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Consistent ranking of volatility models
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Cited by:
- Szabolcs Blazsek & Marco Villatoro, 2015. "Is Beta- t -EGARCH(1,1) superior to GARCH(1,1)?," Applied Economics, Taylor & Francis Journals, vol. 47(17), pages 1764-1774, April.
- Tae-Hwy Lee & Ekaterina Seregina & Yaojue Xu, 2023. "Elicitability and Encompassing for Volatility Forecasts by Bregman Functions," Working Papers 202311, University of California at Riverside, Department of Economics.
- Georgiana-Denisa Banulescu & Bertrand Candelon & Christophe Hurlin & Sébastien Laurent, 2014. "Do We Need Ultra-High Frequency Data to Forecast Variances?," Working Papers halshs-01078158, HAL.
- Bermudez, P. de Zea & Marín, J. Miguel & Rue, Håvard & Veiga, Helena, 2024.
"Integrated nested Laplace approximations for threshold stochastic volatility models,"
Econometrics and Statistics, Elsevier, vol. 30(C), pages 15-35.
- Zea Bermudez, Patrícia de & Rue, Havard, 2021. "Integrated nested Laplace approximations for threshold stochastic volatility models," DES - Working Papers. Statistics and Econometrics. WS 31804, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Neil Shephard & Ole E. Barndorff-Nielsen & Department of Mathematical Sciences & University of Aarhus & Denmark, 2005.
"Variation, jumps, market frictions and high frequency data in financial econometrics,"
Economics Series Working Papers
240, University of Oxford, Department of Economics.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," Economics Papers 2005-W16, Economics Group, Nuffield College, University of Oxford.
- Meng, Xiaochun & Taylor, James W., 2018. "An approximate long-memory range-based approach for value at risk estimation," International Journal of Forecasting, Elsevier, vol. 34(3), pages 377-388.
- Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009.
"Nuisance parameters, composite likelihoods and a panel of GARCH models,"
Economics Papers
2009-W12, Economics Group, Nuffield College, University of Oxford.
- 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.
- Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," Economics Series Working Papers 458, University of Oxford, Department of Economics.
- Degiannakis, Stavros & Floros, Christos, 2016.
"Intra-day realized volatility for European and USA stock indices,"
Global Finance Journal, Elsevier, vol. 29(C), pages 24-41.
- Degiannakis, Stavros & Floros, Christos, 2014. "Intra-Day Realized Volatility for European and USA Stock Indices," MPRA Paper 64940, University Library of Munich, Germany, revised Jan 2015.
- Christophe Hurlin & Jérémy Leymarie & Antoine Patin, 2018.
"Loss functions for LGD model comparison,"
Working Papers
halshs-01516147, HAL.
- Jérémy Leymarie & Christophe Hurlin & Antoine Patin, 2018. "Loss Functions for LGD Models Comparison," Post-Print hal-01923050, HAL.
- Degiannakis, Stavros & Floros, Christos, 2013.
"Modeling CAC40 volatility using ultra-high frequency data,"
Research in International Business and Finance, Elsevier, vol. 28(C), pages 68-81.
- Degiannakis, Stavros & Floros, Christos, 2013. "Modeling CAC40 Volatility Using Ultra-high Frequency Data," MPRA Paper 80445, University Library of Munich, Germany.
- Jui-Cheng Hung & Tien-Wei Lou & Yi-Hsien Wang & Jun-De Lee, 2013. "Evaluating and improving GARCH-based volatility forecasts with range-based estimators," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 4041-4049, October.
- Tsiaras, Leonidas, 2009.
"The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks,"
Finance Research Group Working Papers
F-2009-02, University of Aarhus, Aarhus School of Business, Department of Business Studies.
- Leonidas Tsiaras, 2010. "The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks," CREATES Research Papers 2010-34, Department of Economics and Business Economics, Aarhus University.
- Bollerslev, Tim & Kretschmer, Uta & Pigorsch, Christian & Tauchen, George, 2009.
"A discrete-time model for daily S & P500 returns and realized variations: Jumps and leverage effects,"
Journal of Econometrics, Elsevier, vol. 150(2), pages 151-166, June.
- Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2007. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," CREATES Research Papers 2007-22, Department of Economics and Business Economics, Aarhus University.
- Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
- Francesco Audrino & Peter Bühlmann, 2009.
"Splines for financial volatility,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 655-670, June.
- Francesco Audrino & Peter Bühlmann, 2007. "Splines for Financial Volatility," University of St. Gallen Department of Economics working paper series 2007 2007-11, Department of Economics, University of St. Gallen.
- Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2017. "Equity index variance: Evidence from flexible parametric jump–diffusion models," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 85-103.
