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Feike C. Drost

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.

Working papers

  1. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2009. "The asymptotic structure of nearly unstable non negative integer-valued AR(1) models," Other publications TiSEM ac0494ae-7a32-43ca-b5b4-d, Tilburg University, School of Economics and Management.

    Cited by:

    1. Becheri, I.G. & Drost, Feike C. & van den Akker, R., 2013. "Asymptotically UMP Panel Unit Root Tests," Discussion Paper 2013-017, Tilburg University, Center for Economic Research.
    2. Marc Hallin & Ramon van den Akker & Bas Werker, 2012. "Rank-Based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Working Papers ECARES ECARES 2012-042, ULB -- Universite Libre de Bruxelles.
    3. Barczy, M. & Ispány, M. & Pap, G., 2011. "Asymptotic behavior of unstable INAR(p) processes," Stochastic Processes and their Applications, Elsevier, vol. 121(3), pages 583-608, March.
    4. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    5. Becheri, I.G. & Drost, Feike C. & van den Akker, R., 2013. "Asymptotically UMP Panel Unit Root Tests," Other publications TiSEM e34b7d23-8e53-4cea-ba69-5, Tilburg University, School of Economics and Management.
    6. Mátyás Barczy & Márton Ispány & Gyula Pap, 2014. "Asymptotic Behavior of Conditional Least Squares Estimators for Unstable Integer-valued Autoregressive Models of Order 2," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 866-892, December.

  2. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2008. "Efficient Estimation of Autoregression Parameters and Innovation Distributions forSemiparametric Integer-Valued AR(p) Models (Revision of DP 2007-23)," Discussion Paper 2008-53, Tilburg University, Center for Economic Research.

    Cited by:

    1. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "Local Asymptotic Normality and Efficient Estimation for inar (P) Models," Other publications TiSEM 95ec06ea-005b-4c08-a2e6-f, Tilburg University, School of Economics and Management.
    2. Jentsch, Carsten & Leucht, Anne, 2014. "Bootstrapping Sample Quantiles of Discrete Data," Working Papers 14-15, University of Mannheim, Department of Economics.
    3. Germán Aneiros, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 439-441, September.
    4. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.

  3. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2007. "Note on Integer-Valued Bilinear Time Series Models," Discussion Paper 2007-47, Tilburg University, Center for Economic Research.

    Cited by:

    1. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "Local Asymptotic Normality and Efficient Estimation for inar (P) Models," Other publications TiSEM 95ec06ea-005b-4c08-a2e6-f, Tilburg University, School of Economics and Management.
    2. Segers, J.J.J. & van den Akker, R. & Werker, B.J.M., 2008. "Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known," Discussion Paper 2008-40, Tilburg University, Center for Economic Research.
    3. Predrag M. Popović & Hassan S. Bakouch, 2020. "A bivariate integer-valued bilinear autoregressive model with random coefficients," Statistical Papers, Springer, vol. 61(5), pages 1819-1840, October.
    4. Segers, J.J.J. & van den Akker, R. & Werker, B.J.M., 2008. "Improving Upon the Marginal Empirical Distribution Functions when the Copula is Known," Other publications TiSEM 950a8cda-8f8c-43a9-a5c2-8, Tilburg University, School of Economics and Management.
    5. Sakineh Ramezani & Mehrnaz Mohammadpour, 2022. "Integer-valued Bilinear Model with Dependent Counting Series," Methodology and Computing in Applied Probability, Springer, vol. 24(1), pages 321-343, March.
    6. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    7. E. Gonçalves & N. Mendes-Lopes & F. Silva, 2015. "Infinitely Divisible Distributions in Integer-Valued Garch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(4), pages 503-527, July.
    8. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2009. "The asymptotic structure of nearly unstable non negative integer-valued AR(1) models," Other publications TiSEM ac0494ae-7a32-43ca-b5b4-d, Tilburg University, School of Economics and Management.
    9. Doukhan, Paul & Fokianos, Konstantinos & Li, Xiaoyin, 2012. "On weak dependence conditions: The case of discrete valued processes," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1941-1948.

  4. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "An Asymptotic Analysis of Nearly Unstable inar (1) Models," Discussion Paper 2006-44, Tilburg University, Center for Economic Research.

    Cited by:

    1. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "Local Asymptotic Normality and Efficient Estimation for inar (P) Models," Other publications TiSEM 95ec06ea-005b-4c08-a2e6-f, Tilburg University, School of Economics and Management.

