. Samuel Tabot Enow, 2023. "Stock Market Liquidity during Periods of Distress and its Implications: Evidence from International Financial Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 13(1), pages 1-6, January.
    37. Maciej Augustyniak & Mathieu Boudreault & Manuel Morales, 2018. "Maximum Likelihood Estimation of the Markov-Switching GARCH Model Based on a General Collapsing Procedure," Methodology and Computing in Applied Probability, Springer, vol. 20(1), pages 165-188, March.
    38. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    39. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    40. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    41. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    42. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
    43. Shuang Lin & Minke Wang & Zhihong Cheng & Fan He & Jiuhao Chen & Chuanhui Liao & Shengda Zhang, 2022. "Risk Management of Fuel Hedging Strategy Based on CVaR and Markov Switching GARCH in Airline Company," Sustainability, MDPI, vol. 14(22), pages 1-9, November.
    44. Wee, Damien C.H. & Chen, Feng & Dunsmuir, William T.M., 2022. "Likelihood inference for Markov switching GARCH(1,1) models using sequential Monte Carlo," Econometrics and Statistics, Elsevier, vol. 21(C), pages 50-68.
    45. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    46. Hwang, Eunju & Jeon, ChanHyeok, 2024. "Nonnegative GARCH-type models with conditional Gamma distributions and their applications," Computational Statistics & Data Analysis, Elsevier, vol. 198(C).
    47. Szabolcs Blazsek & Anna Downarowicz, 2008. "Regime switching models of hedge fund returns," Faculty Working Papers 12/08, School of Economics and Business Administration, University of Navarra.
    48. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    49. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    50. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    51. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    52. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    53. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    54. Toshiyuki Yam awake & Joseph Sheely & Roberto Serrano & Jiro Hodoshima, 2022. "Comparative Performance of Cryptocurrencies through the Aumann and Serrano Economic Index of Riskiness," Working Papers 2022-007, Brown University, Department of Economics.
    55. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    56. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    57. Pierre-Julien Trombe & Pierre Pinson & Henrik Madsen, 2012. "A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations," Energies, MDPI, vol. 5(3), pages 1-37, March.
    58. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    59. Dohyun Chun & Donggyu Kim, 2021. "State Heterogeneity Analysis of Financial Volatility Using High-Frequency Financial Data," Papers 2102.13404, arXiv.org.
    60. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    61. Aknouche, Abdelhakim & Demouche, Nacer, 2018. "Ergodicity conditions for a double mixed Poisson autoregression," MPRA Paper 88843, University Library of Munich, Germany.
    62. N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.
    63. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    64. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    65. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
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    67. He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
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    70. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    71. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    72. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    73. Kim, Yujin & Hwang, Eunju, 2018. "A dynamic Markov regime-switching GARCH model and its cumulative impulse response function," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 20-30.
    74. Kotsompolis, Giorgos & Konstantakis, Konstantinos N. & Xidonas, Panos & Michaelides, Panayotis G. & Thomakos, Dimitrios D., 2023. "Climate change economics and the determinants of carbon emissions’ futures returns: A regime-driven ARDL model," Finance Research Letters, Elsevier, vol. 58(PC).
    75. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
    76. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.

  30. Winfried Pohlmeier & Luc Bauwens & David Veredas, 2007. "High frequency financial econometrics. Recent developments," ULB Institutional Repository 2013/136223, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. PESTIEAU, Pierre & RACIONERO, Maria, 2015. "Tagging with Leisure Needs," LIDAM Reprints CORE 2747, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    3. Juan D. Moreno-Ternero, 2010. "Voting over piece-wise linear tax methods," Working Papers 10.02, Universidad Pablo de Olavide, Department of Economics.
    4. GILLIS, Nicolas & GLINEUR, François, 2010. "On the geometric interpretation of the nonnegative rank," LIDAM Discussion Papers CORE 2010051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Gautier, Axel & Wauthy, Xavier, 2012. "Competitively neutral universal service obligations," Information Economics and Policy, Elsevier, vol. 24(3), pages 254-261.
    6. GILLIS, Nicolas & GLINEUR, François, 2011. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Reprints CORE 2382, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. MAULEON, Ana & VANNETELBOSCH, Vincent & VERGARI, Cecilia, 2010. "Unions' relative concerns and strikes in wage bargaining," LIDAM Discussion Papers CORE 2010076, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Michel Le Breton & Juan Moreno-Ternero & Alexei Savvateev & Shlomo Weber, 2013. "Stability and fairness in models with a multiple membership," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(3), pages 673-694, August.
    11. GILLIS, Nicolas & GLINEUR, François, 2010. "A multilevel approach for nonnegative matrix factorization," LIDAM Discussion Papers CORE 2010047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. THISSE, Jacques-François, 2011. "Geographical economics: a historical perspective," LIDAM Reprints CORE 2351, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Helmuth Cremer & Firouz Gahvari & Pierre Pestieau, 2009. "Fertility, Human Capital Accumulation, and the Pension System," CESifo Working Paper Series 2736, CESifo.
    14. Marie-Louise Leroux & Grégory Ponthière, 2013. "Utilitarianism and unequal longevities: A remedy?," Post-Print hal-00813226, HAL.
    15. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    17. MANZI, Jorge & SAN MARTIN, Ernesto & VAN BELLEGEM, Sébastien, 2010. "School system evaluation by value-added analysis under endogeneity," LIDAM Discussion Papers CORE 2010046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Bouezmarni, Taoufik & Van Bellegem, Sébastien, 2009. "Nonparametric Beta Kernel Estimator for Long Memory Time Series," TSE Working Papers 09-082, Toulouse School of Economics (TSE).
    19. Bauwens, Luc & Korobilis, Dimitris & Koop, Gary & Rombouts, Jeroen V.K., 2011. "A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models," SIRE Discussion Papers 2011-25, Scottish Institute for Research in Economics (SIRE).
    20. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. DI SUMMA, Marco & WOLSEY, Laurence, 2010. "Mixing sets linked by bidirected paths," LIDAM Discussion Papers CORE 2010063, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    23. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    24. GRANDJEAN, Gilles, 2011. "Risk-sharing networks and farsighted stability," LIDAM Discussion Papers CORE 2011014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Per J. AGRELL & Axel GAUTIER, 2017. "A theory of soft capture," LIDAM Reprints CORE 2863, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    26. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    27. Vandenbussche, Hylke & Song, Huasheng & ,, 2010. "Innovation, antidumping, and retaliation," CEPR Discussion Papers 7916, C.E.P.R. Discussion Papers.
    28. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    29. BRECHET, Thierry & JOUVET, Pierre-André & ROTILLON, Gilles, 2013. "Tradable pollution permits in dynamic general equilibrium: can optimality and acceptability be reconciled?," LIDAM Reprints CORE 2478, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. LEROUX, Marie - Louise & PESTIEAU, Pierre, 2010. "The political economy of derived pension rights," LIDAM Discussion Papers CORE 2010048, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. UNO, Hiroshi, 2011. "Nested potentials and robust equilibria," LIDAM Discussion Papers CORE 2011009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    32. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2010. "Iterative Regularization in Nonparametric Instrumental Regression," IDEI Working Papers 630, Institut d'Économie Industrielle (IDEI), Toulouse.
    33. RAMAEKERS, Eve, 2010. "Fair allocation of indivisible goods among two agents," LIDAM Discussion Papers CORE 2010087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    34. CALCIANO, Filippo L., 2011. "The complementarity foundations of industrial organization," LIDAM Discussion Papers CORE 2011005, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Brownlees Christian T. & Vannucci Marina, 2013. "A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 21-46, February.
    36. LUTTENS, Roland Iwan, 2010. "Lower bounds rule!," LIDAM Discussion Papers CORE 2010069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    37. Katarzyna Bień-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 117-142, June.
    38. STEPHAN, Rüdiger, 2010. "An extension of disjunctive programming and its impact for compact tree formulations," LIDAM Discussion Papers CORE 2010045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    39. GABSZEWICZ, Jean & TAROLA, Ornella, 2010. "Product innovation and market acquisition of firms," LIDAM Discussion Papers CORE 2010078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    40. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    41. DENUIT, Michel & EECKHOUDT, Louis & TSETLIN, Ilia & WINKLER, Robert L., 2010. "Multivariate concave and convex stochastic dominance," LIDAM Discussion Papers CORE 2010044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    42. HINDRIKS, Jean & VERSCHELDE, Marijn & RAYP, Glenn & SCHOORS, Koen, 2010. "School autonomy and educational performance: within-country evidence," LIDAM Discussion Papers CORE 2010082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  31. BAUWENS, Luc & MION, Giordano & THISSE, Jacques-François, 2007. "The resistible decline of European science," LIDAM Discussion Papers CORE 2007092, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Quentin Max David, 2013. "Determinants of Research Production at Top Universities," Working Papers TIMES² 2014-007, ULB -- Universite Libre de Bruxelles.
    2. Shahid Yusuf & Kaoru Nabeshima, 2009. "Growth through Innovation : An Industrial Strategy for Shanghai," World Bank Publications - Reports 18613, The World Bank Group.
    3. Sonia M. R. Vasconcelos & Martha M. Sorenson & Jacqueline Leta, 2009. "A new input indicator for the assessment of science & technology research?," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 217-230, July.
    4. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2017. "Economists, Research Performance and National Inbreeding: North Versus South," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(1), pages 145-163, February.
    5. Daraio, Cinzia & Moed, Henk F., 2011. "Is Italian science declining?," Research Policy, Elsevier, vol. 40(10), pages 1380-1392.
    6. Raquel Carrasco & Javier Ruiz-Castillo, 2019. "Spatial mobility in elite academic institutions in economics: the case of Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 141-172, June.
    7. Carillo, Maria Rosaria & Papagni, Erasmo & Sapio, Alessandro, 2013. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 47(C), pages 25-36.
    8. Conti, Annamaria & Gaule, Patrick, 2011. "Is the US outperforming Europe in university technology licensing? A new perspective on the European Paradox," Research Policy, Elsevier, vol. 40(1), pages 123-135, February.
    9. Mathieu Goudard & Michel Lubrano, 2013. "Human Capital, Social Capital And Scientific Research In Europe: An Application Of Linear Hierarchical Models," Manchester School, University of Manchester, vol. 81(6), pages 876-903, December.
    10. Stelios Katranidis & Theodore Panagiotidis & Kostas Zontanos, 2022. "A note on the relative productivity drivers of economists: a probit/logit approach for six European countries," Economic Change and Restructuring, Springer, vol. 55(4), pages 2171-2178, November.
    11. Polt, Wolfgang & Berger, Martin & Boekholt, Patries & Cremers, Katrin & Egeln, Jürgen & Gassler, Helmut & Hofer, Reinhold & Rammer, Christian & Deuten, Jasper & Good, Barbara & Warta, Katharina, 2010. "Das deutsche Forschungs- und Innovationssystem: Ein internationaler Sytemvergleich zur Rolle von Wissenschaft, Interaktionen und Governance für die technologische Leistungsfähigkeit," Studien zum deutschen Innovationssystem 11-2010, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    12. Nagar, Jay Prakash & Breschi, Stefano & Fosfuri, Andrea, 2024. "ERC science and invention: Does ERC break free from the EU Paradox?," Research Policy, Elsevier, vol. 53(8).
    13. Panaretos, John & Malesios, Chrisovalandis, 2012. "Influential Mathematicians: Birth, Education and Affiliation," MPRA Paper 68046, University Library of Munich, Germany.
    14. Maria Rosaria Carillo & Erasmo Papagni & Alessandro Sapio, 2012. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise (2001-2003)," Discussion Papers 4_2012, CRISEI, University of Naples "Parthenope", Italy.
    15. David Emanuel Andersson & Åke E. Andersson & Björn Hårsman & Xiyi Yang, 2020. "The geography of science in 12 European countries: a NUTS2-level analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1099-1125, August.
    16. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Geographic mobility and research productivity in a selection of top world economics departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 241-265, April.
    17. Christian Reiner, 2010. "Brain competition policy as a new paradigm of regional policy: A European perspective," Papers in Regional Science, Wiley Blackwell, vol. 89(2), pages 449-461, June.
    18. Argyropoulou, Maria & Soderquist, Klas Eric & Ioannou, George, 2019. "Getting out of the European Paradox trap: Making European research agile and challenge driven," European Management Journal, Elsevier, vol. 37(1), pages 1-5.

  32. BAUWENS, Luc & GALLI, Fausto, 2007. "Efficient importance sampling for ML estimation of SCD models," LIDAM Discussion Papers CORE 2007053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
    2. Tore Selland KLEPPE & Jun YU & Hans J. SKAUG, 2009. "Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers 20-2009, Singapore Management University, School of Economics.
    3. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    4. Kleppe, Tore Selland & Liesenfeld, Roman, 2011. "Efficient high-dimensional importance sampling in mixture frameworks," Economics Working Papers 2011-11, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    6. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
    7. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Kleppe, Tore Selland & Liesenfeld, Roman, 2014. "Efficient importance sampling in mixture frameworks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 449-463.
    9. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    10. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Bekierman Jeremias & Gribisch Bastian, 2016. "Estimating stochastic volatility models using realized measures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(3), pages 279-300, June.
    12. Skaug, Hans J. & Yu, Jun, 2014. "A flexible and automated likelihood based framework for inference in stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 642-654.
    13. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    14. Pastorello, S. & Rossi, E., 2010. "Efficient importance sampling maximum likelihood estimation of stochastic differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2753-2762, November.
    15. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    16. Siem Jan Koopman & Andre Lucas & Marcel Scharth, 2011. "Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models," Tinbergen Institute Discussion Papers 11-057/4, Tinbergen Institute, revised 27 Jan 2012.
    17. Zhongxian Men & Adam W. Kolkiewicz & Tony S. Wirjanto, 2013. "Bayesian Inference of Asymmetric Stochastic Conditional Duration Models," Working Paper series 28_13, Rimini Centre for Economic Analysis.

  33. BAUWENS, Luc & STORTI, Giuseppe, 2007. "A component GARCH model with time varying weights," LIDAM Discussion Papers CORE 2007019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    3. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    4. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2014. "Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification," CREATES Research Papers 2014-13, Department of Economics and Business Economics, Aarhus University.
    5. Jamal Bouoiyour & Refk Selmi, 2014. "Commodity price uncertainty and manufactured exports in Morocco and Tunisia: Some insights from a novel GARCH model," Post-Print hal-01879687, HAL.
    6. Boudt, Kris & Daníelsson, Jón & Laurent, Sébastien, 2013. "Robust forecasting of dynamic conditional correlation GARCH models," International Journal of Forecasting, Elsevier, vol. 29(2), pages 244-257.
    7. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    8. Bouoiyour, Jamal & Selmi, Refk, 2013. "The controversial link between exchange rate volatility and exports: Evidence from Tunisian case," MPRA Paper 49133, University Library of Munich, Germany, revised Mar 2013.
    9. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
    10. Bouoiyour, Jamal & Selmi, Refk, 2013. "Nonlinearities and the nexus between inflation and inflation uncertainty in Egypt: New evidence from wavelets transform framework," MPRA Paper 52414, University Library of Munich, Germany.
    11. Jamal Bouoiyour & Refk Selmi, 2016. "Bitcoin: a beginning of a new phase?," Economics Bulletin, AccessEcon, vol. 36(3), pages 1430-1440.
    12. Henryk Gurgul & Roland Mestel & Robert Syrek, 2017. "MIDAS models in banking sector – systemic risk comparison," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 18(2), pages 165-181.
    13. Bouoiyour, Jamal & Miftah, Amal & Selmi, Refk, 2014. "Do Financial Flows raise or reduce Economic growth Volatility? Some Lessons from Moroccan case," MPRA Paper 57258, University Library of Munich, Germany.
    14. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    15. Mobarek, Asma & Muradoglu, Gulnur & Mollah, Sabur & Hou, Ai Jun, 2016. "Determinants of time varying co-movements among international stock markets during crisis and non-crisis periods," Journal of Financial Stability, Elsevier, vol. 24(C), pages 1-11.
    16. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    18. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Becker Ralf & Clements Adam E & Hurn Stan, 2011. "Semi-Parametric Forecasting of Realized Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-23, May.
    20. Bouoiyour, Jamal & Selmi, Refk, 2015. "Bitcoin Price: Is it really that New Round of Volatility can be on way?," MPRA Paper 65580, University Library of Munich, Germany.
    21. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    22. Stefano Grassi & Paolo Santucci de Magistris, 2013. "It’s all about volatility (of volatility): evidence from a two-factor stochastic volatility model," CREATES Research Papers 2013-03, Department of Economics and Business Economics, Aarhus University.
    23. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    24. N. Alemohammad & S. Rezakhah & S. H. Alizadeh, 2020. "Markov switching asymmetric GARCH model: stability and forecasting," Statistical Papers, Springer, vol. 61(3), pages 1309-1333, June.
    25. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.

  34. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Braione, Manuela & Scholtes, Nicolas K., 2014. "Construction of value-at-risk forecasts under different distributional assumptions within a BEKK framework," LIDAM Discussion Papers CORE 2014059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bonga-Bonga, Lumengo & Nleya, Lebogang, 2016. "Assessing portfolio market risk in the BRICS economies: use of multivariate GARCH models," MPRA Paper 75809, University Library of Munich, Germany.
    3. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.

  35. BAUWENS, Luc, 2006. "Econometric analysis of intra-daily trading activity on the Tokyo Stock Exchange," LIDAM Reprints CORE 1862, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    2. Petra Tomanová & Vladimír Holý, 2021. "Clustering of arrivals in queueing systems: autoregressive conditional duration approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 859-874, September.
    3. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    4. Francisco Blasques & Vladimir Holy & Petra Tomanova, 2019. "Zero-Inflated Autoregressive Conditional Duration Model for Discrete Trade Durations with Excessive Zeros," Tinbergen Institute Discussion Papers 19-004/III, Tinbergen Institute.

  36. BAUWENS, Luc & HAFNER, Christian & ROMBOUTS, Jeroen, 2006. "Multivariate mixed normal conditional heteroskedasticity," LIDAM Discussion Papers CORE 2006012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    3. Simon A. BRODA & Markus HAAS & Jochen KRAUSE & Marc S. PAOLELLA & Sven C. STEUDE, 2011. "Stable Mixture GARCH Models," Swiss Finance Institute Research Paper Series 11-39, Swiss Finance Institute.
    4. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    5. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    6. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    7. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    8. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    10. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    11. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    12. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Mitica Pepi, 2022. "The Impact of the Global Pandemic Crisis on East and Central EU Stock Markets," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 963-968, September.
    15. Abdelhakim Aknouche & Nadia Rabehi, 2010. "On an independent and identically distributed mixture bilinear time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 113-131, March.
    16. Rombouts, Jeroen V.K. & Stentoft, Lars, 2011. "Multivariate option pricing with time varying volatility and correlations," Journal of Banking & Finance, Elsevier, vol. 35(9), pages 2267-2281, September.
    17. Rossi, E. & Spazzini, F., 2010. "Model and distribution uncertainty in multivariate GARCH estimation: A Monte Carlo analysis," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2786-2800, November.
    18. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    19. Bentarzi, M. & Hamdi, F., 2008. "Mixture periodic autoregressive conditional heteroskedastic models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 1-16, September.
    20. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    21. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    22. Maddalena Cavicchioli, 2021. "Statistical inference for mixture GARCH models with financial application," Computational Statistics, Springer, vol. 36(4), pages 2615-2642, December.
    23. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    24. Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    25. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.
    26. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    27. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
    28. Anghelache, Gabriela Victoria & Kralik, Lorand Istvan & Acatrinei, Marius & Pete, Stefan, 2014. "Influence of the EU Accession Process and the Global Crisis on the CEE Stock Markets: A Multivariate Correlation Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 35-52, June.
    29. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.