- Nicholas Taylor, 2014. "The Economic Value of Volatility Forecasts: A Conditional Approach," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 433-478.
- Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023.
"The contribution of jump signs and activity to forecasting stock price volatility,"
Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
- , 2019. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 1902, Federal Reserve Bank of Dallas, revised 17 Dec 2022.
- Ruijun Bu & Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, 2021. "The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility," Working Papers 202109, University of Liverpool, Department of Economics.
- David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
- Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
- Christensen, K. & Podolskij, M. & Thamrongrat, N. & Veliyev, B., 2017.
"Inference from high-frequency data: A subsampling approach,"
Journal of Econometrics, Elsevier, vol. 197(2), pages 245-272.
- Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
- Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
- Degiannakis, Stavros & Livada, Alexandra, 2013.
"Realized volatility or price range: Evidence from a discrete simulation of the continuous time diffusion process,"
Economic Modelling, Elsevier, vol. 30(C), pages 212-216.
- Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80449, University Library of Munich, Germany.
- Degiannakis, Stavros & Livada, Alexandra, 2013. "Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process," MPRA Paper 80489, University Library of Munich, Germany.
- Fiszeder, Piotr & Perczak, Grzegorz, 2016. "Low and high prices can improve volatility forecasts during periods of turmoil," International Journal of Forecasting, Elsevier, vol. 32(2), pages 398-410.
- Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
- Dimitris Politis & Dimitrios Thomakos, 2007.
"NoVaS Transformations: Flexible Inference for Volatility Forecasting,"
Working Papers
0005, University of Peloponnese, Department of Economics.
- Politis, Dimitris N & Thomakos, Dimitrios D, 2008. "NoVaS Transformations: Flexible Inference for Volatility Forecasting," University of California at San Diego, Economics Working Paper Series qt982208kx, Department of Economics, UC San Diego.
- Dimitris N. Politis & Dimitrios D. Thomakos, 2007. "NoVaS Transformations: Flexible Inference for Volatility Forecasting," Working Paper series 44_07, Rimini Centre for Economic Analysis.
- Bauwens, Luc & Dzuverovic, Emilija & Hafner, Christian, 2024.
"Asymmetric Models for Realized Covariances,"
LIDAM Discussion Papers CORE
2024024, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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).
- Gabriel Rodríguez, 2015. "Modeling Latin-American Stock Markets Volatility: Varying Probabilities and Mean Reversion in a Random Level Shifts Model," Documentos de Trabajo / Working Papers 2015-403, Departamento de Economía - Pontificia Universidad Católica del Perú.
- 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.
- Rombouts, Jeroen & Stentoft, Lars & Violante, Franceso, 2014.
"The value of multivariate model sophistication: An application to pricing Dow Jones Industrial Average options,"
International Journal of Forecasting, Elsevier, vol. 30(1), pages 78-98.
- Jeroen V.K. Rombouts & Lars Stentoft & Francesco Violante, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average options," CREATES Research Papers 2012-04, Department of Economics and Business Economics, Aarhus University.
- ROMBOUTS, Jeroen V. K. & STENTOFT, Lars & VIOLANTE, Francesco, 2012. "The value of multivariate model sophistication: an application to pricing Dow Jones Industrial Average options," LIDAM Discussion Papers CORE 2012003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Jeroen Rombouts & Lars Stentoft & Francesco Violente, 2012. "The Value of Multivariate Model Sophistication: An Application to pricing Dow Jones Industrial Average Options," CIRANO Working Papers 2012s-05, CIRANO.
- 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.
- M. Pilar Muñoz & M. Dolores Marquez & Lesly M. Acosta, 2007. "Forecasting volatility by means of threshold models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 343-363.
- Isao Ishida & Toshiaki Watanabe, 2009.
"Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model,"
CIRJE F-Series
CIRJE-F-608, CIRJE, Faculty of Economics, University of Tokyo.
- Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," Global COE Hi-Stat Discussion Paper Series gd08-032, Institute of Economic Research, Hitotsubashi University.
- Shao, Xi-Dong & Lian, Yu-Jun & Yin, Lian-Qian, 2009. "Forecasting Value-at-Risk using high frequency data: The realized range model," Global Finance Journal, Elsevier, vol. 20(2), pages 128-136.
- Renò, Roberto, 2008. "Nonparametric Estimation Of The Diffusion Coefficient Of Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 24(5), pages 1174-1206, October.
- Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
- Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015.
"Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes,"
Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
- Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
- 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.
- 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).
- 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.
- BAUWENS, Luc & SUCARRAT, Genaro, 2010. "General-to-specific modelling of exchange rate volatility: a forecast evaluation," LIDAM Reprints CORE 2234, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, Luc & Sucarrat, Genaro, 2008. "General to specific modelling of exchange rate volatility : a forecast evaluation," UC3M Working papers. Economics we081810, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- A. Amendola & V. Candila, 2016. "Evaluation of volatility predictions in a VaR framework," Quantitative Finance, Taylor & Francis Journals, vol. 16(5), pages 695-709, May.