  5. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "Local Asymptotic Normality and Efficient Estimation for inar (P) Models," Discussion Paper 2006-45, Tilburg University, Center for Economic Research.

    Cited by:

    1. Mohamed Sadoun & Mohamed Bentarzi, 2021. "Locally asymptotically efficient estimation for parametric PINAR(p) models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(3), pages 257-289, August.
    2. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    3. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "An Asymptotic Analysis of Nearly Unstable inar (1) Models," Other publications TiSEM 6e89d2b0-1d07-4f01-9b2f-5, Tilburg University, School of Economics and Management.
    4. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2009. "The asymptotic structure of nearly unstable non negative integer-valued AR(1) models," Other publications TiSEM ac0494ae-7a32-43ca-b5b4-d, Tilburg University, School of Economics and Management.
    5. Mátyás Barczy & Márton Ispány & Gyula Pap, 2014. "Asymptotic Behavior of Conditional Least Squares Estimators for Unstable Integer-valued Autoregressive Models of Order 2," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 866-892, December.
    6. Drost, F.C. & van den Akker, R. & Werker, B.J.M., 2006. "An Asymptotic Analysis of Nearly Unstable inar (1) Models," Discussion Paper 2006-44, Tilburg University, Center for Economic Research.
    7. Ruijun Bu & Brendan McCabe & Kaddour Hadri, 2008. "Maximum likelihood estimation of higher‐order integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 973-994, November.

  6. Boes, M.J. & Drost, F.C. & Werker, B.J.M., 2005. "The Impact of Overnight Periods on Option Pricing," Discussion Paper 2005-1, Tilburg University, Center for Economic Research.

    Cited by:

    1. Entrop, Oliver & Scholz, Hendrik & Wilkens, Marco, 2009. "The price-setting behavior of banks: An analysis of open-end leverage certificates on the German market," Journal of Banking & Finance, Elsevier, vol. 33(5), pages 874-882, May.
    2. Kuttu, Saint & Aboagye, Anthony Q.Q. & Bokpin, Godfred A., 2018. "Evidence of time-varying conditional discrete jump dynamics in sub-Saharan African foreign exchange markets," Research in International Business and Finance, Elsevier, vol. 46(C), pages 211-226.
    3. Piccotti, Louis R., 2018. "Jumps, cojumps, and efficiency in the spot foreign exchange market," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 49-67.
    4. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
    5. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    6. Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
    7. Fang Liang & Lingshan Du & Zhuo Huang, 2023. "Option pricing with overnight and intraday volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1576-1614, November.
    8. Kaplanski, Guy & Levy, Haim, 2015. "Trading breaks and asymmetric information: The option markets," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 390-404.
    9. Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 251-268, February.
    10. Patrizia Perras & Niklas Wagner, 2020. "On the pricing of overnight market risk," Empirical Economics, Springer, vol. 59(3), pages 1307-1327, September.
    11. Ally Quan Zhang & Matthias Thul, 2017. "How much is the gap?—Efficient jump risk-adjusted valuation of leveraged certificates," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1387-1401, September.
    12. Shou-Lei Wang & Yu-Fei Yang & Yu-Hua Zeng, 2014. "The Adjoint Method for the Inverse Problem of Option Pricing," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, March.
    13. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.

  7. Drost, F.C. & Werker, B.J.M., 2001. "Semiparametric Duration Models," Discussion Paper 2001-11, Tilburg University, Center for Economic Research.

    Cited by:

    1. Perera, Indeewara & Silvapulle, Mervyn J., 2021. "Bootstrap based probability forecasting in multiplicative error models," Journal of Econometrics, Elsevier, vol. 221(1), pages 1-24.
    2. Marcelo Fernandes & Marcelo C. Medeiros & Alvaro Veiga, 2016. "A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1221-1250, August.
    3. 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).
    4. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    5. Malec, Peter & Schienle, Melanie, 2012. "Nonparametric Kernel density estimation near the boundary," SFB 649 Discussion Papers 2012-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. 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).
    7. Stanislav Anatolyev & Dmitry Shakin, 2006. "Trade intensity in the Russian stock market:dynamics, distribution and determinants," Working Papers w0070, New Economic School (NES).
    8. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    9. 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.
    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. De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
    12. 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.
    13. Fernandes, Marcelo & Medeiros, Marcelo C. & Veiga, Alvaro, 2013. "A (semi-)parametric functional coefficient autoregressive conditional duration model," Textos para discussão 343, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    14. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    15. 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.
    16. 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.
    17. 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.
    18. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    19. Spierdijk, Laura, 2004. "An empirical analysis of the role of the trading intensity in information dissemination on the NYSE," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 163-184, March.
    20. Fernandes, Marcelo & Barros, Carlos Felipe, 2014. "Market Depth at the BM&FBovespa," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(1), March.
    21. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    22. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    23. Simos G. Meintanis & Bojana Milošević & Marko Obradović, 2020. "Goodness-of-fit tests in conditional duration models," Statistical Papers, Springer, vol. 61(1), pages 123-140, February.
    24. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    25. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.
    26. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    27. Peter Hall, 2007. "Comments on: Nonparametric inference with generalized likelihood ratio tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(3), pages 448-449, December.
    28. 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.
    29. Spierdijk, L. & Nijman, T.E. & van Soest, A.H.O., 2002. "The Price Impact of Trades in Illiquid Stocks in Periods of High and Low Market Activity," Other publications TiSEM d8b70967-e398-4f5d-825b-1, Tilburg University, School of Economics and Management.
    30. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    31. Rodrigues, Bruno Dore & Souza, Reinaldo Castro & Stevenson, Maxwell J., 2012. "An analysis of intraday market behaviour before takeover announcements," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 23-32.
    32. Denisa Georgiana Banulescu & Gilbert Colletaz & Christophe Hurlin & Sessi Tokpavi, 2013. "High-Frequency Risk Measures," Working Papers halshs-00859456, HAL.
    33. Spierdijk, L., 2002. "An Empirical Analysis of the Role of the Trading Intensity in Information Dissemination on the NYSE," Discussion Paper 2002-30, Tilburg University, Center for Economic Research.
    34. 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.
    35. 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.
    36. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
    37. Fernandes, Marcelo, 2004. "Bounds for the probability distribution function of the linear ACD process," Statistics & Probability Letters, Elsevier, vol. 68(2), pages 169-176, June.
    38. Spierdijk, L., 2002. "An Empirical Analysis of the Role of the Trading Intensity in Information Dissemination on the NYSE," Other publications TiSEM d495caf0-2f2a-425f-8e50-e, Tilburg University, School of Economics and Management.

  8. Feike C. Drost & Bas J. M. Werker, 2000. "Efficient Estimation in Semiparametric Time Series: the ACD Model," Econometric Society World Congress 2000 Contributed Papers 0836, Econometric Society.

    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. Taylor, Nicholas, 2004. "Trading intensity, volatility, and arbitrage activity," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1137-1162, May.

  9. Gonzalez-Rivera, G. & Drost, F.C., 1998. "Efficiency comparisons of maximum likelihood-based estimators in garch models," Discussion Paper 1998-124, Tilburg University, Center for Economic Research.

    Cited by:

    1. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    2. Claude Diebolt & Mohamed Chikhi, 2021. "Testing The Weak Form Efficiency Of The French Etf Market With Lstar-Anlstgarch Approach Using A Semiparametric Estimation," Working Papers 09-21, Association Française de Cliométrie (AFC).
    3. Fiorentini, Gabriele & Sentana, Enrique, 2021. "New testing approaches for mean–variance predictability," Journal of Econometrics, Elsevier, vol. 222(1), pages 516-538.
    4. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    5. Klar, B. & Lindner, F. & Meintanis, S.G., 2012. "Specification tests for the error distribution in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3587-3598.
    6. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    7. Daglis, Theodoros & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Papadakis, Theodoulos Eleftherios, 2020. "The forecasting ability of solar and space weather data on NASDAQ’s finance sector price index volatility," Research in International Business and Finance, Elsevier, vol. 52(C).
    8. HAFNER, Christian & ROMBOUTS, Jeroen, 2003. "Semiparametric multivariate GARCH models," LIDAM Discussion Papers CORE 2003003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Carlo Grillenzoni, 2009. "Kernel Likelihood Inference for Time Series," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(1), pages 127-140, March.
    10. Jianqing Fan & Lei Qi & Dacheng Xiu, 2014. "Quasi-Maximum Likelihood Estimation of GARCH Models With Heavy-Tailed Likelihoods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 178-191, April.
    11. Christian Francq & Jean-Michel Zakoïan, 2008. "A Tour in the Asymptotic Theory of GARCH Estimation," Working Papers 2008-03, Center for Research in Economics and Statistics.
    12. Verhoeven, Peter & McAleer, Michael, 2004. "Fat tails and asymmetry in financial volatility models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 351-361.
    13. Abdelouahab Bibi, 2021. "Asymptotic properties of QMLE for seasonal threshold GARCH model with periodic coefficients," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 477-514, June.
    14. Rombouts, Jeroen V. K. & Hafner, Christian M., 2004. "Semiparametric multivariate volatility models," Papers 2004,14, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    15. Eduardo Rossi, 2010. "Univariate GARCH models: a survey (in Russian)," Quantile, Quantile, issue 8, pages 1-67, July.
    16. Bibi, Abdelouahab & Ghezal, Ahmed, 2017. "Asymptotic properties of QMLE for periodic asymmetric strong and semi-strong GARCH models," MPRA Paper 81126, University Library of Munich, Germany.