  37. BAUWENS, Luc & LUBRANO, Michel, 2006. "Bayesian inference in dynamic disequilibrium models: an application to the Polish credit market," LIDAM Discussion Papers CORE 2006050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Claessens, Stijn & Sakho, Yaye Seynabou, 2013. "Assessing firms'financing constraints in Brazil," Policy Research Working Paper Series 6624, The World Bank.
    2. Jaunius Karmelavičius & Ieva Mikaliūnaitė-Jouvanceau & Austėja Petrokaitė, 2022. "Housing and credit misalignments in a two-market disequilibrium framework," Bank of Lithuania Occasional Paper Series 42, Bank of Lithuania.
    3. Baird, Matthew & Daugherty, Lindsay & Kumar, Krishna B., 2019. "Improving Estimation of Labor Market Disequilibrium Using Shortage Indicators, with an Application to the Market for Anesthesiologists," IZA Discussion Papers 12129, Institute of Labor Economics (IZA).
    4. Matthew Baird & Lindsay Daugherty & Krishna Kumar, 2017. "Improving Estimation of Labor Market Disequilibrium through Inclusion of Shortage Indicators," CINCH Working Paper Series 1701, Universitaet Duisburg-Essen, Competent in Competition and Health.
    5. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.
    6. Paolo Del Giovane & Andrea Nobili & Federico M. Signoretti, 2017. "Assessing the Sources of Credit Supply Tightening: Was the Sovereign Debt Crisis Different from Lehman?," International Journal of Central Banking, International Journal of Central Banking, vol. 13(2), pages 197-234, June.
    7. Aloysius Deno Hervino, 2011. "Avoiding risk in working capital credit distribution in Indonesia," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 3(2), pages 199-210, April.
    8. Carpenter, Seth & Demiralp, Selva & Eisenschmidt, Jens, 2014. "The effectiveness of non-standard monetary policy in addressing liquidity risk during the financial crisis: The experiences of the Federal Reserve and the European Central Bank," Journal of Economic Dynamics and Control, Elsevier, vol. 43(C), pages 107-129.
    9. Bofinger, Peter & Maas, Daniel & Ries, Mathias, 2017. "A model of the market for bank credit: The case of Germany," W.E.P. - Würzburg Economic Papers 98, University of Würzburg, Department of Economics.
    10. Tamini, Arnaud & Petey, Joël, 2021. "Hoarding of reserves in the banking industry: Explaining the African paradox," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 214-225.
    11. Schmidt, Torsten & Zwick, Lina, 2012. "In Search for a Credit Crunch in Germany," Ruhr Economic Papers 361, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

  38. BAUWENS, Luc & SUCARRAT, Genaro, 2006. "General to specific modelling of exchange rate volatility: a forecast evaluation," LIDAM Discussion Papers CORE 2006021, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2011. "Mortality density forecasts: An analysis of six stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 48(3), pages 355-367, May.
    2. Chortareas, Georgios & Jiang, Ying & Nankervis, John. C., 2011. "Forecasting exchange rate volatility using high-frequency data: Is the euro different?," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1089-1107, October.
    3. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    4. Tennant, David, 2011. "Why do people risk exposure to Ponzi schemes? Econometric evidence from Jamaica," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 328-346, July.
    5. Sucarrat, Genaro, 2009. "Forecast Evaluation of Explanatory Models of Financial Variability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-33.
    6. Sucarrat, Genaro, 2009. "Econometric reduction theory and philosophy," UC3M Working papers. Economics we091005, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    8. Carlisle E. Moody & Thomas B. Marvell, 2010. "On the Choice of Control Variables in the Crime Equation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 696-715, October.
    9. Kim Karlsson, Hyunjoo & Li, Yushu, 2024. "Investigation of Swedish krona exchange rate volatility by APARCH-Support Vector Regression," Working Papers in Economics and Statistics 10/2024, Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    10. Philipp Otto, 2022. "A Multivariate Spatial and Spatiotemporal ARCH Model," Papers 2204.12472, arXiv.org.
    11. Alvaro Escribano & Genaro Sucarrat, 2011. "Automated model selection in finance: General-to-speci c modelling of the mean and volatility speci cations," Working Papers 2011-09, Instituto Madrileño de Estudios Avanzados (IMDEA) Ciencias Sociales.
    12. Holger Fink & Andreas Fuest & Henry Port, 2018. "The Impact of Sovereign Yield Curve Differentials on Value-at-Risk Forecasts for Foreign Exchange Rates," Risks, MDPI, vol. 6(3), pages 1-19, August.
    13. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    14. Clavero, Borja, 2017. "A contribution to the Quantity Theory of Disaggregated Credit," MPRA Paper 76657, University Library of Munich, Germany.
    15. Panday, Anjan, 2015. "Impact of monetary policy on exchange market pressure: The case of Nepal," Journal of Asian Economics, Elsevier, vol. 37(C), pages 59-71.
    16. Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    17. J. James Reade & Ulrich Volz, 2011. "From the General to the Specific," Discussion Papers 11-18, Department of Economics, University of Birmingham.
    18. Sucarrat, Genaro, 2009. "Automated financial multi-path GETS modelling," UC3M Working papers. Economics we093620, Universidad Carlos III de Madrid. Departamento de Economía.
    19. Lyonnet, Victor & Werner, Richard, 2012. "Lessons from the Bank of England on ‘quantitative easing’ and other ‘unconventional’ monetary policies," International Review of Financial Analysis, Elsevier, vol. 25(C), pages 94-105.
    20. Cui, Jin & In, Francis & Maharaj, Elizabeth Ann, 2016. "What drives the Libor–OIS spread? Evidence from five major currency Libor–OIS spreads," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 358-375.

  39. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Florian Heiss, 2008. "Sequential numerical integration in nonlinear state space models for microeconometric panel data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 373-389.
    2. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    3. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    4. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    5. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," LIDAM Discussion Papers CORE 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Drew Creal & Siem Jan Koopman & André Lucas, 2008. "A General Framework for Observation Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 08-108/4, Tinbergen Institute.
    7. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    8. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    10. Siem Jan Koopman & André Lucas & Marcel Scharth, 2016. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 97-110, March.
    11. Marco Minozzo & Silvia Centanni, 2012. "Monte Carlo likelihood inference for marked doubly stochastic Poisson processes with intensity driven by marked point processes," Working Papers 11/2012, University of Verona, Department of Economics.
    12. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    13. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    14. Zhang, Xuan & Kim, Minjoo & Yan, Cheng & Zhao, Yang, 2024. "Default dependence in the insurance and banking sectors: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    15. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    16. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
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    27. Blazsek, Szabolcs, 2012. "Patents, secret innovations and firm's rate of return : differential effects of the innovation leader," UC3M Working papers. Economics we1202, Universidad Carlos III de Madrid. Departamento de Economía.
    28. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
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    32. Kohler, Alexander & von Wyss, Rico, 2012. "Where does Information Processing in a Fragmented Market Take Place? – Evidence from the Swiss Stock Market after MiFID," Working Papers on Finance 1209, University of St. Gallen, School of Finance.
    33. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    34. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    35. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
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    Cited by:

    1. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
    2. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    3. Maxime Morariu-Patrichi & Mikko S. Pakkanen, 2018. "State-dependent Hawkes processes and their application to limit order book modelling," Papers 1809.08060, arXiv.org, revised Sep 2021.
    4. Adam Clements & Yin Liao, 2014. "The role in index jumps and cojumps in forecasting stock index volatility: Evidence from the Dow Jones index," NCER Working Paper Series 101, National Centre for Econometric Research.
    5. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    6. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    7. Bacry, E. & Delattre, S. & Hoffmann, M. & Muzy, J.F., 2013. "Some limit theorems for Hawkes processes and application to financial statistics," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2475-2499.
    8. Angelos Dassios & Jiwook Jang & Hongbiao Zhao, 2019. "A Generalised CIR Process with Externally-Exciting and Self-Exciting Jumps and Its Applications in Insurance and Finance," Risks, MDPI, vol. 7(4), pages 1-18, October.
    9. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    10. Pietro Fodra & Huy^en Pham, 2013. "High frequency trading and asymptotics for small risk aversion in a Markov renewal model," Papers 1310.1756, arXiv.org, revised Jan 2015.
    11. Hainaut, Donatien, 2016. "Impact of volatility clustering on equity indexed annuities," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 367-381.
    12. Fan, Lina & Yang, Hao & Zhai, Jia & Zhang, Xiaotao, 2023. "Forecasting stock volatility during the stock market crash period: The role of Hawkes process," Finance Research Letters, Elsevier, vol. 55(PA).
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    14. Roueff, Francois & von Sachs, Rainer & Sansonnet, Laure, 2015. "Time-frequency analysis of locally stationary Hawkes processes," LIDAM Discussion Papers ISBA 2015011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. D’Amico, Guglielmo & Petroni, Filippo, 2018. "Copula based multivariate semi-Markov models with applications in high-frequency finance," European Journal of Operational Research, Elsevier, vol. 267(2), pages 765-777.
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    33. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    34. Adam E Clements & Yin Liao, 2013. "Modeling and forecasting realized volatility: getting the most out of the jump component," NCER Working Paper Series 93, National Centre for Econometric Research.
    35. Angelos Dassios & Xin Dong, 2014. "Stationarity of Bivariate Dynamic Contagion Processes," Papers 1405.5842, arXiv.org.
    36. Monira Essa Aloud, 2016. "Time Series Analysis Indicators under Directional Changes: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 55-64.
    37. Anatoliy Swishchuk, 2021. "Modelling of Limit Order Books by General Compound Hawkes Processes with Implementations," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 399-428, March.
    38. Ketelbuters, John John & Hainaut, Donatien, 2021. "Time-Consistent Evaluation of Credit Risk with Contagion," LIDAM Discussion Papers ISBA 2021004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    39. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
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    42. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    43. Marcello Rambaldi & Vladimir Filimonov & Fabrizio Lillo, 2016. "Detection of intensity bursts using Hawkes processes: an application to high frequency financial data," Papers 1610.05383, arXiv.org.
    44. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
    45. Hamza Bodor & Laurent Carlier, 2024. "A Novel Approach to Queue-Reactive Models: The Importance of Order Sizes," Papers 2405.18594, arXiv.org.
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    47. V. Filimonov & D. Sornette, 2015. "Apparent criticality and calibration issues in the Hawkes self-excited point process model: application to high-frequency financial data," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1293-1314, August.
    48. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    49. Siakoulis, Vasilios, 2015. "Modeling bank default intensity in the USA using autoregressive duration models," MPRA Paper 64526, University Library of Munich, Germany.
    50. Hainaut, Donatien, 2016. "A bivariate Hawkes process for interest rate modeling," Economic Modelling, Elsevier, vol. 57(C), pages 180-196.
    51. Álvaro Cartea, 2013. "Derivatives pricing with marked point processes using tick-by-tick data," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 111-123, January.
    52. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    53. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    54. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    55. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    56. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    57. Jang, Jiwook & Dassios, Angelos, 2013. "A bivariate shot noise self-exciting process for insurance," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 524-532.
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    59. Zhu, Lingjiong, 2013. "Moderate deviations for Hawkes processes," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 885-890.
    60. Ioane Muni Toke, 2011. ""Market making" behaviour in an order book model and its impact on the bid-ask spread," Post-Print hal-01705266, HAL.
    61. Liu, Chenguang, 2020. "Statistical inference for a partially observed interacting system of Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 130(9), pages 5636-5694.
    62. Chavez-Demoulin, V. & McGill, J.A., 2012. "High-frequency financial data modeling using Hawkes processes," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3415-3426.
    63. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    64. Jiwook Jang & Rosy Oh, 2020. "A Bivariate Compound Dynamic Contagion Process for Cyber Insurance," Papers 2007.04758, arXiv.org.
    65. Giuseppe Arbia & Michele Di Marcantonio, 2015. "Forecasting Interest Rates Using Geostatistical Techniques," Econometrics, MDPI, vol. 3(4), pages 1-28, November.
    66. Anatoliy Swishchuk & Aiden Huffman, 2018. "General Compound Hawkes Processes in Limit Order Books," Papers 1812.02298, arXiv.org.
    67. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    68. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.
    69. Dassios, Angelos & Jang, Jiwook & Zhao, Hongbiao, 2019. "A generalised CIR process with externally-exciting and self-exciting jumps and its applications in insurance and finance," LSE Research Online Documents on Economics 102043, London School of Economics and Political Science, LSE Library.
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    72. Samuel N. Cohen & Robert J. Elliott, 2013. "Filters and smoothers for self-exciting Markov modulated counting processes," Papers 1311.6257, arXiv.org.
    73. E. Bacry & K. Dayri & J. F. Muzy, 2011. "Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data," Papers 1112.1838, arXiv.org.
    74. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    79. Giacomo Bormetti & Lucio Maria Calcagnile & Michele Treccani & Fulvio Corsi & Stefano Marmi & Fabrizio Lillo, 2015. "Modelling systemic price cojumps with Hawkes factor models," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1137-1156, July.
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  41. BAUWENS, Luc & PREMINGER, Arie & ROMBOUTS, Jeroen, 2006. "Regime switching GARCH models," LIDAM Discussion Papers CORE 2006011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    2. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. He, Zhongfang & Maheu, John M., 2010. "Real time detection of structural breaks in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2628-2640, November.
    4. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    5. Chunming Yuan, 2008. "The Exchange Rate and Macroeconomic Determinants: Time-Varying Transitional Dynamics," UMBC Economics Department Working Papers 09-114, UMBC Department of Economics, revised 01 Nov 2009.
    6. Bauwens Luc & Storti Giuseppe, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-33, May.
    7. Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer.
    8. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    9. Nyberg, Henri, 2010. "QR-GARCH-M Model for Risk-Return Tradeoff in U.S. Stock Returns and Business Cycles," MPRA Paper 23724, University Library of Munich, Germany.
    10. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    11. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    12. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    13. Chunming Yuan, 2008. "Forecasting Exchange Rates: The Multi-State Markov-Switching Model with Smoothing," UMBC Economics Department Working Papers 09-115, UMBC Department of Economics, revised 01 Nov 2009.
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    16. Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Time-varying mixture GARCH models and asymmetric volatility," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 602-623.
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    19. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
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  42. Luc Bauwens & David Veredas & Winfried Pohlmeier, 2005. "High frequency finance," ULB Institutional Repository 2013/136220, ULB -- Universite Libre de Bruxelles.

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    1. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Working Papers hal-00603385, HAL.
    2. Lillie Lam & Laurence Fung & Ip-wing Yu, 2009. "Forecasting a Large Dimensional Covariance Matrix of a Portfolio of Different Asset Classes," Working Papers 0901, Hong Kong Monetary Authority.
    3. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Papers 1106.5040, arXiv.org.
    4. Cosma, Antonio & Galli, Fausto, 2014. "A non parametric ACD model," MPRA Paper 53990, University Library of Munich, Germany.
    5. Yuanhua Feng & Sarah Forstinger & Christian Peitz, 2013. "On the iterative plug-in algorithm for estimating diurnal patterns of financial trade durations," Working Papers CIE 66, Paderborn University, CIE Center for International Economics.
    6. Tsunehiro Ishihara & Yasuhiro Omori & Manabu Asai, 2011. "Matrix Exponential Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-812, CIRJE, Faculty of Economics, University of Tokyo.
    7. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.

  43. BAUWENS, Luc & LAURENT, Sébastien, 2005. "A new class of multivariate skew densities, with application to generalized autoregressive conditional heteroscedasticity models," LIDAM Reprints CORE 1793, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    1. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    2. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    3. Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 69-94, January.
    4. Yu, Honghai & Du, Donglei & Fang, Libing & Yan, Panpan, 2018. "Risk contribution of crude oil to industry stock returns," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 179-199.
    5. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    6. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    7. Luis García-Álvarez & Richard Luger, 2011. "Dynamic Correlations, Estimation Risk, and Porfolio Management During the Financial Crisis," Working Papers wp2011_1103, CEMFI, revised Sep 2011.
    8. Kinateder, Harald & Campbell, Ross & Choudhury, Tonmoy, 2021. "Safe haven in GFC versus COVID-19: 100 turbulent days in the financial markets," Finance Research Letters, Elsevier, vol. 43(C).
    9. Julio Mulero & Miguel A. Sordo & Marilia C. de Souza & Alfonso Suárez‐LLorens, 2017. "Two stochastic dominance criteria based on tail comparisons," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(6), pages 575-589, November.
    10. Abdul Hakim & Michael McAleer, 2009. "VaR Forecasts and Dynamic Conditional Correlations for Spot and Futures Returns on Stocks and Bonds," CIRJE F-Series CIRJE-F-676, CIRJE, Faculty of Economics, University of Tokyo.
    11. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    12. Javier Mencía & Enrique Sentana, 2008. "Multivariate Location-Scale Mixtures of Normals and Mean-Variance-skewness Portfolio Allocation," Working Papers wp2008_0805, CEMFI.
    13. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
    14. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    15. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    16. C. Alexander & M. Coulon & Y. Han & X. Meng, 2024. "Evaluating the discrimination ability of proper multi-variate scoring rules," Annals of Operations Research, Springer, vol. 334(1), pages 857-883, March.
    17. Conrad, Christian & Karanasos, Menelaos & Zeng, Ning, 2011. "Multivariate fractionally integrated APARCH modeling of stock market volatility: A multi-country study," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 147-159, January.
    18. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
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    23. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
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    29. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
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    36. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
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  44. BAUWENS, Luc & RIME, Dagfinn & SUCARRAT, Genaro, 2005. "Exchange rate volatility and the mixture of distribution hypothesis," LIDAM Discussion Papers CORE 2005058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Michael Frömmel & Eyup Kadioglu, 2023. "Impact of trading hours extensions on foreign exchange volatility: intraday evidence from the Moscow exchange," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    2. Munazza Jabeen & Saud Ahmad Khan, 2014. "Modelling Exchange Rate Volatility by Macroeconomic Fundamentals in Pakistan," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 58-76, September.
    3. POPOVICI, Oana Cristina, 2015. "A Volatility Analysis Of The Euro Currency And The Bond Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 67-79.
    4. M. Frömmel & A. Mende & L. Menkhoff, 2007. "Order Flows, News, and Exchange Rate Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/474, Ghent University, Faculty of Economics and Business Administration.
    5. Luc, BAUWENS & Genaro, SUCARRAT, 2006. "General to Specific Modelling of Exchange Rate Volatility : a Forecast Evaluation," Discussion Papers (ECON - Département des Sciences Economiques) 2006013, Université catholique de Louvain, Département des Sciences Economiques.
    6. Saïd Souam & Faycal Hamdi, 2018. "Mixture Periodic GARCH Models: Theory and Applications," Post-Print hal-01589209, HAL.
    7. Olivier Damette & Stéphane Goutte, 2015. "Tobin tax and trading volume tightening: a reassessment," Post-Print hal-01203841, HAL.
    8. Olivier Damette, 2016. "Mixture distribution hypothesis and the impact of a Tobin tax on exchange rate volatility : a reassessment," Post-Print hal-01601393, HAL.
    9. Olivier Damette & Beum-Jo Park, 2015. "Tobin Tax and Volatility: A Threshold Quantile Autoregressive Regression Framework," Review of International Economics, Wiley Blackwell, vol. 23(5), pages 996-1022, November.
    10. Jakree Koosakul & Ilhyock Shim, 2017. "The beneficial aspect of FX volatility for market liquidity," BIS Working Papers 629, Bank for International Settlements.
    11. Francis Bismans & Olivier Damette, 2012. "La taxe Tobin : une synthèse des travaux basés sur la théorie des jeux et l’économétrie," Working Papers of BETA 2012-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    12. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Rime, Dagfinn & Sucarrat, Genaro, 2007. "Exchange rate variability, market activity and heterogeneity," UC3M Working papers. Economics we077039, Universidad Carlos III de Madrid. Departamento de Economía.
    14. Francq, Christian & Sucarrat, Genaro, 2017. "An equation-by-equation estimator of a multivariate log-GARCH-X model of financial returns," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 16-32.
    15. Ewa M. Syczewska, 2014. "The EURPLN, DAX and WIG20: the Granger causality tests before and during the crisis," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 14, pages 93-104.
    16. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    17. Sensoy, Ahmet & Serdengeçti, Süleyman, 2019. "Intraday volume-volatility nexus in the FX markets: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 1-12.
    18. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2018. "Public information arrival, price discovery and dynamic correlations in the Chinese renminbi markets," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 168-186.
    19. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    20. Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Angelo Ranaldo & Paolo Santucci de Magistris, 2018. "Trading Volume, Illiquidity and Commonalities in FX Markets," Working Papers on Finance 1823, University of St. Gallen, School of Finance, revised Oct 2019.