- Xu, Jiawen & Perron, Pierre, 2014.
"Forecasting return volatility: Level shifts with varying jump probability and mean reversion,"
International Journal of Forecasting, Elsevier, vol. 30(3), pages 449-463.
- Jiawen Xu & Pierre Perron, 2013. "Forecasting Return Volatility: Level Shifts with Varying Jump Probability and Mean Reversion," Boston University - Department of Economics - Working Papers Series 2013-021, Boston University - Department of Economics.
- Roxana Chiriac & Valeri Voev, 2011.
"Modelling and forecasting multivariate realized volatility,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 922-947, September.
- Chiriac, Roxana & Voev, Valeri, 2008. "Modelling and forecasting multivariate realized volatility," CoFE Discussion Papers 08/06, University of Konstanz, Center of Finance and Econometrics (CoFE).
- Roxana Chiriac & Valeri Voev, 2008. "Modelling and Forecasting Multivariate Realized Volatility," CREATES Research Papers 2008-39, Department of Economics and Business Economics, Aarhus University.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016.
"Do We Need High Frequency Data to Forecast Variances?,"
Annals of Economics and Statistics, GENES, issue 123-124, pages 135-174.
- Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
- Matteo Luciani & David Veredas, "undated". "A simple model for vast panels of volatilities," ULB Institutional Repository 2013/136239, ULB -- Universite Libre de Bruxelles.
- Audrino, Francesco, 2014.
"Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks,"
Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
- Audrino, Francesco, 2011. "Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks," Economics Working Paper Series 1112, University of St. Gallen, School of Economics and Political Science.
- Becker, R. & Clements, A.E. & Doolan, M.B. & Hurn, A.S., 2015. "Selecting volatility forecasting models for portfolio allocation purposes," International Journal of Forecasting, Elsevier, vol. 31(3), pages 849-861.
- Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.
- Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
- Angelidis, Timotheos & Degiannakis, Stavros, 2007.
"Backtesting VaR Models: A Τwo-Stage Procedure,"
MPRA Paper
80418, University Library of Munich, Germany.
- Angelidis, Timotheos & Degiannakis, Stavros, 2007. "Backtesting VaR Models: A Τwo-Stage Procedure," MPRA Paper 96327, University Library of Munich, Germany.
- Thomas Chuffart, 2015.
"Selection Criteria in Regime Switching Conditional Volatility Models,"
Econometrics, MDPI, vol. 3(2), pages 1-28, May.
- Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," AMSE Working Papers 1339, Aix-Marseille School of Economics, France, revised 14 Jul 2013.
- Thomas Chuffart, 2015. "Selection Criteria in Regime Switching Conditional Volatility Models," Post-Print hal-01457388, HAL.
- Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," Working Papers halshs-00844413, HAL.
- Wang Pu & Yixiang Chen & Feng Ma, 2016. "Forecasting the realized volatility in the Chinese stock market: further evidence," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3116-3130, July.
- Cordis, Adriana S. & Kirby, Chris, 2014. "Discrete stochastic autoregressive volatility," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 160-178.
- Fabian Hollstein & Marcel Prokopczuk & Chardin Wese Simen, 2020. "The Conditional Capital Asset Pricing Model Revisited: Evidence from High-Frequency Betas," Management Science, INFORMS, vol. 66(6), pages 2474-2494, June.
- Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Research Discussion Papers 19/2010, Bank of Finland.
- 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.
- Rodríguez, Gabriel, 2017. "Modeling Latin-American stock and Forex markets volatility: Empirical application of a model with random level shifts and genuine long memory," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 393-420.
- Julien Chevallier & Benoît Sévi, 2011.
"On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting,"
Annals of Finance, Springer, vol. 7(1), pages 1-29, February.
- Chevallier, Julien & Benoit, Sevi, 2009. "On the Realized Volatility of the ECX CO2 Emissions 2008 Futures Contract: Distribution, Dynamics and Forecasting," Sustainable Development Papers 55834, Fondazione Eni Enrico Mattei (FEEM).
- Julien Chevallier & Benoît Sévi, 2009. "On the Realized Volatility of the ECX CO2 Emissions 2008 Futures Contract: Distribution, Dynamics and Forecasting," Working Papers 2009.113, Fondazione Eni Enrico Mattei.
- Julien Chevallier & Benoît Sévi, 2009. "On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting," EconomiX Working Papers 2009-24, University of Paris Nanterre, EconomiX.
- Julien Chevallier & Benoît Sévi, 2009. "On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting," Working Papers halshs-00387286, HAL.