  10. de Jong, F.C.J.M. & Drost, F.C. & Werker, B.J.M., 1997. "Exchange rate target zones : A new approach," Discussion Paper 97.04, Tilburg University, Center for Economic Research.

    Cited by:

    1. Nour Meddahi & Eric Renault, 1998. "Quadratic M-Estimators for ARCH-Type Processes," CIRANO Working Papers 98s-29, CIRANO.
    2. Marie Bessec, 2000. "Mean-Reversion versus PPP Adjustment: The Two Regimes of Exchange Rate Dynamics Under the EMS, 1979-1998," Econometric Society World Congress 2000 Contributed Papers 1305, Econometric Society.

  11. Drost, F.C. & Klaassen, C.A.J., 1996. "Efficient Estimation in Semiparametric GARCH Models," Discussion Paper 1996-38, Tilburg University, Center for Economic Research.

    Cited by:

    1. Drost, F.C. & Werker, B.J.M., 2001. "Semiparametric Duration Models," Discussion Paper 2001-11, Tilburg University, Center for Economic Research.
    2. Drost, F.C. & Klaassen, C.A.J. & Werker, B.J.M., 1997. "Adaptive estimation in time-series models," Other publications TiSEM aa253902-af93-4e1e-b974-2, Tilburg University, School of Economics and Management.
    3. Gabriele Fiorentini & Enrique Sentana, 2018. "Consistent non-Gaussian pseudo maximum likelihood estimators," Working Paper series 18-06, Rimini Centre for Economic Analysis.
    4. Nour Meddahi & Eric Renault, 1998. "Quadratic M-Estimators for ARCH-Type Processes," CIRANO Working Papers 98s-29, CIRANO.
    5. Drost, F.C. & Werker, B.J.M., 1994. "Closing the GARCH gap : Continuous time GARCH modeling," Discussion Paper 1994-2, Tilburg University, Center for Economic Research.
    6. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    7. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers CWP25/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    9. Claude Diebolt & Mohamed Chikhi, 2021. "Testing The Weak Form Efficiency Of The French Etf Market With Lstar-Anlstgarch Approach Using A Semiparametric Estimation," Working Papers 09-21, Association Française de Cliométrie (AFC).
    10. Enno Mammen & Oliver Linton, 2004. "Estimating Semiparametric ARCH Models by Kernel Smoothing Methods," FMG Discussion Papers dp511, Financial Markets Group.
    11. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    12. Francq, Christian & Zakoian, Jean-Michel, 2023. "Local Asymptotic Normality Of General Conditionally Heteroskedastic And Score-Driven Time-Series Models," Econometric Theory, Cambridge University Press, vol. 39(5), pages 1067-1092, October.
    13. 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.
    14. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, Osaka University.
    15. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
    16. Douglas Hodgson, 2002. "Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form," Cahiers de recherche CREFE / CREFE Working Papers 146, CREFE, Université du Québec à Montréal.
    17. Francesco Audrino, 2005. "Local Likelihood for non‐parametric ARCH(1) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 251-278, March.
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  12. Drost, F.C. & Nijman, T.E. & Werker, B.J.M., 1994. "Estimation and testing in models containing both jumps and conditional heteroskedasticity," Discussion Paper 1994-105, Tilburg University, Center for Economic Research.