  45. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2005. "Bayesian inference for the mixed conditional heteroskedasticity model," LIDAM Discussion Papers CORE 2005085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    3. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    4. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    5. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    6. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    7. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 517-539, November.
    8. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    9. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  46. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," LIDAM Reprints CORE 1731, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, July.
    2. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    3. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & van DIJK, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," LIDAM Reprints CORE 1922, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Waggoner, Daniel F. & Wu, Hongwei & Zha, Tao, 2016. "Striated Metropolis–Hastings sampler for high-dimensional models," Journal of Econometrics, Elsevier, vol. 192(2), pages 406-420.
    5. McCausland, William J., 2008. "On Bayesian analysis and computation for functions with monotonicity and curvature restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 484-507, January.
    6. Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012. "A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
    7. Tsionas, Mike G., 2019. "Multi-objective optimization using statistical models," European Journal of Operational Research, Elsevier, vol. 276(1), pages 364-378.
    8. Rodney Strachan & Herman K. van Dijk, "undated". "Bayesian Model Averaging in Vector Autoregressive Processes with an Investigation of Stability of the US Great Ratios and Risk of a Liquidity Trap in the USA, UK and Japan," MRG Discussion Paper Series 1407, School of Economics, University of Queensland, Australia.
    9. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    10. Hoogerheide, L.F. & van Dijk, H.K., 2007. "Note on neural network sampling for Bayesian inference of mixture processes," Econometric Institute Research Papers EI 2007-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2004. "Neural network based approximations to posterior densities: a class of flexible sampling methods with applications to reduced rank models," Econometric Institute Research Papers EI 2004-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Explaining Adaptive Radial-Based Direction Sampling," Econometric Institute Research Papers EI 2003-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. HOOGERHEIDE, Lennart F. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2007. "Simulation based Bayesian econometric inference: principles and some recent computational advances," LIDAM Discussion Papers CORE 2007015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. David Ardia & Lennart Hoogerheide & Herman K. van Dijk, 2009. "To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods," Tinbergen Institute Discussion Papers 09-017/4, Tinbergen Institute.
    15. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.

  47. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2004. "Econometrics," LIDAM Reprints CORE 1713, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Rombouts, Jeroen V. K. & Bauwens, Luc, 2004. "Econometrics," Papers 2004,33, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. VEREDAS, David & RODRIGUEZ-POO, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," LIDAM Discussion Papers CORE 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Luc Bauwens & Pierre Giot & Joachim Grammig & David Veredas, 2000. "A Comparison of Financial Duration Models via Density Forecasts," Econometric Society World Congress 2000 Contributed Papers 0810, Econometric Society.
    3. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    4. Ciaian, Pavel & Kancs, d'Artis & Pokrivcak, Jan, 2008. "Comparative Advantages, Transaction Costs and Factor Content in Agricultural Trade: Empirical Evidence from the CEE," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44135, European Association of Agricultural Economists.
    5. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    7. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Fatima Sol Murta, 2007. "The Money Market Daily Session :an UHF-GARCH Model Applied to the Portuguese Case Before and After the Introduction Of the Minimum Reserve System of the Single Monetary Policy," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 50(3), pages 285-314.
    9. Sule Akkoyunlu & Konstantin A. Kholodilin & Boriss Siliverstovs, 2006. "The Effect of Economic Reforms of 1980s and of the Customs Union 1996 upon the Turkish Intra-Industry Trade," Discussion Papers of DIW Berlin 649, DIW Berlin, German Institute for Economic Research.
    10. Kulan Ranasinghe & Mervyn J. Silvapulle, 2008. "Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown," Monash Econometrics and Business Statistics Working Papers 1/08, Monash University, Department of Econometrics and Business Statistics.
    11. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Miriam Hein, 2005. "Wie hat sich die universitaere volkswirtschaftliche Forschung in der Schweiz seit Beginn der 90er Jahre entwickelt?�," TWI Research Paper Series 11, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    13. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    14. Alfred Steinherr, 1995. "The Pivotal Role of the European Union for Central and Eastern Europe," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 131(III), pages 303-327, September.
    15. Roel C.A. Oomen, 2004. "Statistical Models for High Frequency Security Prices," Econometric Society 2004 North American Winter Meetings 77, Econometric Society.
    16. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    17. Iheb FRIJA, 2008. "La compétitivité de l'industrie d'habillement tunisienne. Atouts et limites (The tunisian clothing industry competitiveness : assets and limits)," Working Papers 200, Laboratoire de Recherche sur l'Industrie et l'Innovation. ULCO / Research Unit on Industry and Innovation.
    18. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    19. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    20. Ola Simonsen, 2007. "An empirical model for durations in stocks," Annals of Finance, Springer, vol. 3(2), pages 241-255, March.
    21. J. David Richardson & Chi Zhang, 1999. "Revealing Comparative Advantage: Chaotic or Coherent Patterns Across Time and Sector and U.S. Trading Partner?," NBER Working Papers 7212, National Bureau of Economic Research, Inc.
    22. David L. Anderson & John Tressler, 2010. "The Merits of Using Citation-Based Journal Weighting Schemes to Measure Research Performance in Economics: The Case of New Zealand," Working Papers in Economics 10/03, University of Waikato.
    23. Dionne, Georges & Duchesne, Pierre & Pacurar, Maria, 2005. "Intraday Value at Risk (IVaR) using tick-by-tick data with application to the Toronto Stock Exchange," Working Papers 05-9, HEC Montreal, Canada Research Chair in Risk Management.
    24. Kulan Ranasinghe & Mervyn J. Silvapulle, 2008. "Semiparametric estimation of duration models when the parameters are subject to inequality constraints and the error distribution is unknown," Monash Econometrics and Business Statistics Working Papers 5/08, Monash University, Department of Econometrics and Business Statistics.
    25. Vinokurov, Evgeny, 2007. "L’enclave russe de Kaliningrad : spécificité territoriale et intégration à l’économie mondiale [The Russian Enclave of Kaliningrad: Territorial Specificity and Integration with the World Economy]," MPRA Paper 20939, University Library of Munich, Germany.
    26. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.
    27. Stefania Mignani & Marcello Pagnini, 2021. "How effective is financial education? Evidence from the Emilia-Romagna region," Working Paper series 21-08, Rimini Centre for Economic Analysis.
    28. Helena Beltran & Albert J. Menkveld, 2004. "Understanding limit order book depth: conditioning on trade informativeness," Econometric Society 2004 Latin American Meetings 142, Econometric Society.
    29. Catherine L. Mann, 1990. "Towards the next generation of newly industrializing economies: the roles for macroeconomic policy and the manufacturing sector," International Finance Discussion Papers 376, Board of Governors of the Federal Reserve System (U.S.).

  48. BAUWENS, Luc & VEREDAS, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," LIDAM Reprints CORE 1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.
    2. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
    3. Katarzyna Bień-Barkowska, 2014. "“Every move you make, every step you take, I’ll be watching you” – the quest for hidden orders in the interbank FX spot market," Bank i Kredyt, Narodowy Bank Polski, vol. 45(3), pages 197-224.
    4. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    5. Dingan Feng & Peter X.-K. Song & Tony S. Wirjanto, 2008. "Time-Deformation Modeling Of Stock Returns Directed By Duration Processes," Working Papers 08010, University of Waterloo, Department of Economics.
    6. DOLADO , Juan J. & RODRIGUEZ-POO, Juan & VEREDAS, David, 2004. "Testing weak exogeneity in the exponential family : an application to financial point processes," LIDAM Discussion Papers CORE 2004049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    8. Katarzyna Bień-Barkowska, 2011. "Multistate asymmetric ACD model: an application to order dynamics in the EUR/PLN spot market," NBP Working Papers 104, Narodowy Bank Polski.
    9. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    10. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    11. Patrick Leung & Catherine S. Forbes & Gael M Martin & Brendan McCabe, 2019. "Forecasting Observables with Particle Filters: Any Filter Will Do!," Monash Econometrics and Business Statistics Working Papers 22/19, Monash University, Department of Econometrics and Business Statistics.
    12. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," LIDAM Discussion Papers CORE 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Zhi-Qiang Jiang & Wei Chen & Wei-Xing Zhou, 2008. "Detrended fluctuation analysis of intertrade durations," Papers 0806.2444, arXiv.org.
    14. Bhatti, Chad R., 2009. "Intraday trade and quote dynamics: A Cox regression analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2240-2249.
    15. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    16. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
    17. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    18. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    20. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.
    21. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
    22. Siem Jan Koopman & André Lucas & Marcel Scharth, 2016. "Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models," The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 97-110, March.
    23. Wen Cao & Clifford Hurvich & Philippe Soulier, 2012. "Drift in Transaction-Level Asset Price Models," Working Papers hal-00756372, HAL.
    24. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    25. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    26. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2013. "Bayesian Inference of Multiscale Stochastic Conditional Duration Models," Working Paper series 63_13, Rimini Centre for Economic Analysis.
    27. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
    28. Katarzyna Bien-Barkowska, 2012. ""Does it take volume to move fx rates?" Evidence from quantile regressions," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 12, pages 35-52.
    29. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    30. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    31. B.P.M. McCabe & G.M. Martin & R.K. Freeland, 2004. "Testing for Dependence in Non-Gaussian Time Series Data," Monash Econometrics and Business Statistics Working Papers 13/04, Monash University, Department of Econometrics and Business Statistics.
    32. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    33. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    34. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    35. FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," LIDAM Discussion Papers CORE 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    36. Gómez-Déniz, E. & Pérez-Rodríguez, J.V., 2019. "Modelling bimodality of length of tourist stay," Annals of Tourism Research, Elsevier, vol. 75(C), pages 131-151.
    37. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    38. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    39. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    40. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    41. Cosma, Antonio & Galli, Fausto, 2014. "A non parametric ACD model," MPRA Paper 53990, University Library of Munich, Germany.
    42. Yong Li & Xiao-Bin Liu & Jun Yu, 2014. "A Bayesian Chi-Squared Test for Hypothesis Testing," Working Papers 03-2014, Singapore Management University, School of Economics.
    43. Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
    44. Tony S. Wirjanto & Adam W. Kolkiewicz & Zhongxian Men, 2013. "Stochastic Conditional Duration Models with Mixture Processes," Working Paper series 29_13, Rimini Centre for Economic Analysis.
    45. Filip Zikes & Jozef Barunik & Nikhil Shenai, 2012. "Modeling and Forecasting Persistent Financial Durations," Papers 1208.3087, arXiv.org, revised Apr 2013.
    46. Hira L. Koul & Indeewara Perera & Narayana Balakrishna, 2023. "A class of Minimum Distance Estimators in Markovian Multiplicative Error Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 87-115, May.
    47. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    48. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
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  49. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Siem Jan Koopman & André Lucas & André Monteiro, 2005. "The Multi-State Latent Factor Intensity Model for Credit Rating Transitions," Tinbergen Institute Discussion Papers 05-071/4, Tinbergen Institute, revised 04 Jul 2005.
    2. Clive G. Bowsher, 2005. "Modelling Security Market Events in Continuous Time: Intensity Based, Multivariate Point Process Models," Economics Papers 2005-W26, Economics Group, Nuffield College, University of Oxford.
    3. Anthony D. Hall & Nikolaus Hautsch, 2004. "Order Aggressiveness and Order Book Dynamics," FRU Working Papers 2005/04, University of Copenhagen. Department of Economics. Finance Research Unit.
    4. Omar Euch & Masaaki Fukasawa & Mathieu Rosenbaum, 2018. "The microstructural foundations of leverage effect and rough volatility," Finance and Stochastics, Springer, vol. 22(2), pages 241-280, April.
    5. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.
    6. Liesenfeld, Roman & Richard, Jean-François, 2004. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Economics Working Papers 2004-12, Christian-Albrechts-University of Kiel, Department of Economics.
    7. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Liesenfeld, Roman & Richard, Jean-François, 2008. "Improving MCMC, using efficient importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 272-288, December.
    9. Jean-Francois Richard & Roman Liesenfeld, 2007. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Working Paper 322, Department of Economics, University of Pittsburgh, revised Jan 2004.
    10. Ban Zheng & Franc{c}ois Roueff & Fr'ed'eric Abergel, 2013. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Papers 1301.5007, arXiv.org, revised Feb 2014.
    11. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    12. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    13. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Gilles Zumbach, 2015. "Cross-sectional universalities in financial time series," Quantitative Finance, Taylor & Francis Journals, vol. 15(12), pages 1901-1912, December.
    15. Grammig, Joachin & Heinen, Andreas & Rengifo, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market: An empirical analysis using a multivariate count data model," MPRA Paper 8115, University Library of Munich, Germany.