- Heejoon Han & Myung D. Park, 2013. "Comparison of Realized Measure and Implied Volatility in Forecasting Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 522-533, September.
- Gabriel Rodríguez & Roxana Tramontana Tocto, 2015.
"Application of a Short Memory Model With Random Level Shifts to the Volatility of Latin American Stock Market Returns,"
Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 52(2), pages 185-211, November.
- Gabriel Rodriguez & Roxana Tramontana, 2014. "An Application of a Short Memory Model With Random Level Shifts to the Volatility of Latin American Stock Market Returns," Documentos de Trabajo / Working Papers 2014-385, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Rodríguez, Gabriel & Tramontana, Roxana, 2015. "An Application of a Short Memory Model with Random Level Shifts to the Volatility of Latin American Stock Market Returns," Working Papers 2015-004, Banco Central de Reserva del Perú.
- Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017.
"Risk Measure Inference,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
- Christophe Hurlin & Sebastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2015. "Risk Measure Inference," Working Papers halshs-00877279, HAL.
- Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Post-Print hal-01457393, HAL.
- repec:awi:wpaper:0472 is not listed on IDEAS
- Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
- Caporin, Massimiliano & McAleer, Michael, 2014.
"Robust ranking of multivariate GARCH models by problem dimension,"
Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
- Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Working Papers in Economics 12/06, University of Canterbury, Department of Economics and Finance.
- Michael McAleer & Massimiliano Caporin, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," KIER Working Papers 815, Kyoto University, Institute of Economic Research.
- Massimiliano Caporin & Michael McAleer, 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Documentos de Trabajo del ICAE 2012-06, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Apr 2012.
- Caporin, M. & McAleer, M.J., 2012. "Robust Ranking of Multivariate GARCH Models by Problem Dimension," Econometric Institute Research Papers EI2012-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
- Stavros Degiannakis, 2008.
"ARFIMAX and ARFIMAX-TARCH realized volatility modeling,"
Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1169-1180.
- Degiannakis, Stavros, 2008. "ARFIMAX and ARFIMAX-TARCH Realized Volatility Modeling," MPRA Paper 80465, University Library of Munich, Germany.
- Silvia Muzzioli, 2010. "Towards a volatility index for the Italian stock market," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 10091, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
- Sébastien Laurent & Jeroen V. K. Rombouts & Francesco Violante, 2012.
"On the forecasting accuracy of multivariate GARCH models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 934-955, September.
- LAURENT, Sébastien & ROMBOUTS, Jeroen V. K. & VIOLANTE, Francesco, 2010. "On the forecasting accuracy of multivariate GARCH models," LIDAM Discussion Papers CORE 2010025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Sébastien Laurent & Jeroen V.K. Rombouts & Francesco Violante, 2010. "On the Forecasting Accuracy of Multivariate GARCH Models," Cahiers de recherche 1021, CIRPEE.
- Rasmus T. Varneskov & Pierre Perron, 2018.
"Combining long memory and level shifts in modelling and forecasting the volatility of asset returns,"
Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 371-393, March.
- Pierre Perron & Rasmus T. Varneskov, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2011-050, Boston University - Department of Economics.
- Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
- Rasmus T. Varneskov & Pierre Perron, 2015. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series wp2015-015, Boston University - Department of Economics.
- Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
- Laurent, Sébastien & Lecourt, Christelle & Palm, Franz C., 2016.
"Testing for jumps in conditionally Gaussian ARMA–GARCH models, a robust approach,"
Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 383-400.
- Sébastien Laurent & Christelle Lecourt & Franz C. Palm, 2016. "Testing for jumps in conditionally Gaussian ARMA-GARCH models, a robust approach," Post-Print hal-01447861, HAL.
- Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
- Scharth, Marcel & Medeiros, Marcelo C., 2009.
"Asymmetric effects and long memory in the volatility of Dow Jones stocks,"
International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
- Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
- Gabriel Rodríguez, 2016. "Modeling Latin-American Stock and Forex Markets Volatility: Empirical Application of a Model with Random Level Shifts and Genuine Long Memory [Modelando la volatilidad de los mercados bursátiles y cam," Documentos de Trabajo / Working Papers 2016-416, Departamento de Economía - Pontificia Universidad Católica del Perú.
- Ekaterina Smetanina, 2017. "Real-Time GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 561-601.
- Tae-Hwy Lee & Huiyu Huang, 2014. "Forecasting Realized Volatility Using Subsample Averaging," Working Papers 201410, University of California at Riverside, Department of Economics.
- Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Bank of Finland Research Discussion Papers 19/2010, Bank of Finland.
- Alain Hecq & Sébastien Laurent & Franz C. Palm, 2011.
"Common Intraday Periodicity,"
Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 325-353, 2012 20 1.
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