    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," Center for Financial Institutions Working Papers 99-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. Xieer Dai & Michael Beenstock & Daniel Felsenstein & David Genesove & Nikita Kotsenko, 2023. "'Traffic light' theory for Covid-19 spatial mitigation policy design," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-35, December.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    4. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien McMahon, 2006. "Forecasting Commodity Prices: GARCH, Jumps, and Mean Reversion," Staff Working Papers 06-14, Bank of Canada.
    5. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    6. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2008. "Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility," Journal of Econometrics, Elsevier, vol. 143(2), pages 227-262, April.
    7. Drost, F.C. & Werker, B.J.M., 1994. "Closing the GARCH gap : Continuous time GARCH modeling," Discussion Paper 1994-2, Tilburg University, Center for Economic Research.
    8. Chan Wing Hong, 2008. "Dynamic Hedging with Foreign Currency Futures in the Presence of Jumps," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-25, May.
    9. Naifar, Nader, 2012. "Modeling the dependence structure between default risk premium, equity return volatility and the jump risk: Evidence from a financial crisis," Economic Modelling, Elsevier, vol. 29(2), pages 119-131.
    10. Bernard, Jean-Thomas & Khalaf, Lynda & Kichian, Maral & McMahon, Sébastien, 2008. "Oil Prices: Heavy Tails, Mean Reversion and the Convenience Yield," Cahiers de recherche 0801, GREEN.
    11. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-Francois, 2003. "Simulation-based exact jump tests in models with conditional heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 28(3), pages 531-553, December.
    12. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    13. Benjamin Y. Zhang & Hao Zhou & Haibin Zhu, 2005. "Explaining credit default swap spreads with the equity volatility and jump risks of individual firms," Finance and Economics Discussion Series 2005-63, Board of Governors of the Federal Reserve System (U.S.).
    14. Andersen, Torben G. & Bollerslev, Tim & Francis X. Diebold,, 2003. "Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility," CFS Working Paper Series 2003/35, Center for Financial Studies (CFS).
    15. Jean-Thomas Bernard, Lynda Khalaf, Maral Kichian, and Sebastien McMahon, 2015. "The Convenience Yield and the Informational Content of the Oil Futures Price," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    16. Chen, Yi-Hsuan & Tu, Anthony H. & Wang, Kehluh, 2008. "Dependence structure between the credit default swap return and the kurtosis of the equity return distribution: Evidence from Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(3), pages 259-271, July.
    17. Khalaf, Lynda & Saphores, Jean-Daniel & Bilodeau, Jean-François, 2000. "Simulation-Based Exact Tests with Unidentified Nuisance Parameters Under the Null Hypothesis: the Case of Jumps Tests in Models with Conditional Heteroskedasticity," Cahiers de recherche 0004, GREEN.
    18. Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
    19. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    20. Lange, Stephen, 1999. "Modeling asset market volatility in a small market:: Accounting for non-synchronous trading effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(1), pages 1-18, January.
    21. Lin, Bing-Huei & Yeh, Shih-Kuo, 2000. "On the distribution and conditional heteroscedasticity in Taiwan stock prices," Journal of Multinational Financial Management, Elsevier, vol. 10(3-4), pages 367-395, December.
    22. Nour Meddahi, 2002. "ARMA Representation of Two-Factor Models," CIRANO Working Papers 2002s-92, CIRANO.
    23. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.
    24. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    25. Andersen, Torben G. & Bollerslev, Tim & Dobrev, Dobrislav, 2007. "No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications," Journal of Econometrics, Elsevier, vol. 138(1), pages 125-180, May.
    26. Kim, Jae Ho & Powell, Warren B., 2011. "An hour-ahead prediction model for heavy-tailed spot prices," Energy Economics, Elsevier, vol. 33(6), pages 1252-1266.
    27. 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.

  13. Drost, F.C. & Werker, B.J.M., 1994. "Closing the GARCH gap : Continuous time GARCH modeling," Discussion Paper 1994-2, Tilburg University, Center for Economic Research.