  50. BAUWENS, Luc & BEN OMRANE, Walid & GIOT, Pierre, 2003. "News announcements, market activity and volatility in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2003029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Jieun Lee & Doojin Ryu, 2019. "The impacts of public news announcements on intraday implied volatility dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(6), pages 656-685, June.
    2. Rasmus Fatum & Michael M. Hutchison & Thomas Wu, 2010. "Asymmetries and state dependence: the impact of macro surprises on intraday exchange rates," Globalization Institute Working Papers 49, Federal Reserve Bank of Dallas.
    3. Wu, Zhen-Xing & Gau, Yin-Feng, 2022. "Informativeness of trades around macroeconomic announcements in the foreign exchange market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    4. Evans, Kevin P. & Speight, Alan E.H., 2010. "Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility," Research in International Business and Finance, Elsevier, vol. 24(1), pages 82-101, January.
    5. Yan, Meng & Chen, Jian & Song, Victor & Xu, Ke, 2022. "Trade friction and price discovery in the USD–CAD spot and forward markets," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    6. Igor Martins & Hedibert Freitas Lopes, 2024. "What events matter for exchange rate volatility ?," Papers 2411.16244, arXiv.org.
    7. Lazarczyk, Ewa, 2016. "Market-specific news and its impact on forward premia on electricity markets," Energy Economics, Elsevier, vol. 54(C), pages 326-336.
    8. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2013. "Is exchange rate – Customer order flow relationship linear? Evidence from the Hungarian FX market," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 20-35.
    9. Michael Frömmel & Norbert Kiss M. & Klára Pintér, 2011. "Macroeconomic announcements, communication and order flow on the Hungarian foreign exchange market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(2), pages 172-188, April.
    10. A. Durre & H. Beltran & P. Giot, 2005. "Volatility regimes and the provision of liquidity in order book markets," Post-Print hal-00268757, HAL.
    11. M. Frömmel & A. Mende & L. Menkhoff, 2007. "Order Flows, News, and Exchange Rate Volatility," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/474, Ghent University, Faculty of Economics and Business Administration.
    12. Aymen Belgacem & Anna Creti & Khaled Guesmi & Amine Lahiani, 2015. "Volatility spillovers and macroeconomic announcements: evidence from crude oil markets," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2974-2984, June.
    13. Jansen, David-Jan & de Haan, Jakob, 2007. "Were verbal efforts to support the euro effective? A high-frequency analysis of ECB statements," European Journal of Political Economy, Elsevier, vol. 23(1), pages 245-259, March.
    14. Henryk Gurgul & Lukaz Lach & Tomasz Wojtowicz, 2016. "Impact of US Macroeconomic News Announcements on Intraday Causalities on Selected European Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(5), pages 405-425, October.
    15. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.
    17. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    18. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    19. Ben Omrane, Walid & Savaşer, Tanseli, 2016. "The sign switch effect of macroeconomic news in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 96-114.
    20. Ran Xiao, 2019. "Essays on Price Discovery and Volatility Dynamics in Emerging Market Currencies," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2019, January-A.
    21. Ayadi, Mohamed A. & Ben Omrane, Walid & Das, Deepan Kumar, 2024. "Macroeconomic news, senior officials' speeches, and emerging currency markets: An intraday analysis of price jump reaction," Emerging Markets Review, Elsevier, vol. 60(C).
    22. Walid Ben Omrane & Christian Hafner, 2015. "Macroeconomic news surprises and volatility spillover in foreign exchange markets," Empirical Economics, Springer, vol. 48(2), pages 577-607, March.
    23. Grobys, Klaus, 2024. "A universal exponent governing foreign exchange rate risks," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    24. Ayadi, Mohamed A. & Ben Omrane, Walid & Wang, Jiayu & Welch, Robert, 2022. "Senior official speech attributes and foreign exchange risk around business cycles," International Review of Financial Analysis, Elsevier, vol. 80(C).
    25. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "How does trading volume affect financial return distributions?," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 190-206.
    26. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    27. Paul Alagidede & Tseke Maserumule, 2018. "Impact of macroeconomic announcements on foreign exchange volatility: Evidence from South Africa," Working Papers 751, Economic Research Southern Africa.
    28. Christopher J. Neely, 2011. "A survey of announcement effects on foreign exchange volatility and jumps," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 361-385.
    29. Walid Bahloul & Rangan Gupta, 2018. "Impact of macroeconomic news surprises and uncertainty for major economies on returns and volatility of oil futures," International Economics, CEPII research center, issue 156, pages 247-253.
    30. Shumi Akhtar & Robert Faff & Barry Oliver, 2011. "The asymmetric impact of consumer sentiment announcements on Australian foreign exchange rates," Australian Journal of Management, Australian School of Business, vol. 36(3), pages 387-403, December.
    31. Aris Kartsaklas, 2018. "Trader Type Effects On The Volatility‐Volume Relationship Evidence From The Kospi 200 Index Futures Market," Bulletin of Economic Research, Wiley Blackwell, vol. 70(3), pages 226-250, July.
    32. BAUWENS, Luc & RIME, Dagfinn & SUCARRAT, Genaro, 2005. "Exchange rate volatility and the mixture of distribution hypothesis," LIDAM Discussion Papers CORE 2005058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    33. Keiichi Goshima & Yusuke Kumano, 2018. "Monetary Policy Announcement and Algorithmic News Trading in the Foreign Exchange Market," IMES Discussion Paper Series 18-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    34. Walid Ben Omrane & Christian M. Hafner, 2009. "Information Spillover, Volatility and the Currency Markets for the Binary Choice Model," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 50-62, April.
    35. Evans, Kevin & Speight, Alan, 2010. "International macroeconomic announcements and intraday euro exchange rate volatility," Journal of the Japanese and International Economies, Elsevier, vol. 24(4), pages 552-568, December.
    36. Simonsen, Ola, 2006. "The Impact of News Releases on Trade Durations in Stocks -Empirical Evidence from Sweden," Umeå Economic Studies 688, Umeå University, Department of Economics.
    37. BELTRAN, Helena & DURRE, Alain & GIOT, Pierre, 2009. "Volatility regimes and order book liquidity: Evidence from the Belgian segment of Euronext," LIDAM Reprints CORE 2132, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    38. Kathryn M. E. Dominguez & Freyan Panthaki, 2007. "The Influence of Actual and Unrequited Interventions," Working Papers 561, Research Seminar in International Economics, University of Michigan.
    39. F. DePenya & L. Gil-Alana, 2006. "Testing of nonstationary cycles in financial time series data," Review of Quantitative Finance and Accounting, Springer, vol. 27(1), pages 47-65, August.
    40. Ben Omrane, Walid & Tao, Yusi & Welch, Robert, 2017. "Scheduled macro-news effects on a Euro/US dollar limit order book around the 2008 financial crisis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 9-30.
    41. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    42. Zied Ftiti & Fredj Jawadi & Waël Louhichi, 2017. "Modelling the relationship between future energy intraday volatility and trading volume with wavelet," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1981-1993, April.
    43. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    44. Michael King & Carol Osler & Dagfinn Rime, 2012. "The Market Microstructure Approach to Foreign Exchange: Looking Back and Looking Forward," Working Papers 54, Brandeis University, Department of Economics and International Business School.
    45. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    46. Laakkonen, Helinä & Lanne, Markku, 2009. "The Relevance of Accuracy for the Impact of Macroeconomic News on Volatility," MPRA Paper 23718, University Library of Munich, Germany.
    47. Olivier Damette, 2016. "Mixture distribution hypothesis and the impact of a Tobin tax on exchange rate volatility : a reassessment," Post-Print hal-01601393, HAL.
    48. Walid Ben Omrane & Robert Welch & Xinyao Zhou, 2020. "The dynamic effect of macroeconomic news on the euro/US dollar exchange rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 84-103, January.
    49. Kate Phylaktis & Long Chen, 2010. "Asymmetric information, price discovery and macroeconomic announcements in FX market: do top trading banks know more?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(3), pages 228-246.
    50. Tseke Maserumule & Paul Alagidede, 2017. "Impact of Macroeconomic Announcements on Foreign Exchange Volatility: Evidence from South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 85(3), pages 405-429, September.
    51. Kathryn M.E. Dominguez, 2003. "When Do Central Bank Interventions Influence Intra-Daily and Longer-Term Exchange Rate Movements?," NBER Working Papers 9875, National Bureau of Economic Research, Inc.
    52. Simonsen, Ola, 2006. "Stock Data, Trade Durations, And Limit Order Book Information," Umeå Economic Studies 689, Umeå University, Department of Economics.
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    55. Kleinbrod, Vincent M. & Li, Xiao-Ming, 2017. "Order flow and exchange rate comovement," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 199-215.
    56. Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
    57. Khademalomoom, Siroos & Narayan, Paresh Kumar, 2019. "Intraday effects of the currency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 65-77.
    58. Bauwens, Luc & Ben Omrane, Walid & Rengifo, Erick, 2010. "Intradaily dynamic portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2400-2418, November.
    59. Liu, Guofang & Fang, Xi & Huang, Yuan & Zhao, Weidong, 2021. "Identifying the role of consumer and producer price index announcements in stock index futures price changes," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 87-101.
    60. Smales, L.A., 2017. "Commodity market volatility in the presence of U.S. and Chinese macroeconomic news," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 15-27.
    61. Kathryn Dominguez & Freyan Panthaki, 2005. "What Defines "News" in Foreign Exchange Markets?," NBER Working Papers 11769, National Bureau of Economic Research, Inc.
    62. Ben Omrane, Walid & Heinen, Andréas, 2009. "Is there any common knowledge news in the Euro/Dollar market?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 656-670, October.
    63. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Working Paper Research 49, National Bank of Belgium.
    64. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    65. Iacopo Giampaoli & Wing Lon Ng & Nick Constantinou, 2013. "Periodicities Of Foreign Exchange Markets And The Directional Change Power Law," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(3), pages 189-206, July.
    66. Christoph S. Weber, 2017. "The Effect of Central Bank Transparency on Exchange Rate Volatility," Working Papers 174, Bavarian Graduate Program in Economics (BGPE).
    67. Munazza Jabeen & Abdul Rashid, 2022. "Macroeconomic News and Exchange Rates: Exploring the Role of Order Flow," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 14(2), pages 222-245, May.
    68. Christopher J. Neely & Brett W. Fawley, 2012. "Capital Flows And Japanese Asset Volatility," Pacific Economic Review, Wiley Blackwell, vol. 17(3), pages 391-414, August.
    69. Williams, Andrew, 2015. "A global index of information transparency and accountability," Journal of Comparative Economics, Elsevier, vol. 43(3), pages 804-824.
    70. Wan, Jer-Yuh & Kao, Chung-Wei, 2008. "The euro and pound volatility dynamics: An investigation from conditional jump process," Research in International Business and Finance, Elsevier, vol. 22(2), pages 193-207, June.
    71. Tao Chen, 2018. "Does Investor Attention Matter To Renminbi Trading?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(03), pages 667-689, June.
    72. Rasmus Fatum & Michael Hutchison & Thomas Wu, 2008. "Do Both U.S. and Foreign Macro Surprises Matter for the Intraday Exchange Rate? Evidence from Japan," EPRU Working Paper Series 2009-01, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics, revised Jan 2009.
    73. Nowak, Sylwia & Andritzky, Jochen & Jobst, Andreas & Tamirisa, Natalia, 2011. "Macroeconomic fundamentals, price discovery, and volatility dynamics in emerging bond markets," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2584-2597, October.
    74. Muhammad Ishfaq & Zhang Bi Qiong & Syed Mehmood Raza Shah, 2017. "Global Macroeconomic Announcements and Foreign Exchange Implied Volatility," International Journal of Economics and Financial Issues, Econjournals, vol. 7(5), pages 119-127.
    75. Firouzi, Shahrokh & Wang, Xiangning, 2021. "The interrelationship between order flow, exchange rate, and the role of American economic news," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    76. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    77. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    78. Sensoy, Ahmet & Serdengeçti, Süleyman, 2019. "Intraday volume-volatility nexus in the FX markets: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 1-12.
    79. Wei Guo & Zhongfei Chen, 2023. "China–US economic and trade relations, trade news, and short‐term fluctuation of the RMB exchange rate," Review of International Economics, Wiley Blackwell, vol. 31(1), pages 180-203, February.
    80. Chen, Yu-Lun & Gau, Yin-Feng, 2010. "News announcements and price discovery in foreign exchange spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1628-1636, July.
    81. Ben Omrane, Walid & de Bodt, Eric, 2007. "Using self-organizing maps to adjust for intra-day seasonality," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1817-1838, June.
    82. Konstantinos Gkillas & Dimitrios Vortelinos & Christos Floros & Athanasios Tsagkanos, 2019. "Economic News Releases and Financial Markets in South Africa," Economies, MDPI, vol. 7(4), pages 1-13, November.
    83. Yuewen Xiao & Xiangkang Yin & Jing Zhao, 2020. "Jumps, News, And Subsequent Return Dynamics: An Intraday Study," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(3), pages 705-731, August.
    84. Telegin, O., 2022. "Bank of Russia regular communications and volatility short-term effects in financial markets," Journal of the New Economic Association, New Economic Association, vol. 54(2), pages 130-155.
    85. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    86. Liu, Yang & Han, Liyan & Yin, Libo, 2019. "News implied volatility and long-term foreign exchange market volatility," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 126-142.
    87. BEN OMRANE, Walid & HEINEN, Andréas, 2003. "The response of individual FX dealers'quoting activity to macroeconomic news announcements," LIDAM Discussion Papers CORE 2003070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    88. Ederington, Louis & Guan, Wei & Yang, Lisa (Zongfei), 2019. "The impact of the U.S. employment report on exchange rates," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 257-267.
    89. Marshall, Andrew & Musayev, Taleh & Pinto, Helena & Tang, Leilei, 2012. "Impact of news announcements on the foreign exchange implied volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 719-737.
    90. Tomáš Plíhal, 2021. "Scheduled macroeconomic news announcements and Forex volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1379-1397, December.
    91. Evans, Kevin P. & Speight, Alan E.H., 2010. "Dynamic news effects in high frequency Euro exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 238-258, July.
    92. Barbara Bedowska-Sojka, 2011. "The Impact of Macro News on Volatility of Stock Exchanges," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 99-110.
    93. Onan, Mustafa & Salih, Aslihan & Yasar, Burze, 2014. "Impact of macroeconomic announcements on implied volatility slope of SPX options and VIX," Finance Research Letters, Elsevier, vol. 11(4), pages 454-462.
    94. Aymen Belgacem & Amine Lahiani, 2012. "More on the impact of US macroeconomic announcements: Evidence from French and German stock markets' volatility," Economics Bulletin, AccessEcon, vol. 32(2), pages 1509-1526.
    95. Lazarczyk, Ewa, 2015. "Private and Public Information on the Nordic Intra-Day Electricity Market," Working Paper Series 1064, Research Institute of Industrial Economics.
    96. Vortelinos, Dimitrios I. & Koulakiotis, Athanasios & Tsagkanos, Athanasios, 2017. "Intraday analysis of macroeconomic news surprises and asymmetries in mini-futures markets," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 150-168.
    97. Gau, Yin-Feng & Wu, Zhen-Xing, 2017. "Macroeconomic announcements and price discovery in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 232-254.
    98. Hoda SELIM, 2010. "Fear of Floating and Exchange Rate Pass-Through to Inflation in Egypt," EcoMod2010 259600151, EcoMod.
    99. Rühl, Tobias R. & Stein, Michael, 2015. "The impact of ECB macro-announcements on bid–ask spreads of European blue chips," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 54-71.
    100. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    101. Han, Young Wook, 2008. "Intraday effects of macroeconomic shocks on the US Dollar-Euro exchange rates," Japan and the World Economy, Elsevier, vol. 20(4), pages 585-600, December.
    102. Ben Omrane, Walid & Savaşer, Tanseli, 2017. "Exchange rate volatility response to macroeconomic news during the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 130-143.
    103. Wan Wei & Susan Pozo & Evan Lau, 2021. "The effects of conventional and unconventional monetary policy on exchange rate volatility," Cogent Economics & Finance, Taylor & Francis Journals, vol. 9(1), pages 1997425-199, January.
    104. Lo, Ingrid & Sapp, Stephen G., 2008. "The submission of limit orders or market orders: The role of timing and information in the Reuters D2000-2 system," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1056-1073, November.
    105. Zhang, Tai-Wei & Chueh, Horace & Hsu, Yao Hua, 2015. "Day-of-the-week trading patterns of informed and uninformed traders in Taiwan's foreign exchange market," Economic Modelling, Elsevier, vol. 47(C), pages 271-279.
    106. Michael Filletti, 2020. "Investigating the influence Brexit had on Financial Markets, in particular the GBP/EUR exchange rate," Papers 2003.05895, arXiv.org.

  51. BAUWENS, Luc & ROMBOUTS, Jeroen, 2003. "Bayesian clustering of many GARCH models," LIDAM Discussion Papers CORE 2003087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
    2. Francq, Christian & Horvath, Lajos & Zakoian, Jean-Michel, 2009. "Merits and drawbacks of variance targeting in GARCH models," MPRA Paper 15143, University Library of Munich, Germany.
    3. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    4. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    5. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Bonato, Mateo & Caporin, Massimiliano & Ranaldo, Angelo, 2012. "Risk Spillovers in International Equity Portfolios," Working Papers on Finance 1214, University of St. Gallen, School of Finance.
    7. ROMBOUTS, Jeroen V. K. & STENTOFT, Lars, 2010. "Option pricing with asymmetric heteroskedastic normal mixture models," LIDAM Discussion Papers CORE 2010049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    9. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    10. Brownlees, Christian T., 2019. "Hierarchical GARCH," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 17-27.
    11. Aielli, Gian Piero & Caporin, Massimiliano, 2014. "Variance clustering improved dynamic conditional correlation MGARCH estimators," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 556-576.
    12. Robert Darkins & Emma J Cooke & Zoubin Ghahramani & Paul D W Kirk & David L Wild & Richard S Savage, 2013. "Accelerating Bayesian Hierarchical Clustering of Time Series Data with a Randomised Algorithm," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    13. Juarez, Miguel A. & Steel, Mark F. J., 2006. "Model-based Clustering of non-Gaussian Panel Data," MPRA Paper 880, University Library of Munich, Germany.
    14. Pietro Coretto & Michele La Rocca & Giuseppe Storti, 2020. "Improving Many Volatility Forecasts Using Cross-Sectional Volatility Clusters," JRFM, MDPI, vol. 13(4), pages 1-23, March.
    15. Jane L. Harvill & Priya Kohli & Nalini Ravishanker, 2017. "Clustering Nonlinear, Nonstationary Time Series Using BSLEX," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 935-955, September.
    16. Sylvia Frühwirth-Schnatter, 2011. "Panel data analysis: a survey on model-based clustering of time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 251-280, December.

  52. BAUWENS, Luc & GALLI, Fausto & GIOT, Pierre, 2003. "The moments of Log-ACD models," LIDAM Discussion Papers CORE 2003011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Katarzyna Bień-Barkowska, 2011. "Multistate asymmetric ACD model: an application to order dynamics in the EUR/PLN spot market," NBP Working Papers 104, Narodowy Bank Polski.
    2. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    3. Fabrizio Cipollini & Giampiero M Gallo & Alessandro Palandri, 2020. "Realized Variance Modeling: Decoupling Forecasting from Estimation," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 532-555.
    4. Feng, Yuanhua & Zhou, Chen, 2015. "Forecasting financial market activity using a semiparametric fractionally integrated Log-ACD," International Journal of Forecasting, Elsevier, vol. 31(2), pages 349-363.
    5. Simonsen, Ola, 2006. "The Impact of News Releases on Trade Durations in Stocks -Empirical Evidence from Sweden," Umeå Economic Studies 688, Umeå University, Department of Economics.
    6. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    7. Jan Beran & Yuanhua Feng & Sucharita Ghosh, 2015. "Modelling long-range dependence and trends in duration series: an approach based on EFARIMA and ESEMIFAR models," Statistical Papers, Springer, vol. 56(2), pages 431-451, May.
    8. Simonsen, Ola, 2006. "Stock Data, Trade Durations, And Limit Order Book Information," Umeå Economic Studies 689, Umeå University, Department of Economics.
    9. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 125, Paderborn University, CIE Center for International Economics.
    10. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    11. Simonsen, Ola, 2005. "An Empirical Model for Durations in Stocks," Umeå Economic Studies 657, Umeå University, Department of Economics.
    12. Xuehai Zhang, 2019. "A Box-Cox semiparametric multiplicative error model," Working Papers CIE 122, Paderborn University, CIE Center for International Economics.
    13. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    14. Helton Saulo & Narayanaswamy Balakrishnan & Roberto Vila, 2021. "On a quantile autoregressive conditional duration model applied to high-frequency financial data," Papers 2109.03844, arXiv.org.
    15. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    16. Ola Simonsen, 2007. "An empirical model for durations in stocks," Annals of Finance, Springer, vol. 3(2), pages 241-255, March.
    17. Hautsch, Nikolaus, 2008. "Capturing common components in high-frequency financial time series: A multivariate stochastic multiplicative error model," Journal of Economic Dynamics and Control, Elsevier, vol. 32(12), pages 3978-4015, December.
    18. Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.
    19. Yuanhua Feng & Jan Beran & Sebastian Letmathe & Sucharita Ghosh, 2020. "Fractionally integrated Log-GARCH with application to value at risk and expected shortfall," Working Papers CIE 137, Paderborn University, CIE Center for International Economics.
    20. Aerambamoorthy Thavaneswaran & Nalini Ravishanker & You Liang, 2015. "Generalized duration models and optimal estimation using estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 129-156, February.

  53. BAUWENS, Luc & KIRMAN, Alan & LUBRANO, Michel & PROTOPOPESCU, Camelia, 2003. "Ranking economics departments in Europe: a statistical approach," LIDAM Discussion Papers CORE 2003050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Fredrick M. Wamalwa & Justine Burns, 2018. "Teacher Human Capital, Teacher Effort and Student Achievements in Kenya," Working Papers 150, Economic Research Southern Africa.
    2. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Are Migrants More Productive Than Stayers? Some Evidence From A Set Of Highly Productive Academic Economists," Economic Inquiry, Western Economic Association International, vol. 55(3), pages 1308-1323, July.
    3. AMIR, Rabah & KNAUFF, Malgorzata, 2005. "Ranking economics departments worldwide on the basis of PhD placement," LIDAM Discussion Papers CORE 2005051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Jan Ours & Frederic Vermeulen, 2007. "Ranking Dutch Economists," De Economist, Springer, vol. 155(4), pages 469-487, December.
    5. Rodgers, Joan R. & Valadkhani, Abbas, 2005. "Ranking of Australian Economics Departments Based on Their Total and Per Academic Staff Research Output," Economics Working Papers wp05-18, School of Economics, University of Wollongong, NSW, Australia.
    6. Tombazos, Christis G., 2005. "A revisionist perspective of European research in economics," European Economic Review, Elsevier, vol. 49(2), pages 251-277, February.
    7. Raul Ramos & Vicente Royuela & Jordi Suriñach, 2006. "An analysis of the determinants in economics and business publications by spanish universities between 1994 and 2004," IREA Working Papers 200602, University of Barcelona, Research Institute of Applied Economics, revised Dec 2006.
    8. Jang C. Jin, 2009. "Asian University Rankings in International and Development Economics: An Application of Zipf's Law," Review of International Economics, Wiley Blackwell, vol. 17(1), pages 137-143, February.
    9. Azar, Ofer H., 2006. "Behavioral economics and socio-economics journals: A citation-based ranking," MPRA Paper 4377, University Library of Munich, Germany.
    10. van Dalen, Hendrik Peter, 2021. "How the publish-or-perish principle divides a science: The case of economists," Other publications TiSEM a6a5a855-bb5a-4d52-a841-3, Tilburg University, School of Economics and Management.
    11. Marcella Corsi & Carlo D'Ippoliti & Federico Lucidi, 2011. "On the Evaluation of Economic Research: the Case of Italy," DULBEA Working Papers 11-04, ULB -- Universite Libre de Bruxelles.
    12. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & Nicolas Robinson-García & Daniel Torres-Salinas, 2013. "Benchmarking research performance at the university level with information theoretic measures," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 435-452, April.
    13. Stefano Benati & Silvana Stefani, 2011. "The Academic Journal Ranking Problem: A Fuzzy-Clustering Approach," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 7-20, April.
    14. Javier Ruiz-Castillo, 2008. "Economics research in Spain during the 1990s: a literature review," Spanish Economic Review, Springer;Spanish Economic Association, vol. 10(3), pages 221-249, September.
    15. Haucap, Justus & Mödl, Michael, 2013. "Zum Verhältnis von Spitzenforschung und Politikberatung: Eine empirische Analyse vor dem Hintergrund des Ökonomenstreits," DICE Ordnungspolitische Perspektiven 40, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    16. Kevin Greenidge & Lisa Drakes, 2010. "Tax Policy and Macroeconomic Activity in Barbados," Money Affairs, CEMLA, vol. 0(2), pages 182-210, July-Dece.
    17. Frank Neri & Joan R. Rodgers, 2013. "Eagles and Turkeys: Human Capital Externalities, Departmental Co-authorship and Research Productivity," Australian Economic Papers, Wiley Blackwell, vol. 52(3-4), pages 171-189, December.
    18. Henrekson, Magnus & Waldenström, Daniel, 2007. "How Should Research Performance be Measured? A Study of Swedish Economists," Working Paper Series 712, Research Institute of Industrial Economics, revised 22 Oct 2009.
    19. Robert F. Mulligan, 2024. "Publication trends in political economy scholarship 2011–2020," Constitutional Political Economy, Springer, vol. 35(2), pages 200-302, June.
    20. James B. Davies & Martin G. Kocher & Matthias Sutter, 2008. "Economics research in Canada: a long‐run assessment of journal publications," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 22-45, February.
    21. van Dalen, Hendrik Peter, 2020. "How the Publish-or-Perish Principle Divides a Science : The Case of Academic Economists," Other publications TiSEM 6fbb6b92-0e06-4271-b6e7-3, Tilburg University, School of Economics and Management.
    22. Frank Neri & Joan Rodgers, 2012. "Human capital externalities, departmental co-authorship and research productivity," Economics Working Papers wp12-05, School of Economics, University of Wollongong, NSW, Australia.
    23. Püttmann, Vitus & Thomsen, Stephan L. & Trunzer, Johannes, 2020. "Zur Relevanz von Ausstattungsunterschieden für Forschungsleistungsvergleiche: Ein Diskussionsbeitrag für die Wirtschaftswissenschaften in Deutschland," Hannover Economic Papers (HEP) dp-679, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, revised Mar 2021.
    24. Stelios Katranidis & Theodore Panagiotidis & Costas Zontanos, 2017. "Economists, Research Performance and National Inbreeding: North Versus South," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(1), pages 145-163, February.
    25. van Dalen, Hendrik Peter, 2019. "Do the Values of Economists Matter in the Art and Science of Economics?," Other publications TiSEM bda08972-cae2-4c5b-be28-c, Tilburg University, School of Economics and Management.
    26. Laurens Cherchye & Frederic Vermeulen, 2004. "Robust rankings of multi-dimensional performances: An application to Tour de France racing cyclists," Public Economics Working Paper Series wptourf, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Working Group Public Economics.
    27. Nicolas CARAYOL & Agenor LAHATTE, 2014. "Dominance relations and ranking when quantity and quality both matter: Applications to US universities and econ. departments worldwide," Cahiers du GREThA (2007-2019) 2014-14, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    28. Chih-Sheng Hsieh & Michael D. König & Xiaodong Liu & Christian Zimmermann, 2018. "Superstar Economists: Coauthorship networks and research output," Working Papers 2018-28, Federal Reserve Bank of St. Louis.
    29. Michael Graber & Andrey Launov & Klaus Wälde, 2007. "How to Get Tenured (in Germany, in Economics)," Working Papers 2007_32, Business School - Economics, University of Glasgow.
    30. Mustafa Kadir DOĞAN & Tolga YURET, 2013. "Publication Performance and Student Quality of Turkish Economics Departments," Sosyoekonomi Journal, Sosyoekonomi Society, issue 19(19).
    31. Maria Racionero, 2009. "Susanne Warning, The Economic Analysis of Universities: Strategic Groups and Positioning (Edward Elgar Publishing, 2007)," Agenda - A Journal of Policy Analysis and Reform, Australian National University, College of Business and Economics, School of Economics, vol. 16(1), pages 83-86.
    32. Klaus Ritzberger, 2008. "A Ranking of Journals in Economics and Related Fields," German Economic Review, Verein für Socialpolitik, vol. 9(4), pages 402-430, November.
    33. Hendrik P. Dalen, 2021. "How the publish-or-perish principle divides a science: the case of economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1675-1694, February.
    34. Günther G. Schulze & Susanne Warning & Christian Wiermann, 2008. "Zeitschriftenrankings für die Wirtschaftswissenschaften – Konstruktion eines umfassenden Metaindexes," Perspektiven der Wirtschaftspolitik, Verein für Socialpolitik, vol. 9(3), pages 286-305, August.
    35. Frances Ruane & Richard S.J. Tol, 2007. "Centres of Research Excellence in Economics in the Republic of Ireland," Papers WP180, Economic and Social Research Institute (ESRI).
    36. José M. Merigó & Jian-Bo Yang, 2017. "Accounting Research: A Bibliometric Analysis," Australian Accounting Review, CPA Australia, vol. 27(1), pages 71-100, March.
    37. Miriam Hein, 2005. "Wie hat sich die universitaere volkswirtschaftliche Forschung in der Schweiz seit Beginn der 90er Jahre entwickelt?�," TWI Research Paper Series 11, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    38. Chokri Dridi & Wiktor L. Adamowicz & Alfons Weersink, 2010. "Ranking of Research Output of Agricultural Economics Departments in Canada and Selected U.S. Universities," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(3), pages 273-282, September.
    39. Miguel sarmiento, 2009. "Central Bank Economic Research: Output, Demand, Productivity, and Relevance," Borradores de Economia 5935, Banco de la Republica.
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    6. Haoren Zhu & Pengfei Zhao & Wilfred Siu Hung NG & Dik Lun Lee, 2024. "Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns," Papers 2406.11886, arXiv.org.
    7. Manabu Asai & Michael McAleer, 2011. "Dynamic Conditional Correlations for Asymmetric Processes," Documentos de Trabajo del ICAE 2011-30, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
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  55. BAUWENS, Luc & GIOT, Pierre, 2003. "Asymmetric ACD models: Introducing price information in ACD models," LIDAM Reprints CORE 1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Oxford University Press, vol. 9(3), pages 469-488, Summer.
    2. Pyrlik, Vladimir, 2013. "Autoregressive conditional duration as a model for financial market crashes prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6041-6051.
    3. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    4. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Nowak, Sylwia & Anderson, Heather M., 2014. "How does public information affect the frequency of trading in airline stocks?," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 26-38.
    6. A. Durre & H. Beltran & P. Giot, 2005. "Volatility regimes and the provision of liquidity in order book markets," Post-Print hal-00268757, HAL.
    7. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    8. Saulo, Helton & Balakrishnan, Narayanaswamy & Vila, Roberto, 2023. "On a quantile autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 425-448.
    9. Paola Zuccolotto, 2002. "Modelling the impact of open volume on inter-trade autoregressive durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3-4), pages 49-63.
    10. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    11. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    12. Giot, Pierre & Schwienbacher, Armin, 2007. "IPOs, trade sales and liquidations: Modelling venture capital exits using survival analysis," Journal of Banking & Finance, Elsevier, vol. 31(3), pages 679-702, March.
    13. Yiing Fei Tan & Kok Haur Ng & You Beng Koh & Shelton Peiris, 2022. "Modelling Trade Durations Using Dynamic Logarithmic Component ACD Model with Extended Generalised Inverse Gaussian Distribution," Mathematics, MDPI, vol. 10(10), pages 1-20, May.
    14. Zhicheng Li & Haipeng Xing & Xinyun Chen, 2019. "A multifactor regime-switching model for inter-trade durations in the limit order market," Papers 1912.00764, arXiv.org.
    15. Cosma, Antonio & Galli, Fausto, 2014. "A non parametric ACD model," MPRA Paper 53990, University Library of Munich, Germany.
    16. Wang, Keli & Liu, Xiaoquan & Ye, Wuyi, 2023. "Intraday VaR: A copula-based approach," Journal of Empirical Finance, Elsevier, vol. 74(C).
    17. Liu, Shouwei & Tse, Yiu-Kuen, 2015. "Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach," Journal of Econometrics, Elsevier, vol. 189(2), pages 437-446.
    18. Ahmed M. Khalid & Gulasekaran Rajaguru, 2004. "Financial Market Linkages in South Asia: Evidence Using a Multivariate GARCH Model," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 43(4), pages 585-603.
    19. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
    20. Katarzyna Bień-Barkowska, 2014. "Capturing Order Book Dynamics in the Interbank EUR/PLN Spot Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(1), pages 93-117, January.
    21. Christian Hafner, 2005. "Durations, volume and the prediction of financial returns in transaction time," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 145-152.
    22. BAUWENS, Luc & VEREDAS, David, 1999. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," LIDAM Discussion Papers CORE 1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    23. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Australasian Meetings 272, Econometric Society.
    24. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    25. Manganelli, Simone, 2005. "Duration, volume and volatility impact of trades," Journal of Financial Markets, Elsevier, vol. 8(4), pages 377-399, November.
    26. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    27. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Working Paper Research 49, National Bank of Belgium.
    28. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.
    29. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(4), pages 237-273, December.
    30. Charlie X. Cai & Qi Zhang, 2016. "High†Frequency Exchange Rate Forecasting," European Financial Management, European Financial Management Association, vol. 22(1), pages 120-141, January.
    31. Giovanni De Luca & Paola Zuccolotto, 2003. "Finite and infinite mixtures for financial durations," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 431-455.
    32. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism," Papers 2101.02736, arXiv.org.
    33. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
    34. Qi Zhang & Charlie X Cai & Kevin Keasey, 2009. "Forecasting using high-frequency data: a comparison of asymmetric financial duration models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 371-386.
    35. Wing Lon NG, 2004. "Duration and Order Type Clusters," Econometric Society 2004 Far Eastern Meetings 730, Econometric Society.
    36. Barry Harrison & Winston Moore, 2009. "Spillover effects from London and Frankfurt to Central and Eastern European stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 19(18), pages 1509-1521.
    37. Danúbia R. Cunha & Roberto Vila & Helton Saulo & Rodrigo N. Fernandez, 2020. "A General Family of Autoregressive Conditional Duration Models Applied to High-Frequency Financial Data," JRFM, MDPI, vol. 13(3), pages 1-20, March.
    38. Hafner, Christian, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," LIDAM Reprints ISBA 2012027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    39. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
    40. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    41. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
    42. Aerambamoorthy Thavaneswaran & Nalini Ravishanker & You Liang, 2015. "Generalized duration models and optimal estimation using estimating functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(1), pages 129-156, February.
    43. Pérez-Rodríguez, Jorge V. & Sosvilla-Rivero, Simón & Andrada-Felix, Julián & Gómez-Déniz, Emilio, 2022. "Searching for informed traders in stock markets: The case of Banco Popular," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    44. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
    45. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    46. Roman Huptas, 2016. "The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 1-20, March.
    47. Katarzyna Bien-Barkowska, 2011. "Distribution Choice for the Asymmetric ACD Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 55-72.
    48. M. Dolores Jiménez-Gamero & Sangyeol Lee & Simos G. Meintanis, 2020. "Goodness-of-fit tests for parametric specifications of conditionally heteroscedastic models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 682-703, September.

  56. Luc Bauwens & Charles S. Bos & Herman K. van Dijk & Rutger D. van Oest, 2002. "Adaptive Polar Sampling," Computing in Economics and Finance 2002 307, Society for Computational Economics.

    Cited by:

    1. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    2. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    3. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.
    4. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    5. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.

  57. BAUWENS, Luc & LAURENT, Sébastien, 2002. "A new class of multivariate skew densities, with application to GARCH models," LIDAM Discussion Papers CORE 2002020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    2. Gianni Amisano & Roberto Casarin, 2008. "Particle Filters for Markov-Switching Stochastic-Correlation Models," Working Papers 0814, University of Brescia, Department of Economics.
    3. Lunina, Veronika, 2016. "Joint Modelling of Power Price, Temperature, and Hydrological Balance with a View towards Scenario Analysis," Working Papers 2016:30, Lund University, Department of Economics.
    4. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    5. Boswijk, H.P. & Weide, R. van der, 2006. "Wake me up before you GO-GARCH," CeNDEF Working Papers 06-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    6. Kai-Li Wang & Mei-Ling Chen, 2007. "The dynamics in the spot, futures, and call options with basis asymmetries: an intraday analysis in a generalized multivariate GARCH-M MSKST framework," Review of Quantitative Finance and Accounting, Springer, vol. 29(4), pages 371-394, November.
    7. Sentana, Enrique & Mencía, Javier, 2005. "Estimation and Testing of Dynamic Models with Generalized Hyperbolic Innovations," CEPR Discussion Papers 5177, C.E.P.R. Discussion Papers.
    8. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2016. "Cross-Commodity News Transmission and Volatility Spillovers in the German Energy Markets," Working Papers 2016:2, Lund University, Department of Economics, revised 11 Oct 2017.
    9. Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, University Library of Munich, Germany.
    10. Eric Jondeau & Michael Rockinger, 2005. "Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?," FAME Research Paper Series rp132, International Center for Financial Asset Management and Engineering.
    11. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    12. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    13. BAUWENS, Luc & BEN OMRANE, Walid & RENGIFO, Erick, 2006. "Intra-daily FX optimal portfolio allocation," LIDAM Discussion Papers CORE 2006010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Econometric modeling of exchange rate volatility and jumps," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 16, pages 373-427, Edward Elgar Publishing.
    15. Michal Kaut & Stein Wallace, 2011. "Shape-based scenario generation using copulas," Computational Management Science, Springer, vol. 8(1), pages 181-199, April.
    16. Bauwens Luc & Storti Giuseppe, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-33, May.
    17. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Dongming Zhu & John W. Galbraith, 2009. "Forecasting Expected Shortfall with a Generalized Asymmetric Student-t Distribution," CIRANO Working Papers 2009s-24, CIRANO.
    19. Bal??zs ??gert & Ev??en Kocenda, 2007. "Time-Varying Comovements in Developed and Emerging European Stock Markets: Evidence from Intraday Data," William Davidson Institute Working Papers Series wp861, William Davidson Institute at the University of Michigan.
    20. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    21. Eric Jondeau & Michael Rockinger, 2002. "Conditional Dependency of Financial Series: The Copula-GARCH Model," FAME Research Paper Series rp69, International Center for Financial Asset Management and Engineering.
    22. Choi, Pilsun & Nam, Kiseok, 2008. "Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 41-63, January.
    23. Fantazzini , Dean, 2009. "Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 14(2), pages 100-127.
    24. Vincenzo Candila, 2013. "A Comparison of the Forecasting Performances of Multivariate Volatility Models," Working Papers 3_228, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    25. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    26. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2009. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working Papers 0905, University of Nevada, Las Vegas , Department of Economics.
    27. Philippe Lambert & Sébastien Laurent, 2008. "Testing Conditional Dynamics in Asymmetry. A Residual-Based Approach," Working Papers ECARES 2008_009, ULB -- Universite Libre de Bruxelles.
    28. Harvey, A. & Chakravarty, T., 2008. "Beta-t-(E)GARCH," Cambridge Working Papers in Economics 0840, Faculty of Economics, University of Cambridge.
    29. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    30. LOMBARDI, Marco & VEREDAS, David, 2007. "Indirect estimation of elliptical stable distributions," LIDAM Discussion Papers CORE 2007018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    31. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    32. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.
    33. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.

  58. BAUWENS , Luc & LUBRANO, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," LIDAM Reprints CORE 1569, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Anna Pajor, 2009. "Bayesian Analysis of the Box-Cox Transformation in Stochastic Volatility Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 9, pages 81-90.
    2. Fonseca, Thais C O & Cerqueira, Vinicius S & Migon, Helio S & Torres, Christian A C, 2021. "Evaluating the performance of degrees of freedom estimation in asymmetric GARCH models with t-student innovations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
    3. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    4. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    5. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    6. Lin, Lisha & Li, Yaqiong & Gao, Rui & Wu, Jianhong, 2021. "The numerical simulation of Quanto option prices using Bayesian statistical methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    7. Martin, G.M. & Forbes, C.S. & Martin, V.L., 2000. "Implicit Bayesian Inference Using Option Prices," Monash Econometrics and Business Statistics Working Papers 5/00, Monash University, Department of Econometrics and Business Statistics.
    8. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    9. G.C. Lim & G.M. Martin & V.L. Martin, 2002. "Parametric Pricing of Higher Order Moments in S&P500 Options," Monash Econometrics and Business Statistics Working Papers 1/02, Monash University, Department of Econometrics and Business Statistics.
    10. Ausin, Maria Concepcion & Galeano, Pedro, 2007. "Bayesian estimation of the Gaussian mixture GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
    11. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
    12. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Eirini Konstantinidi & Gkaren Papazian & George Skiadopoulos, 2015. "Modeling the Dynamics of Temperature with a View to Weather Derivatives," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 17, pages 511-544, World Scientific Publishing Co. Pte. Ltd..
    14. Chen, Yufeng & Xu, Jing & Miao, Jiafeng, 2023. "Dynamic volatility contagion across the Baltic dry index, iron ore price and crude oil price under the COVID-19: A copula-VAR-BEKK-GARCH-X approach," Resources Policy, Elsevier, vol. 81(C).
    15. Darsinos, T. & Satchell, S.E., 2001. "Bayesian Forecasting of Options Prices: A Natural Framework for Pooling Historical and Implied Volatiltiy Information," Cambridge Working Papers in Economics 0116, Faculty of Economics, University of Cambridge.
    16. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," JRFM, MDPI, vol. 4(1), pages 1-23, December.
    17. Ehlers, Ricardo S., 2012. "Computational tools for comparing asymmetric GARCH models via Bayes factors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 858-867.
    18. Lisha Lin & Yaqiong Li & Rui Gao & Jianhong Wu, 2019. "The Numerical Simulation of Quanto Option Prices Using Bayesian Statistical Methods," Papers 1910.04075, arXiv.org.
    19. Chiang, Min-Hsien & Huang, Hsin-Yi, 2011. "Stock market momentum, business conditions, and GARCH option pricing models," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 488-505, June.
    20. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.
    21. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    22. Kiyotaka Satoyoshi & Hidetoshi Mitsui, 2011. "Empirical Study of Nikkei 225 Options with the Markov Switching GARCH Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(1), pages 55-68, March.
    23. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    24. Tunaru, Radu & Zheng, Teng, 2017. "Parameter estimation risk in asset pricing and risk management: A Bayesian approach," International Review of Financial Analysis, Elsevier, vol. 53(C), pages 80-93.
    25. Li, Chao & Shang, Pengjian, 2018. "Complexity analysis based on generalized deviation for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 118-128.
    26. Yuzhi Cai, 2021. "Estimating expected shortfall using a quantile function model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4332-4360, July.

  59. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2002-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    2. Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, University Library of Munich, Germany.
    3. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.

  60. BAUWENS, Luc & HUNTER, John, 2000. "Identifying long-run behaviour with non-stationary data," LIDAM Discussion Papers CORE 2000043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Tabaghdehi, Seyedeh Asieh H. & Hunter, John, 2020. "Long-run price behaviour in the gasoline market - The role of exogeneity," Journal of Business Research, Elsevier, vol. 116(C), pages 620-627.

  61. BAUWENS, Luc & GINSBURGH, Victor, 2000. "Art experts and auctions are pre-sale estimates unbiased and fully informative?," LIDAM Reprints CORE 1485, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Beggs, Alan & Graddy, Kathryn, 2006. "Failure to Meet the Reserve Price: The Impact on Returns to Art," CEPR Discussion Papers 5811, C.E.P.R. Discussion Papers.
    2. Michel Clement & Anke Lepthien & Tim Schulze, 2016. "Erfolgsfaktoren bei der Vermarktung von Kunst [Success Factors for Marketing of Arts]," Schmalenbach Journal of Business Research, Springer, vol. 68(4), pages 377-400, December.
    3. Ünsal Özdilek, 2013. "Visual autocorrelation of prices," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(2), pages 203-223, May.
    4. Melissa Boyle & Justin Svec, 2022. "The Roundness of Antiquity Valuations from Auction Houses and Sales," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 602-630, October.
    5. Spaenjers, Christophe & Goetzmann, William N. & Mamonova, Elena, 2015. "The economics of aesthetics and record prices for art since 1701," Explorations in Economic History, Elsevier, vol. 57(C), pages 79-94.
    6. Tim R. L. Fry, 2020. "Heterogeneity in Auction Price Distributions for Australian Indigenous Artists," The Economic Record, The Economic Society of Australia, vol. 96(313), pages 177-186, June.
    7. Calin Valsan & Robert Sproule, 2008. "Reservation Prices And Pre-Auction Estimates: A Study In Abstract Art," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 10(24), pages 257-272, June.
    8. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 490-520.
    9. Ali-Kein, Hela Hadj & Lecocq, Sebastien & Visser, Michael, 2007. "The Impact of Gurus: Parker Grades and EN PRIMEUR Wine Prices," Working Papers 37292, American Association of Wine Economists.
    10. Patrick Georges & Aylin Seçkin, 2013. "Black notes and white noise: a hedonic approach to auction prices of classical music manuscripts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(1), pages 33-60, February.
    11. Victor Ginsburgh, 2003. "Awards, Success and Aesthetic Quality in the Arts," Journal of Economic Perspectives, American Economic Association, vol. 17(2), pages 99-111, Spring.
    12. G. Candela & P. Figini & A. E. Scorcu, 2003. "Price indices for artists - A proposal," Working Papers 491, Dipartimento Scienze Economiche, Universita' di Bologna.
    13. Menival, David & Charters, Steve, 2014. "The impact of geographic reputation on the value created in Champagne," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 58(2), April.
    14. Kathryn Graddy & Orley Ashenfelter & Princeton University and NBER, 2002. "Auctions and the Price of Art," Economics Series Working Papers 131, University of Oxford, Department of Economics.
    15. Ashenfelter, Orley C & Graddy, Kathryn, 2002. "Art Auctions: A Survey of Empirical Studies," CEPR Discussion Papers 3387, C.E.P.R. Discussion Papers.
    16. Lucio Picci & Antonello Scorcu, 2003. "Bidders' and Sellers' Strategies in Sequential Auctions. New Evidence about the Afternoon Effect," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 30(2), pages 163-178, June.
    17. Patrick Georges & Aylin Seçkin, 2012. "Auction Prices of Classical Music Manuscripts – A Hedonic Approach," Working Papers 1202E, University of Ottawa, Department of Economics.
    18. Bronwyn Coate & Tim R.L. Fry, 2012. "Better off Dead? Prices Realised for Australian Paintings Sold at Auction," ACEI Working Paper Series AWP-02-2012, Association for Cultural Economics International, revised Feb 2012.
    19. Victor Ginsburgh & Sheila Weyers, 2008. "Quantitative approaches to valuation in the arts, with an application to movies," ULB Institutional Repository 2013/7292, ULB -- Universite Libre de Bruxelles.
    20. Calin Valsan & Robert Sproule, 2006. "Hedonic Models and Pre-Auction Estimates: Abstract Art Revisited," Economics Bulletin, AccessEcon, vol. 26(5), pages 1-10.
    21. Michael Beckmann, 2004. "Art Auctions and Bidding Rings: Empirical Evidence from German Auction Data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 28(2), pages 125-141, May.
    22. Draper, Paul & Duboisée de Ricquebourg, Alan & Clacher, Iain, 2018. "Auctions, market efficiency, and the trade in second-hand and antique silver," Economics Letters, Elsevier, vol. 162(C), pages 45-48.
    23. Nicoletta MARINELLI & Giulio PALOMBA, 2008. "A Model for Pricing the Italian Contemporary Art Paintings at Auction," Working Papers 316, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    24. Jun-ichi Itaya & Heinrich Ursprung, 2008. "Price and Death," CESifo Working Paper Series 2213, CESifo.
    25. Aubry, Mathieu & Kräussl, Roman & Manso, Gustavo & Spaenjers, Christophe, 2019. "Machine learning, human experts, and the valuation of real assets," CFS Working Paper Series 635, Center for Financial Studies (CFS).
    26. Stuart Kells, 2003. "Explaining The Breadth Of Expert Estimate Ranges In Auctions Of Rare Books," Department of Economics - Working Papers Series 873, The University of Melbourne.
    27. Seçkin Aylin & Atukeren Erdal, 2012. "A Heckit Model of Sales Dynamics in Turkish Art Auctions: 2005-2008," Review of Middle East Economics and Finance, De Gruyter, vol. 7(3), pages 1-32, May.
    28. Lisa Farrell & Tim R.L. Fry, 2017. "Pre-sale information and hammer prices for Australian Indigenous art," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(5), pages 483-500, November.
    29. Brunella Bruno & Emilia Garcia‐Appendini & Giacomo Nocera, 2018. "Experience and Brokerage in Asset Markets: Evidence from Art Auctions," Financial Management, Financial Management Association International, vol. 47(4), pages 833-864, December.
    30. Shailendra Gurjar & Usha Ananthakumar, 2023. "Presale Estimates and Auction Prices in Indian Art Market: Accuracy, Determinants and Motivations," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(3), pages 555-567, September.
    31. Graddy, Kathryn & Hamilton, Jonathan, 2017. "Auction guarantees for works of art," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 303-312.