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    1. Dankenbring, Henning, 1998. "Volatility estimates of the short term interest rate with an application to German data," SFB 373 Discussion Papers 1998,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
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    3. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    4. Mattiussi, V. & Iori, G., 2006. "Currency futures volatility during the 1997 East Asian crisis: an application of Fourier analysis," Working Papers 06/09, Department of Economics, City University London.
    5. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    6. 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.
    7. Meddahi, N., 2001. "A Theoretical Comparison Between Integrated and Realized Volatilies," Cahiers de recherche 2001-26, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    8. Samet Günay, 2016. "Performance of the Multifractal Model of Asset Returns (MMAR): Evidence from Emerging Stock Markets," IJFS, MDPI, vol. 4(2), pages 1-17, May.
    9. Manabu Asai & Michael McAleer, 2013. "Leverage and Feedback Effects on Multifactor Wishart Stochastic Volatility for Option Pricing," Tinbergen Institute Discussion Papers 13-003/III, Tinbergen Institute.
    10. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    11. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    12. Andrea, SILVESTRINI, 2005. "Temporal aggregaton of univariate linear time series models," Discussion Papers (ECON - Département des Sciences Economiques) 2005044, Université catholique de Louvain, Département des Sciences Economiques.
    13. 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.
    14. F. Fornari & A. Mele, 2000. "Recovering the Probability Density Function of Asset Prices using Garch as Diffusion Approximations," THEMA Working Papers 2000-12, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    15. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Elena Andreou & Eric Ghysels, 2000. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation and Empirical Results," CIRANO Working Papers 2000s-19, CIRANO.
    17. 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.
    18. Zhang, Hanyu & Assereto, Martina & Byrne, Julie, 2023. "Deferring real options with solar renewable energy certificates," Global Finance Journal, Elsevier, vol. 55(C).
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    20. Christian M. Hafner & Sébastien Laurent & Francesco Violante, 2017. "Weak Diffusion Limits of Dynamic Conditional Correlation Models," Post-Print hal-01590010, HAL.
    21. David Mcmillan & Alan Speight, 2008. "Long-memory in high-frequency exchange rate volatility under temporal aggregation," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 251-261.
    22. Eric Ghysels & Joann Jasiak, 1997. "GARCH for Irregularly Spaced Data: The ACD-GARCH Model," CIRANO Working Papers 97s-06, CIRANO.
    23. Amir Safari & Detlef Seese, 2010. "Behavior of realized volatility and correlation in exchange markets," International Econometric Review (IER), Econometric Research Association, vol. 2(2), pages 73-96, September.
    24. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
    25. Denisa Banulescu-Radu & Christophe Hurlin & Bertrand Candelon & Sébastien Laurent, 2016. "Do We Need High Frequency Data to Forecast Variances?," Post-Print hal-01448237, HAL.
    26. Corradi, Valentina, 2000. "Reconsidering the continuous time limit of the GARCH(1, 1) process," Journal of Econometrics, Elsevier, vol. 96(1), pages 145-153, May.
    27. Monica Gentile & Roberto Renò, 2005. "Specification Analysis of Diffusion Models for the Italian Short Rate," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(1), pages 51-83, February.
    28. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    29. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    30. Laurent Calvet & Adlai Fisher & Benoit Mandelbrot, 1999. "A Multifractal Model of Assets Returns," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-072, New York University, Leonard N. Stern School of Business-.
    31. Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, July.
    32. 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.
    33. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    34. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    35. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    36. Nour Meddahi, 2003. "ARMA representation of integrated and realized variances," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 335-356, December.
    37. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    38. Fernandes, Marcelo & Preumont, Pierre-Yves, 2012. "The Finite-Sample Size of the BDS Test for GARCH Standardized Residuals," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 32(2), April.
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    40. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    41. Robin de Vilder & Marcel P. Visser, 2007. "Proxies for daily volatility," PSE Working Papers halshs-00588307, HAL.
    42. Subbotin, Alexandre, 2009. "Volatility Models: from Conditional Heteroscedasticity to Cascades at Multiple Horizons," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 15(3), pages 94-138.