  62. BAUWENS , Luc & GIOT, Pierre & GRAMMIG, Joachim & VEREDAS, David, 2000. "A comparison of financial duration models via density forecasts," LIDAM Discussion Papers CORE 2000060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Herrera, Rodrigo & Schipp, Bernhard, 2013. "Value at risk forecasts by extreme value models in a conditional duration framework," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 33-47.
    2. Isao Ishida, 2005. "Scanning Multivariate Conditional Densities with Probability Integral Transforms," CARF F-Series CARF-F-045, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. VEREDAS, David & RODRIGUEZ-POO, Juan & ESPASA, Antoni, 2002. "On the (intradaily) seasonality and dynamics of a financial point process: a semiparametric approach," LIDAM Discussion Papers CORE 2002023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    5. Bhatti, Chad R., 2009. "On the interday homogeneity in the intraday rate of trading," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2250-2257.
    6. DOLADO , Juan J. & RODRIGUEZ-POO, Juan & VEREDAS, David, 2004. "Testing weak exogeneity in the exponential family : an application to financial point processes," LIDAM Discussion Papers CORE 2004049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," LIDAM Discussion Papers CORE 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    9. Yogo Purwono & Irwan Adi Ekaputra & Zaäfri Ananto Husodo, 2018. "Estimation of Dynamic Mixed Hitting Time Model Using Characteristic Function Based Moments," Computational Economics, Springer;Society for Computational Economics, vol. 51(2), pages 295-321, February.
    10. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.
    11. BOUEZMARNI, Taoufik & ROMBOUTS, Jeroen V. K., 2006. "Nonparametric density estimation for positive time series," LIDAM Discussion Papers CORE 2006085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Artur Sokolovsky & Luca Arnaboldi, 2020. "A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components," Papers 2009.09993, arXiv.org, revised Jun 2022.
    13. Christian T. Brownlees & Giampiero Gallo, 2006. "Financial Econometric Analysis at Ultra–High Frequency: Data Handling Concerns," Econometrics Working Papers Archive wp2006_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    14. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
    15. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    16. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Andrew Harvey & Ryoko Ito, 2017. "Modeling time series with zero observations," Economics Papers 2017-W01, Economics Group, Nuffield College, University of Oxford.
    18. Helton Saulo & Jeremias Leão & Víctor Leiva & Robert G. Aykroyd, 2019. "Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data," Statistical Papers, Springer, vol. 60(5), pages 1605-1629, October.
    19. Stanislav Anatolyev & Dmitry Shakin, 2006. "Trade intensity in the Russian stock market:dynamics, distribution and determinants," Working Papers w0070, New Economic School (NES).
    20. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    21. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    22. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    23. Fatima Sol Murta, 2007. "The Money Market Daily Session :an UHF-GARCH Model Applied to the Portuguese Case Before and After the Introduction Of the Minimum Reserve System of the Single Monetary Policy," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 50(3), pages 285-314.
    24. Andres, P. & Harvey, A., 2012. "The Dyanamic Location/Scale Model: with applications to intra-day financial data," Cambridge Working Papers in Economics 1240, Faculty of Economics, University of Cambridge.
    25. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.
    26. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    27. Vasileios Siakoulis & Ioannis Venetis, 2015. "On inter-arrival times of bond market extreme events. An application to seven European markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(4), pages 717-741, October.
    28. Wu, Zhengxiao, 2012. "On the intraday periodicity duration adjustment of high-frequency data," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 282-291.
    29. FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," LIDAM Discussion Papers CORE 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. Andres, Philipp, 2014. "Maximum likelihood estimates for positive valued dynamic score models; The DySco package," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 34-42.
    31. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    32. Zdeněk Zmeškal & Dana Dluhošová & Karolina Lisztwanová & Antonín Pončík & Iveta Ratmanová, 2023. "Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy," Forecasting, MDPI, vol. 5(2), pages 1-19, May.
    33. Cosma, Antonio & Galli, Fausto, 2014. "A non parametric ACD model," MPRA Paper 53990, University Library of Munich, Germany.
    34. Liu, Chun & Maheu, John M., 2012. "Intraday dynamics of volatility and duration: Evidence from Chinese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 329-348.
    35. Amisano, Gianni & Geweke, John, 2008. "Comparing and evaluating Bayesian predictive distributions of assets returns," Working Paper Series 969, European Central Bank.
    36. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    37. Liu, Shouwei & Tse, Yiu-Kuen, 2015. "Intraday Value-at-Risk: An asymmetric autoregressive conditional duration approach," Journal of Econometrics, Elsevier, vol. 189(2), pages 437-446.
    38. Allen, David & Lazarov, Zdravetz & McAleer, Michael & Peiris, Shelton, 2009. "Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2535-2555.
    39. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2007. "Modeling Transaction Data of Trade Direction and Estimation of Probability of Informed Trading," Finance Working Papers 22483, East Asian Bureau of Economic Research.
    40. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2013. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121, December.
    41. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    42. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
    43. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
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    45. GIOT, Pierre, 2003. "The information content of implied volatility indexes for forecasting volatility and market risk," LIDAM Discussion Papers CORE 2003027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    89. Katarzyna Bień-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 117-142, June.
    90. Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
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    92. Zhou, Weijie & Wang, Zhengxin & Guo, Haiming, 2016. "Modelling volatility recurrence intervals in the Chinese commodity futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 514-525.
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    98. Roman Huptas, 2019. "Point forecasting of intraday volume using Bayesian autoregressive conditional volume models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(4), pages 293-310, July.
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    104. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2008. "Fractals in trade duration: capturing long-range dependence and heavy tailedness in modeling trade duration," Annals of Finance, Springer, vol. 4(2), pages 217-241, March.
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  65. BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K., 1999. "Adaptive polar sampling with an application to a Bayes measure of value-at-risk," LIDAM Discussion Papers CORE 1999057, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Research Papers EI 2000-20/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée.
    3. Badescu Alex & Kulperger Reg & Lazar Emese, 2008. "Option Valuation with Normal Mixture GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-42, May.
    4. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics.
    5. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    6. Ausin, Maria Concepcion & Galeano, Pedro, 2007. "Bayesian estimation of the Gaussian mixture GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
    7. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    8. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
    9. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
    10. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    11. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    12. Qiang Xia & Heung Wong & Jinshan Liu & Rubing Liang, 2017. "Bayesian Analysis of Power-Transformed and Threshold GARCH Models: A Griddy-Gibbs Sampler Approach," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 353-372, October.

  66. BAUWENS, Luc & GIOT, Pierre, 1998. "Asymmetric ACD models: introducing price information in ACD models with a two state transition model," LIDAM Discussion Papers CORE 1998044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Florian Ielpo & Dominique Gúegan, 2009. "Understanding the Importance of the Duration and Size of the Variations of Fed’s Target Rate," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(3-4), pages 44-72, August.
    2. BAUWENS, Luc & VEREDAS, David, 1999. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," LIDAM Discussion Papers CORE 1999058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Sylwia Nowak, 2008. "How Do Public Announcements Affect The Frequency Of Trading In U.S. Airline Stocks?," CAMA Working Papers 2008-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
    5. GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," LIDAM Discussion Papers CORE 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  67. BAUWENS, LUC & GIOT, Pierre, 1997. "The logarithmic ACD model: an application to market microstructure and NASDAQ," LIDAM Discussion Papers CORE 1997089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Gerhard, Frank & Hautsch, Nikolaus, 2000. "Determinants of Inter-Trade Durations and Hazard Rates Using Proportional Hazard ARMA Model," CoFE Discussion Papers 00/20, University of Konstanz, Center of Finance and Econometrics (CoFE).
    2. Hujer Reinhard & Grammig Joachim & Kokot Stefan, 2000. "Time Varying Trade Intensities and the Deutsche Telekom IPO / Zeitvariable Handelsintensitaten und die Deutsche Telekom IPO," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 220(6), pages 689-714, December.

  68. BAUWENS, Luc & DEPRINS, Dominique & VANDEUREN, Jean-Pierre, 1997. "Modelling interest rates with a cointegrated VAR-GARCH model," LIDAM Discussion Papers CORE 1997080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Yvan Lengwiler & Carlos Lenz, 2008. "Intelligible Factors for the Yield Curve," Working Papers 2008-02, Swiss National Bank.
    2. Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
    3. Chang, Yoosoon & Miller, J. Isaac & Park, Joon Y., 2005. "Extracting a Common Stochastic Trend: Theories with Some Applications," Working Papers 2005-06, Rice University, Department of Economics.
    4. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
    5. Röthig, Andreas, 2004. "Currency futures and currency crises," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 4022, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Ge, Yuanlong & Wang, H. Holly & Ahn, Sung K., 2008. "Implication of Cotton Price Behavior on Market Integration," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37623, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Röthig, Andreas, 2004. "Currency Futures and Currency Crises," Darmstadt Discussion Papers in Economics 136, Darmstadt University of Technology, Department of Law and Economics.
    8. Hui, Cho-Hoi & Fong, Tom Pak-Wing, 2015. "Price cointegration between sovereign CDS and currency option markets in the financial crises of 2007–2013," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 174-190.

  69. BAUWENS, Luc & GIOT, Pierre, 1997. "A Gibbs sampling approach to cointegration," LIDAM Discussion Papers CORE 1997016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Sugita, Katsuhiro, 2002. "Testing For Cointegration Rank Using Bayes Factors," The Warwick Economics Research Paper Series (TWERPS) 654, University of Warwick, Department of Economics.
    2. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    3. SILVESTRINI, Andrea, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," LIDAM Reprints CORE 2220, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Gareth W. Peters & Balakrishnan Kannan & Ben Lasscock & Chris Mellen, 2010. "Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model," Papers 1004.3830, arXiv.org.
    5. Sugita, Katsuhiro, 2002. "Testing for Cointegration Rank Using Bayes Factors," Economic Research Papers 269467, University of Warwick - Department of Economics.
    6. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Strachan, Rodney W. & Inder, Brett, 2004. "Bayesian analysis of the error correction model," Journal of Econometrics, Elsevier, vol. 123(2), pages 307-325, December.
    8. Chew Lian Chua & Peter Summers, 2004. "Structural Error Correction Model: A Bayesian Perspective," Econometric Society 2004 Far Eastern Meetings 702, Econometric Society.

  70. BAUWENS, LUC & LUBRANO, Michel, 1997. "Bayesian option pricing using asymmetric GARCH," LIDAM Discussion Papers CORE 1997059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    2. HAFNER, Christian & HERWARTZ, Helmut, 1998. "Volatility impulse response functions for multivariate GARCH models," LIDAM Discussion Papers CORE 1998047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Abel Rodríguez & Enrique ter Horst & Samuel Malone, 2015. "Bayesian Inference for a Structural Credit Risk Model with Stochastic Volatility and Stochastic Interest Rates," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 839-867.

  71. BAUWENs, Luc & LUBRANO , Michel, 1996. "Bayesian Inference on GARCH Models using the Gibbs Sampler," LIDAM Discussion Papers CORE 1996027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2021. "Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects," JRFM, MDPI, vol. 14(5), pages 1-28, May.
    2. Mathias Silva & Michel Lubrano, 2023. "Bayesian correction for missing rich using a Pareto II tail with unknown threshold: Combining EU-SILC and WID data," Working Papers hal-04231661, HAL.
    3. Zhang, Xibin & King, Maxwell L. & Hyndman, Rob J., 2006. "A Bayesian approach to bandwidth selection for multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3009-3031, July.
    4. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    5. Sylvia Kaufmann & Sylvia Frühwirth‐Schnatter, 2002. "Bayesian analysis of switching ARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 425-458, July.
    6. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    7. Manabu Asai & Michael McAleer, 2022. "Bayesian Analysis of Realized Matrix-Exponential GARCH Models," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 103-123, January.
    8. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    9. Miazhynskaia, Tatiana & Fruhwirth-Schnatter, Sylvia & Dorffner, Georg, 2006. "Bayesian testing for non-linearity in volatility modeling," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 2029-2042, December.
    10. Juan Carlos Ruilova & Pedro Alberto Morettin, 2020. "Parsimonious Heterogeneous ARCH Models for High Frequency Modeling," JRFM, MDPI, vol. 13(2), pages 1-19, February.
    11. Fu, Jin-Yu & Lin, Jin-Guan & Hao, Hong-Xia, 2023. "Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1698-1712.
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    1. Luca Benati & Thomas A. Lubik, 2021. "Searching for Hysteresis," Working Paper 21-03, Federal Reserve Bank of Richmond.
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    1. Maya Papineau & Kareman Yassin & Guy Newsham & Sarah Brice, 2020. "Conditional demand analysis as a tool to evaluate energy policy options on the path to grid decarbonization," Carleton Economic Papers 20-21, Carleton University, Department of Economics.
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    5. Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
    6. Hanne Marit Dalen and Bodil M. Larsen, 2015. "Residential End-use Electricity Demand: Development over Time," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    7. Muhammad Akmal & David I. Stern, 2001. "The structure of Australian residential energy demand," Working Papers in Ecological Economics 0101, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
    8. Brabec, Marek & Konár, Ondrej & Pelikán, Emil & Malý, Marek, 2008. "A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers," International Journal of Forecasting, Elsevier, vol. 24(4), pages 659-678.
    9. Aydinalp-Koksal, Merih & Ugursal, V. Ismet, 2008. "Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector," Applied Energy, Elsevier, vol. 85(4), pages 271-296, April.
    10. Hanne Marit Dalen & Bodil M. Larsen, 2013. "Residential end-use electricity demand. Development over time," Discussion Papers 736, Statistics Norway, Research Department.
    11. Hannah Goozee, 2017. "Energy, Poverty and Development: A Primer for the Sustainable Development Goals," Working Papers id:11933, eSocialSciences.
    12. Fan Zhang, 2015. "Energy Price Reform and Household Welfare: The Case of Turkey," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    13. Muhammad Akmal & David I. Stern, 2001. "Residential energy demand in Australia: an application of dynamic OLS," Working Papers in Ecological Economics 0104, Australian National University, Centre for Resource and Environmental Studies, Ecological Economics Program.
    14. Muhammad, Akmal, 2002. "The structure of consumer energy demand in Australia: an application of a dynamic almost ideal demand system," 2002 Conference (46th), February 13-15, 2002, Canberra, Australia 125050, Australian Agricultural and Resource Economics Society.
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    1. Christophe Courbage & Henri Loubergé & Béatrice Rey, 2017. "On the properties of non-monetary measures for risks," Working Papers halshs-01471888, HAL.
    2. Pierre Picard, 2020. "Splitting Risks in Insurance Markets With Adverse Selection," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 997-1033, December.
    3. Emily Norman Zietz, 2003. "An Examination of the Demand for Life Insurance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 6(2), pages 159-191, September.

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    1. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    2. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    3. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.

  77. BAUWENS, Luc & LUBRANO, Michel, 1991. "Bayesian diagnostics for heterogeneity," LIDAM Reprints CORE 963, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. LUBRANO, Michel, 1998. "Smooth transition GARCH models: a Bayesian perspective," LIDAM Discussion Papers CORE 1998066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Lee, Grace H.Y. & Azali, M., 2012. "Is East Asia an optimum currency area?," Economic Modelling, Elsevier, vol. 29(2), pages 87-95.

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    1. Kleibergen, F.R. & van Dijk, H.K., 1997. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Econometric Institute Research Papers EI 9714/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2002. "Functional approximations to posterior densities: a neural network approach to efficient sampling," Econometric Institute Research Papers EI 2002-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Lennart F. Hoogerheide & Johan F. Kaashoek, 2004. "Functional Approximations to Likelihoods/Posterior Densities: A Neural Network Approach to Efficient Sampling," Computing in Economics and Finance 2004 74, Society for Computational Economics.

  79. ZELLNER, A. & BAUWENS, Luc & VAN DIJK, H., 1987. "Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods," LIDAM Discussion Papers CORE 1987056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Kajal Lahiri & Chuanming Gao, 2001. "A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Discussion Papers 01-15, University at Albany, SUNY, Department of Economics.
    2. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2012. "Bayesian model averaging in the instrumental variable regression model," Journal of Econometrics, Elsevier, vol. 171(2), pages 237-250.
    3. Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
    4. Frank Kleibergen & Eric Zivot, 2003. "Bayesian and Classical Approaches to Instrumental Variable Regression," Working Papers UWEC-2002-21-P, University of Washington, Department of Economics.
    5. Pholo Bala, Alain, 2009. "Urban concentration and economic growth: checking for specific regional effects," LIDAM Discussion Papers CORE 2009038, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.
    7. van Dijk, H.K., 2002. "On Bayesian structural inference in a simultaneous equation model," Econometric Institute Research Papers EI 2002-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & van DIJK, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," LIDAM Reprints CORE 1922, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Kien C. Tran & Mike G. Tsionas, 2022. "Instrumental Variables Estimation without Outside Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 489-506, September.
    10. Steel, M.F.J., 1989. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM b3f4c27f-4dab-46b3-9587-6, Tilburg University, School of Economics and Management.
    11. Nascimento, Marcus Gerardus Lavagnole & Abanto-Valle, Carlos Antonio & Mendonça, Mario Jorge, 2019. "Multivariate Spatial IV Regression," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 38(2), January.
    12. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.
    13. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
    14. Kwan, Yum K., 1998. "Asymptotic Bayesian analysis based on a limited information estimator," Journal of Econometrics, Elsevier, vol. 88(1), pages 99-121, November.
    15. Scott E. Atkinson & Jeffrey H. Dorfman, 2009. "Feasible estimation of firm-specific allocative inefficiency through Bayesian numerical methods," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 675-697.
    16. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    17. Dellaportas, Petros & Tsionas, Mike G., 2019. "Importance sampling from posterior distributions using copula-like approximations," Journal of Econometrics, Elsevier, vol. 210(1), pages 45-57.
    18. Chao, J. C. & Phillips, P. C. B., 1998. "Posterior distributions in limited information analysis of the simultaneous equations model using the Jeffreys prior," Journal of Econometrics, Elsevier, vol. 87(1), pages 49-86, August.
    19. Steel, M.F.J., 1988. "Seemingly unrelated regression equation systems under diffuse stochastic prior information : A recursive analytical approach," Discussion Paper 1988-5, Tilburg University, Center for Economic Research.
    20. Radchenko, Stanislav & Tsurumi, Hiroki, 2006. "Limited information Bayesian analysis of a simultaneous equation with an autocorrelated error term and its application to the U.S. gasoline market," Journal of Econometrics, Elsevier, vol. 133(1), pages 31-49, July.
    21. Arnold Zellner & Tomohiro Ando & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2011. "Instrumental Variables, Errors in Variables, and Simultaneous Equations Models: Applicability and Limitations of Direct Monte Carlo," Tinbergen Institute Discussion Papers 11-137/4, Tinbergen Institute.
    22. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2013. "Historical Developments in Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 13-191/III, Tinbergen Institute.
    23. Dorfman, Jeffrey H., 1995. "A numerical bayesian test for cointegration of AR processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 289-324.
    24. John C. Chao & Peter C.B. Phillips, 1996. "Bayesian Posterior Distributions in Limited Information Analysis of the Simultaneous Equations Model Using the Jeffreys Prior," Cowles Foundation Discussion Papers 1137, Cowles Foundation for Research in Economics, Yale University.
    25. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    26. Heckelei, Thomas & Mittelhammer, Ron C., 2003. "Bayesian bootstrap multivariate regression," Journal of Econometrics, Elsevier, vol. 112(2), pages 241-264, February.
    27. Hoogerheide, L.F. & Kleibergen, F.R. & van Dijk, H.K., 2006. "Natural conjugate priors for the instrumental variables regression model applied to the Angrist-Krueger data," Econometric Institute Research Papers EI 2006-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    28. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
    29. Chuanming Gao & Kajal Lahiri, 2019. "A Comparison of Some Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Econometrics, MDPI, vol. 7(3), pages 1-28, July.
    30. Li, Mingliang & Mumford, Kevin J. & Tobias, Justin L., 2012. "A Bayesian analysis of payday loans and their regulation," Journal of Econometrics, Elsevier, vol. 171(2), pages 205-216.

  80. BAUWENS, Luc & RICHARD, Jean-François, 1985. "A 1-1 poly-t random variable generator with application to Monte Carlo integration," LIDAM Reprints CORE 644, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bauwens, L. & Dijk, H. K., 1989. "Bayesian Limited Information Analysis Revisited," Econometric Institute Archives 272386, Erasmus University Rotterdam.
    2. Steel, M.F.J. & Richard, J., 1989. "Bayesian multivariate exogeneity analysis : An application to a UK money demand equation," Other publications TiSEM 2978b800-0592-4480-a5db-3, Tilburg University, School of Economics and Management.
    3. Müller-Plantenberg, Nikolas, 2012. "Long swings in Japan’s current account and in the yen," Working Papers in Economic Theory 2012/08, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    4. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    5. SILVESTRINI, Andrea, 2010. "Testing fiscal sustainability in Poland: a Bayesian analysis of cointegration," LIDAM Reprints CORE 2220, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Steel, M.F.J., 1989. "A Bayesian analysis of simultaneous equation models by combining recursive analytical and numerical approaches," Other publications TiSEM b3f4c27f-4dab-46b3-9587-6, Tilburg University, School of Economics and Management.
    7. Hop, J. P. & van Duk, H. K., 1990. "Two Algorithms For The Computation Of Posterior Moments And Densities Using Monte Carlo Integration," Econometric Institute Archives 272483, Erasmus University Rotterdam.
    8. Koop, G. & Strachan, R.W. & van Dijk, H.K. & Villani, M., 2005. "Bayesian approaches to cointegratrion," Econometric Institute Research Papers EI 2005-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
    10. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
    11. W.E. Griffiths & Ma. Rebecca Valenzuela, 2004. "Gibbs Samplers for a Set of Seemingly Unrelated Regressions," Department of Economics - Working Papers Series 912, The University of Melbourne.

  81. BAUWENS, Luc & d'ALCANTARA, Gonzague, 1983. "An export model for the Belgian industry," LIDAM Reprints CORE 533, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Bradley, John & Modesto, Leonor & Sosvilla-Rivero, Simon, 1995. "HERMIN : A macroeconometric modelling framework for the EU periphery," Economic Modelling, Elsevier, vol. 12(3), pages 221-247, July.
    2. Bradley, John & Fanning, Connell & Prendergast, Canice & Wynne, Mark, 1985. "Medium-Term Analysis of Fiscal Policy in Ireland: A Macroeconometric Study of the Period 1967-1980," Research Series, Economic and Social Research Institute (ESRI), number GRS122.

Articles

  1. Bauwens, Luc & Xu, Yongdeng, 2023. "DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations," International Journal of Forecasting, Elsevier, vol. 39(2), pages 938-955.
    See citations under working paper version above.
  2. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    See citations under working paper version above.
  3. Bauwens, Luc & Chevillon, Guillaume & Laurent, Sébastien, 2023. "We modeled long memory with just one lag!," Journal of Econometrics, Elsevier, vol. 236(1).
    See citations under working paper version above.
  4. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," Journal of Econometrics, Elsevier, vol. 217(2), pages 496-522.
    See citations under working paper version above.
  5. Maciej Augustyniak & Luc Bauwens & Arnaud Dufays, 2019. "A New Approach to Volatility Modeling: The Factorial Hidden Markov Volatility Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 696-709, October.

    Cited by:

    1. Rombouts, Jeroen V.K. & Stentoft, Lars & Violante, Francesco, 2020. "Dynamics of variance risk premia: A new model for disentangling the price of risk," Journal of Econometrics, Elsevier, vol. 217(2), pages 312-334.
    2. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    3. Zhang, Xiaoyuan & Zhang, Tianqi, 2023. "On pricing double-barrier options with Markov regime switching," Finance Research Letters, Elsevier, vol. 51(C).
    4. Augustyniak, Maciej & Dufays, Arnaud, 2018. "Modeling macroeconomic series with regime-switching models characterized by a high-dimensional state space," Economics Letters, Elsevier, vol. 170(C), pages 122-126.
    5. Mawuli Segnon & Bjorn Schulte-Tillmann & Riza Demirer & Rangan Gupta, 2025. "Deglobalization and Foreign Exchange Volatility: The Role of Supply Chain Pressures," Working Papers 202506, University of Pretoria, Department of Economics.
    6. Xu Cheng & Eric Renault & Paul Sangrey, 2024. "Identifying the Volatility Risk Price Through the Leverage Effect," PIER Working Paper Archive 24-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Bjoern Schulte-Tillman & Mawuli Segnon & Bernd Wilfling, 2022. "Financial-market volatility prediction with multiplicative Markov-switching MIDAS components," CQE Working Papers 9922, Center for Quantitative Economics (CQE), University of Muenster.
    8. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.

  6. Yukai Yang & Luc Bauwens, 2018. "State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering," Econometrics, MDPI, vol. 6(4), pages 1-22, December.
    See citations under working paper version above.
  7. Bauwens, Luc & Braione, Manuela & Storti, Giuseppe, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," Econometrics and Statistics, Elsevier, vol. 1(C), pages 40-61.
    See citations under working paper version above.
  8. Luc Bauwens & Jean-François Carpantier & Arnaud Dufays, 2017. "Autoregressive Moving Average Infinite Hidden Markov-Switching Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 162-182, April.
    See citations under working paper version above.
  9. Bauwens, Luc & Grigoryeva, Lyudmila & Ortega, Juan-Pablo, 2016. "Estimation and empirical performance of non-scalar dynamic conditional correlation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 17-36.
    See citations under working paper version above.
  10. Luc Bauwens & Edoardo Otranto, 2016. "Modeling the Dependence of Conditional Correlations on Market Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 254-268, April.
    See citations under working paper version above.
  11. Luc Bauwens & Manuela Braione & Giuseppe Storti, 2016. "Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices," Annals of Economics and Statistics, GENES, issue 123-124, pages 103-134.
    See citations under working paper version above.
  12. Luc Bauwens & Gary Koop & Dimitris Korobilis & Jeroen V.K. Rombouts, 2015. "The Contribution of Structural Break Models to Forecasting Macroeconomic Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 596-620, June.
    See citations under working paper version above.
  13. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.
    See citations under working paper version above.
  14. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    See citations under working paper version above.
  15. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    See citations under working paper version above.
  16. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 171-184.
    See citations under working paper version above.
  17. Bauwens, Luc & Rombouts, Jeroen V.K., 2012. "On marginal likelihood computation in change-point models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3415-3429.
    See citations under working paper version above.
  18. Luc Bauwens & Giordano Mion & Jacques-François Thisse, 2011. "The Resistible Decline of European Science," Recherches économiques de Louvain, De Boeck Université, vol. 77(4), pages 5-31.
    See citations under working paper version above.
  19. Luc Bauwens & Arie Preminger & Jeroen V. K. Rombouts, 2010. "Theory and inference for a Markov switching GARCH model," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 218-244, July.
    See citations under working paper version above.
  20. Bauwens, Luc & Ben Omrane, Walid & Rengifo, Erick, 2010. "Intradaily dynamic portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2400-2418, November.

    Cited by:

    1. Kotchoni, Rachidi, 2012. "Applications of the characteristic function-based continuum GMM in finance," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3599-3622.
    2. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    3. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.

  21. Bauwens, Luc & Sucarrat, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: A forecast evaluation," International Journal of Forecasting, Elsevier, vol. 26(4), pages 885-907, October.
    See citations under working paper version above.
  22. Bauwens Luc & Storti Giuseppe, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-33, May.
    See citations under working paper version above.
  23. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    See citations under working paper version above.
  24. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    See citations under working paper version above.
  25. Luc Bauwens & Alvaro Escribano & Michel Lubrano, 2007. "The Econometrics of Industrial Organization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1153-1156.

    Cited by:

    1. Ooms, M., 2008. "Trends in Applied Econometrics Software Development 1985-2008, an analysis of Journal of Applied Econometrics research articles, software reviews, data and code," Serie Research Memoranda 0021, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.

  26. L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, July.
    See citations under working paper version above.
  27. Luc Bauwens & Michel Lubrano, 2007. "Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 469-486.
    See citations under working paper version above.
  28. L. Bauwens & J. V. K. Rombouts, 2007. "Bayesian Clustering of Many Garch Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 365-386.
    See citations under working paper version above.
  29. Bauwens, Luc, 2006. "Econometric Analysis of Intra-daily Trading Activity on the Tokyo Stock Exchange," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 24(1), pages 1-23, March.
    See citations under working paper version above.
  30. Luc Bauwens & Nikolaus Hautsch, 2006. "Stochastic Conditional Intensity Processes," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 450-493.
    See citations under working paper version above.
  31. Luc Bauwens & Winfried Pohlmeier & David Veredas, 2006. "Editor’s introduction," Empirical Economics, Springer, vol. 30(4), pages 791-794, January.

    Cited by:

    1. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).

  32. Bauwens, Luc & Peter Boswijk, H. & Urbain, Jean-Pierre, 2006. "Causality and exogeneity in econometrics," Journal of Econometrics, Elsevier, vol. 132(2), pages 305-309, June.

    Cited by:

    1. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in Quantiles and Dynamic Relations in Energy Markets," Working Papers 116, VATT Institute for Economic Research.
    2. Kyritsis, Evangelos & Andersson, Jonas, 2019. "Causality in quantiles and dynamic relations in energy markets: (De)tails matter," Energy Policy, Elsevier, vol. 133(C).
    3. SUCARRAT, Genaro, 2006. "The first stage in Hendry’s reduction theory revisited," LIDAM Discussion Papers CORE 2006082, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. White, Halbert, 2006. "Time-series estimation of the effects of natural experiments," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 527-566.

  33. Luc Bauwens & Dagfinn Rime & Genaro Sucarrat, 2006. "Exchange rate volatility and the mixture of distribution hypothesis," Empirical Economics, Springer, vol. 30(4), pages 889-911, January.
    See citations under working paper version above.
  34. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    See citations under working paper version above.
  35. Bauwens, Luc & Laurent, Sebastien, 2005. "A New Class of Multivariate Skew Densities, With Application to Generalized Autoregressive Conditional Heteroscedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 346-354, July.
    See citations under working paper version above.
  36. Bauwens, Luc & Ben Omrane, Walid & Giot, Pierre, 2005. "News announcements, market activity and volatility in the euro/dollar foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1108-1125, November.
    See citations under working paper version above.
  37. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    See citations under working paper version above.
  38. Bauwens, Luc & Lubrano, Michel & van Dijk, Herman K., 2004. "Recent advances in Bayesian econometrics," Journal of Econometrics, Elsevier, vol. 123(2), pages 197-199, December.

    Cited by:

    1. Majda Benzidia & Michel Lubrano, 2016. "A Bayesian Look at American Academic Wages: The Case of Michigan State University," Working Papers halshs-01358882, HAL.

  39. Bauwens, Luc & Veredas, David, 2004. "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," Journal of Econometrics, Elsevier, vol. 119(2), pages 381-412, April.
    See citations under working paper version above.
  40. Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
    See citations under working paper version above.
  41. Luc Bauwens & Pierre Giot, 2003. "Asymmetric ACD models: Introducing price information in ACD models," Empirical Economics, Springer, vol. 28(4), pages 709-731, November.
    See citations under working paper version above.
  42. Michel Lubrano & Luc Bauwens & Alan Kirman & Camelia Protopopescu, 2003. "Ranking Economics Departments in Europe: A Statistical Approach," Journal of the European Economic Association, MIT Press, vol. 1(6), pages 1367-1401, December.
    See citations under working paper version above.
  43. Bauwens, Luc & Lubrano, Michel, 2002. "Bayesian option pricing using asymmetric GARCH models," Journal of Empirical Finance, Elsevier, vol. 9(3), pages 321-342, August.
    See citations under working paper version above.
  44. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
    See citations under working paper version above.
  45. Luc Bauwens & Michel Lubrano, 1998. "Bayesian inference on GARCH models using the Gibbs sampler," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 23-46.
    See citations under working paper version above.
  46. Bauwens, Luc & Polasek, Wolfgang & van Dijk, Herman K., 1996. "Editor's introduction," Journal of Econometrics, Elsevier, vol. 75(1), pages 1-5, November.

    Cited by:

    1. Villani, Mattias & Larsson, Rolf, 2004. "The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis," Working Paper Series 175, Sveriges Riksbank (Central Bank of Sweden).

  47. Bauwens, Luc & Fiebig, Denzil G & Steel, Mark F J, 1994. "Estimating End-Use Demand: A Bayesian Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 221-231, April.
    See citations under working paper version above.
  48. Luc Bauwens & Michel Lubrano, 1991. "Bayesian Diagnostics for Heterogeneity," Annals of Economics and Statistics, GENES, issue 20-21, pages 17-40.
    See citations under working paper version above.
  49. Luc Bauwens, 1991. "The 'pathologie' of the Natural Conjugate Prior Density in the Regression Model," Annals of Economics and Statistics, GENES, issue 23, pages 49-64.
    See citations under working paper version above.
  50. Balassa, Bela & Bauwens, Luc, 1988. "The determinants of intra-European trade in manufactured goods," European Economic Review, Elsevier, vol. 32(7), pages 1421-1437, September.

    Cited by:

    1. Mary Lovely & Douglas Nelson, 2002. "Intra-industry trade as an indicator of labor market adjustment," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 179-206, June.
    2. Justyna Lapinska, 2016. "Determinant Factors Of Intra-Industry Trade: The Case Of Poland And Its European Union Trading Partners," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(2), pages 251-264, June.
    3. Venables, Anthony & Rice, Patricia & Stewart, Martin, 2002. "The Geography of Intra-Industry Trade: Empirics," CEPR Discussion Papers 3368, C.E.P.R. Discussion Papers.
    4. Kwanho Shin & Yunjong Wang, 2003. "Trade Integration and Business Cycle Synchronization in East Asia," ISER Discussion Paper 0574, Institute of Social and Economic Research, Osaka University.
    5. Fischer, Manfred M. & Johannson, Börje, 1994. "Opening Up International Trade in Eastern European Countries. Consequences for Aggregate Trade Flows in the Rhine-Main-Danube Area," MPRA Paper 77812, University Library of Munich, Germany.
    6. Martin Andresen, 2010. "A cross-industry analysis of intra-industry trade measurement thresholds: Canada and the United States, 1988–1999," Empirical Economics, Springer, vol. 38(3), pages 793-808, June.
    7. Das, Gouranga G., 2007. "Intra-Industry Trade and Development: Revisiting Theory, Measurement and New Evidences," MPRA Paper 37260, University Library of Munich, Germany, revised 01 Sep 2008.
    8. Béatrice Colin-Sédillot, 1994. "Les échanges industriels entre la France et les pays d'Europe centrale et orientale : premières tendances de la spécialisation," Économie et Statistique, Programme National Persée, vol. 279(1), pages 69-80.
    9. Dilip Nachane & Amlendu Dubey, 2018. "India in the globalized economy : Growth spillovers & business cycle synchronization," International Economics and Economic Policy, Springer, vol. 15(1), pages 89-115, January.
    10. Das, Gouranga G., 2002. "Cross-Country Analysis of Empirical Evidences of Intra-industry Trade in Manufactures for Dynamic Asian and Other Developing Economies: Implications for Economic Growth and Development," MPRA Paper 37916, University Library of Munich, Germany, revised 2002.
    11. Kwanho Shin & Yunjong Wang, 2003. "Monetary Integration Ahead of Trade Integration in East Asia?," ISER Discussion Paper 0572, Institute of Social and Economic Research, Osaka University.
    12. Fedoseeva, Svetlana & Zeidan, Rodrigo, 2016. "A dead-end tunnel or the light at the end of it: The role of BRICs in European exports," Economic Modelling, Elsevier, vol. 59(C), pages 237-248.

  51. Bela Balassa & Luc Bauwens, 1988. "Inter-industry and intra-industry specialization in manufactured goods," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 124(1), pages 1-13, March.

    Cited by:

    1. Jianhong Zhang & Arjen van Witteloostuijn & Chaohong Zhou, 2005. "Chinese Bilateral Intra-Industry Trade: A Panel Data Study for 50 Countries in the 1992–2001 Period," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 141(3), pages 510-540, October.
    2. Venables, Anthony & Rice, Patricia & Stewart, Martin, 2002. "The Geography of Intra-Industry Trade: Empirics," CEPR Discussion Papers 3368, C.E.P.R. Discussion Papers.
    3. Das, Gouranga G., 2007. "Intra-Industry Trade and Development: Revisiting Theory, Measurement and New Evidences," MPRA Paper 37260, University Library of Munich, Germany, revised 01 Sep 2008.
    4. Maylene Y. Damoense-Azevedo & André C. Jordaan, 2012. "Factors influencing bilateral intra-industry trade in the auto industry: the case of South Africa," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-82.
    5. Das, Gouranga G., 2002. "Cross-Country Analysis of Empirical Evidences of Intra-industry Trade in Manufactures for Dynamic Asian and Other Developing Economies: Implications for Economic Growth and Development," MPRA Paper 37916, University Library of Munich, Germany, revised 2002.

  52. Zellner, Arnold & Bauwens, Luc & Van Dijk, Herman K., 1988. "Bayesian specification analysis and estimation of simultaneous equation models using Monte Carlo methods," Journal of Econometrics, Elsevier, vol. 38(1-2), pages 39-72.
    See citations under working paper version above.
  53. Balassa, Bela & Bauwens, Luc, 1987. "Intra-industry Specialisation in a Multi-country and Multi-industry Framework," Economic Journal, Royal Economic Society, vol. 97(388), pages 923-939, December.