    43. Bollerslev, T. & Ghysels, E., 1994. "Periodic Autoregressive Conditional Heteroskedasticity," Cahiers de recherche 9408, Universite de Montreal, Departement de sciences economiques.
    44. 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.
    45. Drost, Feike C. & Klaassen, Chris A. J., 1997. "Efficient estimation in semiparametric GARCH models," Journal of Econometrics, Elsevier, vol. 81(1), pages 193-221, November.
    46. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    47. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    48. Jensen Anders Tolver & Lange Theis, 2010. "On Convergence of the QMLE for Misspecified GARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-31, June.
    49. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
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    1. Bo Zhou, 2023. "Semiparametrically Optimal Cointegration Test," Papers 2305.08880, arXiv.org.
    2. Drost, F.C. & Werker, B.J.M., 2001. "Semiparametric Duration Models," Discussion Paper 2001-11, Tilburg University, Center for Economic Research.
    3. Marc Hallin & Ramon van den Akker & Bas Werker, 2012. "Rank-Based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Working Papers ECARES ECARES 2012-042, ULB -- Universite Libre de Bruxelles.
    4. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    5. Dabo-Niang, Sophie & Francq, Christian & Zakoian, Jean-Michel, 2009. "Combining parametric and nonparametric approaches for more efficient time series prediction," MPRA Paper 16893, University Library of Munich, Germany.
    6. André Klein & Guy Melard, 2004. "An algorithm for computing the asymptotic Fisher information matrix for seasonal SISO models," ULB Institutional Repository 2013/13746, ULB -- Universite Libre de Bruxelles.
    7. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers CWP25/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    9. Michael Jansson, 2008. "Semiparametric Power Envelopes for Tests of the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 76(5), pages 1103-1142, September.
    10. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    11. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    12. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    13. Francq, Christian & Zakoian, Jean-Michel, 2023. "Local Asymptotic Normality Of General Conditionally Heteroskedastic And Score-Driven Time-Series Models," Econometric Theory, Cambridge University Press, vol. 39(5), pages 1067-1092, October.
    14. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    15. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.
    16. Marc Hallin & Catherine Vermandele & Bas J. M. Werker, 2008. "Semiparametrically efficient inference based on signs and ranks for median‐restricted models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(2), pages 389-412, April.
    17. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, Osaka University.
    18. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
    19. Hafner, Christian & Reznikova, Olga, 2010. "Efficient estimation of a semiparametric dynamic copula model," LIDAM Reprints ISBA 2010033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Anton Schick & Wolfgang Wefelmeyer, 2002. "Estimating the Innovation Distribution in Nonlinear Autoregressive Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(2), pages 245-260, June.
    21. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers 25/12, Institute for Fiscal Studies.
    22. Douglas Hodgson, 2002. "Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form," Cahiers de recherche CREFE / CREFE Working Papers 146, CREFE, Université du Québec à Montréal.
    23. Marc Hallin & Abdeslam Serroukh, 1998. "Adaptive Estimation of the Lag of a Long–memory Process," Statistical Inference for Stochastic Processes, Springer, vol. 1(2), pages 111-129, May.
    24. HAFNER, Christian & ROMBOUTS, Jeroen, 2003. "Semiparametric multivariate GARCH models," LIDAM Discussion Papers CORE 2003003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    26. Gonzalez-Rivera, G. & Drost, F.C., 1998. "Efficiency comparisons of maximum likelihood-based estimators in garch models," Discussion Paper 1998-124, Tilburg University, Center for Economic Research.
    27. Christian Francq & Jean-Michel Zakoian, 2013. "Inference in Non Stationary Asymmetric Garch Models," Working Papers 2013-11, Center for Research in Economics and Statistics.
    28. Francq, Christian & Zakoian, Jean-Michel, 2024. "Finite moments testing in a general class of nonlinear time series models," MPRA Paper 121193, University Library of Munich, Germany.
    29. Christian Francq & Jean-Michel Zakoïan, 2006. "Inference in GARCH when some coefficients are equal to zero," Computing in Economics and Finance 2006 64, Society for Computational Economics.
    30. Drost, Feike C. & Klaassen, Chris A. J., 1997. "Efficient estimation in semiparametric GARCH models," Journal of Econometrics, Elsevier, vol. 81(1), pages 193-221, November.
    31. Shiqing Ling & Ke Zhu, 2022. "Self-Weighted LSE and Residual-Based QMLE of ARMA-GARCH Models," JRFM, MDPI, vol. 15(2), pages 1-17, February.