    Cited by:

    1. Gervais, Antoine, 2019. "Indirect measures of trade costs: Limitations and caveats," Economics Letters, Elsevier, vol. 176(C), pages 96-102.
    2. J. Hanna & L. L鶩 & S. Petit, 2015. "Intra-tourism trade, income distribution and tourism endowment: an econometric investigation," Applied Economics, Taylor & Francis Journals, vol. 47(21), pages 2184-2200, May.
    3. Godwin Odo ONOGWU, 2014. "Determinants of the intra-industry trade in cereal and miscellaneous edible preparations: the evidence for Nigeria and the ECOWAS partners," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(1), pages 21-30.
    4. Soumyananda Dinda, 2014. "Climate Change: An Emerging Trade Opportunity in South Asia," South Asian Journal of Macroeconomics and Public Finance, , vol. 3(2), pages 221-239, December.
    5. Filippo Reganati & Rosanna Pittiglio, 2007. "Two-Way International Trade And Production In Italy: A Country/Industry Specific Analysis," Quaderni DSEMS 19-2007, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    6. Seyed-Rohollah Ahmadi, 2016. "The Impact of Sanction on Bilateral Intra-Industry Trade between Iran and SCO Countries," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 20(3), pages 277-293, Summer.
    7. Tripathi, Sabyasachi & Leitão, Nuno Carlos, 2013. "India’s Trade and Gravity Model: A Static and Dynamic Panel Data," MPRA Paper 45502, University Library of Munich, Germany.
    8. Veeramani C, 2001. "India's intra-industry trade under economic liberalization: Trends and country specific factors," Centre for Development Studies, Trivendrum Working Papers 313, Centre for Development Studies, Trivendrum, India.
    9. BELLINO, Antonella & CELI, Giuseppe, 2016. "The Migration-Trade Nexus in the Presence of Vertical and Horizontal Product Differentiation," CELPE Discussion Papers 137, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    10. Volodymyr Toryanyk & Vladimir Dzhyndzhoian & Yevhen Namliyev, 2018. "Competitiveness Of Ukrainian Export-Oriented Fields," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 4(3).
    11. David Greenaway & Johan Torstensson, 1997. "Back to the future: Taking stock on intra-industry trade," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 133(2), pages 249-269, June.
    12. Gnidchenko, A., 2018. "Structural Transformation in International Trade (2001-2015): Towards a New Classification," Journal of the New Economic Association, New Economic Association, vol. 37(1), pages 62-86.
    13. Nuno Carlos Leit o & Muhammad Shahbaz, 2012. "Liberalization and United States' Intra-Industry Trade," International Journal of Economics and Financial Issues, Econjournals, vol. 2(4), pages 505-512.
    14. Kandogan, Yener, 2009. "A Gravity Model for Components of Imports," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 5(01-2), pages 1-17, April.
    15. Rosanna Pittiglio, Rosanna, 2008. "The intra-industry trade for a high-income country: new empirical evidence for Italy," SIRE Discussion Papers 2008-17, Scottish Institute for Research in Economics (SIRE).
    16. Saeed Rasekhi & Shideh Shojaee, 2012. "Country-specific Determinants of Intra Industry Trade Types of Agricultural Sector in Selected Developing Countries," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 17(1), pages 85-99, winter.
    17. Andriamananjara, Shuby & Nash, John, 1997. "Have trade policy reforms led to greater openness in developing countries : evidence from readily available trade data," Policy Research Working Paper Series 1730, The World Bank.
    18. Aliyu, Shehu Usman Rano & Bawa, Sani, 2013. "Gravity Model by Panel Data Approach: Empirical Evidence from Nigeria," MPRA Paper 52549, University Library of Munich, Germany, revised 04 Jun 2014.
    19. Robert Ballance & Helmut Forstner & W. Sawyer, 1992. "An empirical examination of the role of vertical product differentiation in north-south trade," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 128(2), pages 330-338, June.
    20. Bellino Antonella & Celi Giuseppe, 2016. "The Role of Migration in the Variety and Quality of Trade: Evidence from Germany," German Economic Review, De Gruyter, vol. 17(1), pages 1-25, February.
    21. Fukao, Kyoji & Ishido, Hikari & Ito, Keiko, 2003. "Vertical intra-industry trade and foreign direct investment in East Asia," Journal of the Japanese and International Economies, Elsevier, vol. 17(4), pages 468-506, December.
    22. Sourish Dutta, 2022. "Two Approaches of Measuring Intra-industry Trade," Working Papers hal-03679377, HAL.
    23. Dutta, Sourish, 2022. "Measuring Horizontal and Vertical Differentiation in Intra-industry Trade," SocArXiv rudtq, Center for Open Science.
    24. Snježana Brkić & Radovan Kastratović & Mirela Abidović Salkica, 2021. "Patterns And Determinants Of Intra-Industry Trade In Agri-Food Products Between Bosnia And Herzegovina And Cefta 2006," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 66(229), pages 7-36, April – J.
    25. Jeremiás Máté Balogh & Nuno Carlos Leitão, 2019. "A gravity approach of agricultural trade: The nexus of the EU and African, Caribbean and Pacific countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(11), pages 509-519.
    26. Dutta, Sourish, 2022. "The Problem of Measuring Intra-industry Trade," MPRA Paper 113194, University Library of Munich, Germany.
    27. E.M. Ekanayake & Mihalis Halkides & Robin Rance & Iliana Filyanova, 2007. "Intra-Industry Trade Between The United States And Latin American Countries," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 1(2), pages 109-124.
    28. Leitão, Nuno Carlos & Tripathi, Sabyasachi, 2013. "Portuguese Trade and European Union: The Gravity Model," MPRA Paper 45994, University Library of Munich, Germany.
    29. Celi, Giuseppe, 2010. "Empirical Explanation of Vertical and Horizontal Intra-industry Trade in the UK: A Comment - Spiegazioni empiriche del commercio intra-industriale verticale ed orizzontale del Regno Unito: un commento," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 63(1), pages 53-90.
    30. Davis, Donald R., 1995. "Intra-industry trade: A Heckscher-Ohlin-Ricardo approach," Journal of International Economics, Elsevier, vol. 39(3-4), pages 201-226, November.
    31. Yener Kandogan, 2005. "Trade Creation and Diversion Effects of Europe???s Regional Liberalization Agreements," William Davidson Institute Working Papers Series wp746, William Davidson Institute at the University of Michigan.
    32. Don Clark & Denise Stanley, 2003. "Determinants Of Intraindustry Trade Between The United States And Industrial Nations," International Economic Journal, Taylor & Francis Journals, vol. 17(3), pages 1-17.
    33. Saeed Rasekhi & Shideh Sadat Shojaee, 2012. "Determinant factors of vertical intra industry trade in agricultural sector: A study of Iran and her main trading partners," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 58(4), pages 180-190.
    34. Orszaghova, Lucia & Schudel, Willem & Dautović, Ernest, 2014. "Intra-industry trade between CESEE countries and the EU15," Working Paper Series 1719, European Central Bank.
    35. Ernest Dautović & Lucia Orszaghova & Willem Schudel, 2017. "Converging in divergent ways," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 25(4), pages 625-662, October.
    36. Dutta, Sourish, 2023. "Horizontal and Vertical Differentiation: Approaching Endogenous Measurement in Intra-industry Trade," EconStor Preprints 275680, ZBW - Leibniz Information Centre for Economics.
    37. Filippo Reganati & Rosanna Pittiglio, 2005. "Vertical Intra-Industry Trade: Patterns And Determinants In The Italian Case," Quaderni DSEMS 06-2005, Dipartimento di Scienze Economiche, Matematiche e Statistiche, Universita' di Foggia.
    38. Lars Nilsson, 1999. "Two-way trade between unequal partners: The EU and the developing countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(1), pages 102-127, March.
    39. Venables, Anthony & Rice, Patricia & Stewart, Martin, 2002. "The Geography of Intra-Industry Trade: Empirics," CEPR Discussion Papers 3368, C.E.P.R. Discussion Papers.
    40. Nuno Carlos LEITÃO & Marius-Razvan SURUGIU & Camelia SURUGIU, 2014. "Romanian intra-industry trade: a panel data approach," EuroEconomica, Danubius University of Galati, issue 2(33), pages 7-18, November.
    41. Yener Kandogan, 2009. "Trade Creation and Diversion Effects of Europe's Regional Liberalization Agreements," International Economic Journal, Taylor & Francis Journals, vol. 23(4), pages 591-615.
    42. Joan A. Martín & Vicente Orts, 2001. "A two-stage analysis of monopolistic competition models of intraindustry trade," Investigaciones Economicas, Fundación SEPI, vol. 25(2), pages 315-333, May.
    43. Muhammad Shahbaz & Nuno Carlos Leit o & Muhammad Sabihuddin Butt, 2012. "Pakistan Intra-Industry Trade: A Panel Data Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 225-232.
    44. Matthew A. Cole & Robert J. R. Elliott, 2003. "Do Environmental Regulations Influence Trade Patterns? Testing Old and New Trade Theories," The World Economy, Wiley Blackwell, vol. 26(8), pages 1163-1186, August.
    45. Stefanescu, Razvan & Dumitriu, Ramona, 2007. "Impact of the EU adhesion on the indirect taxes for the intra - community imports," MPRA Paper 41779, University Library of Munich, Germany, revised 02 Oct 2007.
    46. Moshirian, Fariborz & Li, Donghui & Sim, Ah-Boon, 2005. "Intra-industry trade in financial services," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1090-1107, November.
    47. M. Choudhary & Paul Temple & Lei Zhao, 2013. "Taking the measure of things: the role of measurement in EU trade," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(1), pages 75-109, February.
    48. Sheldon, Ian, 1989. "Intra-Industry Trade and Specialisation in Processed Agricultural Products: Theory and Issues," Occasional Papers 232829, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    49. Martin Andresen, 2010. "A cross-industry analysis of intra-industry trade measurement thresholds: Canada and the United States, 1988–1999," Empirical Economics, Springer, vol. 38(3), pages 793-808, June.
    50. Sagnik Bagchi & Surajit Bhattacharyya, 2019. "Country-Specific Determinants of Intra-Industry Trade in India," Foreign Trade Review, , vol. 54(3), pages 129-158, August.
    51. Amadeo Navarro Zapata & María Arrazola & José Hevia, 2023. "Technological intensity in manufacturing trade between ASEAN and the EU: challenges and opportunities," Asia Europe Journal, Springer, vol. 21(1), pages 23-42, March.
    52. Joan Martín-Montaner & Vicente Ríos, 2002. "Vertical specialization and intra-industry trade: The role of factor endowments," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 340-365, June.
    53. Dutta, Sourish, 2023. "Endogenous Horizontal and Vertical Differentiation: Measuring Value Added in Intra-industry Trade," SocArXiv zqb9n, Center for Open Science.
    54. Joakim Gullstrand, 2002. "Does the measurement of intra-industry trade matter?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(2), pages 317-339, June.
    55. Aturupane, Chonira & Djankov, Simeon & Hoekman, Bernard, 1997. "Determinants of intra-industry trade between East and West Europe," Policy Research Working Paper Series 1850, The World Bank.
    56. Pinar Narin Emirhan, 2005. "Determinants of Vertical Intra-Industry Trade of Turkey: Panel Data Approach," Discussion Paper Series 05/05, Dokuz Eylül University, Faculty of Business, Department of Economics, revised 23 Nov 2005.
    57. Kwok Tong Soo, 2016. "Intra-industry trade: A Krugman–Ricardo Model and Data," Economica, London School of Economics and Political Science, vol. 83(330), pages 338-355, April.
    58. Moshirian, Fariborz, 2006. "Aspects of international financial services," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1057-1064, April.
    59. Dutta, Sourish, 2023. "Endogenous Horizontal and Vertical Differentiation: Measuring Value Added in Intra-industry Trade," SocArXiv zqb9n_v1, Center for Open Science.
    60. Chonira Aturupane & Simeon Djankov & Bernard Hoekman, 1999. "Horizontal and vertical intra-industry trade between Eastern Europe and the European union," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(1), pages 62-81, March.
    61. Bruno Carramenha, 2021. "Diversity Management: An Overlook on Brazil's Largest Companies," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 4, May - Aug.
    62. Haq, Zahoor Ul & Meilke, Karl D., 2008. "Differentiated Agri-Food Product Trade and the Linder Effect," Working Papers 46629, Canadian Agricultural Trade Policy Research Network.
    63. Justyna Lapinska, 2014. "Determinants of Intra-Industry Trade in Agricultural and Food Products between Poland and EU Countries," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 3, pages 159-172, September.
    64. Sawyer, William C. & Sprinkle, Richard L. & Tochkov, Kiril, 2010. "Patterns and determinants of intra-industry trade in Asia," Journal of Asian Economics, Elsevier, vol. 21(5), pages 485-493, October.
    65. Miria Pigato, 2009. "Strengthening China's and India's Trade and Investment Ties to the Middle East and North Africa," World Bank Publications - Books, The World Bank Group, number 2626.
    66. Imre Ferto & Károly Attila Soós, 2012. "Controversial issues in factors determining intra-industry trade," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 132-148.
    67. Ruhul Salim & Amirul Islam & Harry Bloch, 2018. "Patterns And Determinants Of Intra-Industry Trade In Southeast Asia: Evidence From The Automotive And Electrical Appliances Sectors," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(03), pages 647-665, June.
    68. M A Cole & R J R Elliott, 2003. "Do Environmental Regulations Influence Trade Patterns? Testing New and Old Trade Theories," Economics Discussion Paper Series 0310, Economics, The University of Manchester.
    69. Ka Ming Cheng, 2021. "Financial And Insurance Services Trade: Does Exchange Rate Or Income Matter?," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 494-509, January.
    70. J. Vicente Blanes Cristobal, 1997. "Comercio intra-industrial y presencia de capital extranjero en España," Working Papers wpdea9705, Department of Applied Economics at Universitat Autonoma of Barcelona.
    71. Nuno Leitão & Horácio Faustino & Yushi Yoshida, 2009. "Determinants of Vertical Intra-Industry Trade in the Automobile Manufacturing Sector: globalization and fragmentation," Working Papers Department of Economics 2009/06, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    72. Ecochard, Pierre & Fontagné, Lionel & Gaulier, Guillaume & Zignago, Soledad, 2005. "Intra-industry trade and regional integration," MPRA Paper 44182, University Library of Munich, Germany.
    73. Sagnik Bagchi & Surajit Bhattacharyya, 2021. "Industry-level determinants of India’s vertical and horizontal IIT," Indian Economic Review, Springer, vol. 56(1), pages 113-145, June.
    74. Shahbaz, Muhammad & Leitão, Nuno Carlos, 2011. "Intra-industry trade: The Pakistan experience," MPRA Paper 28665, University Library of Munich, Germany.
    75. Sledziewska, Katarzyna & Czarny, E., 2016. "Determinants Of Intra-Industry Trade Of The New Member States," Journal of Economic and Social Development, Clinical Journals Press, vol. 3(01), pages 01-10, March.
    76. Hirschberg, Joseph G. & Sheldon, Ian M. & Dayton, James R., 1992. "An Analysis of Bilateral Intra-Industry Trade in the Food Processing Sector," Occasional Papers 233083, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    77. J. Vicente Blanes Cristobal, 1997. "El comercio intra-industrial de España con los países de la comunidad europea(1982-1990):determinantes y efectos de su integración," Working Papers wpdea9704, Department of Applied Economics at Universitat Autonoma of Barcelona.
    78. McCorriston, Steve & Sheldon, Ian M., 1990. "Intra-Industry Trade and Specialisation in Processed Agricultural Products: The Case of the US and EC," Occasional Papers 232835, Regional Research Project NC-194: Organization and Performance of World Food Systems.
    79. Maza, Adolfo & Gutiérrez-Portilla, Paula, 2022. "Outward FDI and exports relation: A heterogeneous panel approach dealing with cross-sectional dependence," International Economics, Elsevier, vol. 170(C), pages 174-189.
    80. Brahim Razgallah, 2004. "La théorie des ZMO s'applique-t-elle aux pays en développement?," International Finance 0403003, University Library of Munich, Germany.
    81. Kwok Tong Soo, 2013. "Intra-industry trade," Working Papers 33867578, Lancaster University Management School, Economics Department.
    82. Maylene Y. Damoense-Azevedo & André C. Jordaan, 2012. "Factors influencing bilateral intra-industry trade in the auto industry: the case of South Africa," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-82.
    83. Jarko Fidrmuc & Daniela Grozea-Helmenstein & Andreas Wörgötter, 1999. "East-west intra-industry trade dynamics," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 135(2), pages 332-346, June.
    84. Robert C. Shelburne, 2002. "Bilateral Intra-Industry Trade in a Multi-Country Helpman-Krugman Model," International Economic Journal, Taylor & Francis Journals, vol. 16(4), pages 53-73.
    85. Rosanna Pittiglio & Filippo Reganati, 2012. "Vertical intra-industry trade in higher and lower quality: a new approach of measuring country-specific determinants," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 4(1/2), pages 44-62.
    86. Moshirian, Fariborz, 2004. "Financial services: Global perspectives," Journal of Banking & Finance, Elsevier, vol. 28(2), pages 269-276, February.
    87. Tsang, Cheuk Yan & Shakur, Shamim, 2017. "New Zealand’s Trade Prospects in an Uncertain Trans-Pacific Partnership (TPP) Environment: Results from Gravity Model," 2017 Conference, October 19-20, Rotorua, New Zealand 269528, New Zealand Agricultural and Resource Economics Society.
    88. Bo Carlsson, 1991. "Flexible manufacturing and U.S. trade performance," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 127(2), pages 300-322, June.
    89. Kwanho Shin & Yunjong Wang, 2003. "Monetary Integration Ahead of Trade Integration in East Asia?," ISER Discussion Paper 0572, Institute of Social and Economic Research, Osaka University.
    90. Frahan, Bruno Henry de & Tharakan, Joe, 1998. "Horizontal And Vertical Intra-Industry Trade In The Processed Food Sector," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20903, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    91. Clark, Don P., 2010. "Scale economies and intra-industry trade," Economics Letters, Elsevier, vol. 108(2), pages 190-192, August.
    92. Mónica Rivera, 2014. "Trade patterns in the process of European integration: Evidence for the intraindustrial exchanges of a Mediterranean peripheral region," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 227-249, January.

  54. Bauwens, Luc & Richard, Jean-Francois, 1985. "A 1-1 poly-t random variable generator with application to Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 19-46.
    See citations under working paper version above.
  55. Bauwens, Luc & d'Alcantara, Gonzague, 1983. "An export model for the Belgian industry," European Economic Review, Elsevier, vol. 22(3), pages 265-276.
    See citations under working paper version above.

Chapters

  1. Luc Bauwens & Dimitris Korobilis, 2013. "Bayesian methods," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 16, pages 363-380, Edward Elgar Publishing.
    See citations under working paper version above.
  2. Luc Bauwens & Dagfinn Rime & Genaro Sucarrat, 2008. "Exchange rate volatility and the mixture of distribution hypothesis," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 7-29, Springer.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), 2008. "High Frequency Financial Econometrics," Studies in Empirical Economics, Springer, number 978-3-7908-1992-2, December.

    Cited by:

    1. PESTIEAU, Pierre & RACIONERO, Maria, 2015. "Tagging with Leisure Needs," LIDAM Reprints CORE 2747, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    3. Juan D. Moreno-Ternero, 2010. "Voting over piece-wise linear tax methods," Working Papers 10.02, Universidad Pablo de Olavide, Department of Economics.
    4. GILLIS, Nicolas & GLINEUR, François, 2010. "On the geometric interpretation of the nonnegative rank," LIDAM Discussion Papers CORE 2010051, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Gautier, Axel & Wauthy, Xavier, 2012. "Competitively neutral universal service obligations," Information Economics and Policy, Elsevier, vol. 24(3), pages 254-261.
    6. GILLIS, Nicolas & GLINEUR, François, 2011. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Reprints CORE 2382, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Tim Bollerslev & Andrew J. Patton & Rogier Quaedvlieg, 2016. "Modeling and Forecasting (Un)Reliable Realized Covariances for More Reliable Financial Decisions," CREATES Research Papers 2016-10, Department of Economics and Business Economics, Aarhus University.
    9. SCHWARZ, Maik & VAN BELLEGEM, Sébastien & FLORENS, Jean - Pierre, 2010. "Nonparametric frontier estimation from noisy data," LIDAM Discussion Papers CORE 2010050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. MAULEON, Ana & VANNETELBOSCH, Vincent & VERGARI, Cecilia, 2010. "Unions' relative concerns and strikes in wage bargaining," LIDAM Discussion Papers CORE 2010076, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Michel Le Breton & Juan Moreno-Ternero & Alexei Savvateev & Shlomo Weber, 2013. "Stability and fairness in models with a multiple membership," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(3), pages 673-694, August.
    12. GILLIS, Nicolas & GLINEUR, François, 2010. "A multilevel approach for nonnegative matrix factorization," LIDAM Discussion Papers CORE 2010047, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. THISSE, Jacques-François, 2011. "Geographical economics: a historical perspective," LIDAM Reprints CORE 2351, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Helmuth Cremer & Firouz Gahvari & Pierre Pestieau, 2009. "Fertility, Human Capital Accumulation, and the Pension System," CESifo Working Paper Series 2736, CESifo.
    15. Marie-Louise Leroux & Grégory Ponthière, 2013. "Utilitarianism and unequal longevities: A remedy?," Post-Print hal-00813226, HAL.
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