    32. Marc Hallin & Ramon van den Akker & Bas J.M. Werker, 2011. "A class of simple distribution-free rank-based unit root tests," Post-Print hal-00834424, HAL.
    33. Hallin, M. & Werker, B.J.M., 2003. "Semiparametric efficiency, distribution-freeness and invariance," Other publications TiSEM fe20db00-786a-4261-9999-6, Tilburg University, School of Economics and Management.
    34. Francq, Christian & Zakoïan, Jean-Michel, 2022. "Testing the existence of moments for GARCH processes," Journal of Econometrics, Elsevier, vol. 227(1), pages 47-64.
    35. Peter M Robinson, 2004. "Efficiency Improvements in Inference on Stationary and Nonstationary Fractional Time Series," STICERD - Econometrics Paper Series 480, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    36. Robinson, Peter & Taylor, Luke, 2017. "Adaptive estimation in multiple time series with independent component errors," LSE Research Online Documents on Economics 68345, London School of Economics and Political Science, LSE Library.
    37. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    38. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    39. Francq, Christian & Zakoïan, Jean-Michel, 2009. "Testing the Nullity of GARCH Coefficients: Correction of the Standard Tests and Relative Efficiency Comparisons," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 313-324.
    40. Marc Hallin & Ramon van den Akker & Bas Werker, 2009. "A class of Simple Semiparametrically Efficient Rank-Based Unit Root Tests," Working Papers ECARES 2009_001, ULB -- Universite Libre de Bruxelles.
    41. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    42. Francq, Christian & Zakoian, Jean-Michel, 2010. "Strict stationarity testing and estimation of explosive ARCH models," MPRA Paper 22414, University Library of Munich, Germany.
    43. I. Gaia Becheri & Feike C. Drost & Bas J.M. Werker, 2016. "Asymptotic Inference for Jump Diffusions with State-Dependent Intensity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 520-542, June.
    44. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 93fe16c1-9f21-4dab-9b73-4, Tilburg University, School of Economics and Management.
    45. André Klein & Guy Mélard, 2004. "An algorithm for computing the asymptotic fisher information matrix for seasonal SISO models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 627-648, September.
    46. Wang, Weining & Wooldridge, Jeffrey M. & Xu, Mengshan, 2020. "Improved Estimation of Dynamic Models of Conditional Means and Variances," IRTG 1792 Discussion Papers 2020-021, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    47. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    48. Marc Hallin & Davide La Vecchia, 2014. "Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models," Working Papers ECARES ECARES 2014-45, ULB -- Universite Libre de Bruxelles.
    49. Rombouts, Jeroen V. K. & Hafner, Christian M., 2004. "Semiparametric multivariate volatility models," Papers 2004,14, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    50. Hallin, M. & van den Akker, R. & Werker, B.J.M., 2011. "A Class of Simple Distribution-free Rank-based Unit Root Tests (Revision of DP 2010-72)," Discussion Paper 2011-002, Tilburg University, Center for Economic Research.
    51. Zhou, Bo, 2024. "Semiparametrically optimal cointegration test," Journal of Econometrics, Elsevier, vol. 242(2).
    52. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    53. Ciccarelli Nicola, 2018. "Semiparametric efficient adaptive estimation of the GJR-GARCH model," Statistics & Risk Modeling, De Gruyter, vol. 35(3-4), pages 141-160, July.
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    60. Drost, F.C. & Klaassen, C.A.J., 1996. "Efficient Estimation in Semiparametric GARCH Models," Other publications TiSEM 3da5ac9e-1f93-41b2-aaa0-5, Tilburg University, School of Economics and Management.
    61. Ciccarelli, Nicola, 2016. "Semiparametric Efficient Adaptive Estimation of the PTTGARCH model," MPRA Paper 72021, University Library of Munich, Germany.
    62. Robinson, Peter, 2004. "Efficiency improvements in inference on stationary and nonstationary fractional time series," LSE Research Online Documents on Economics 2126, London School of Economics and Political Science, LSE Library.
    63. Andreou, E. & Werker, B.J.M., 2003. "A Simple Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2003-118, Tilburg University, Center for Economic Research.
    64. Sun, Yiguo & Stengos, Thanasis, 2006. "Semiparametric efficient adaptive estimation of asymmetric GARCH models," Journal of Econometrics, Elsevier, vol. 133(1), pages 373-386, July.
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  15. Drost, F.C. & Werker, B.J.M., 1993. "A Note on Robinson's Test of Independence," Papers 9315, Tilburg - Center for Economic Research.

    Cited by:

    1. Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Pinkse, Joris, 1998. "A consistent nonparametric test for serial independence," Journal of Econometrics, Elsevier, vol. 84(2), pages 205-231, June.

  16. Drost, F.C. & Nijman, T.E., 1990. "Temporal Aggregation Of Garch Processes," Papers 9066, Tilburg - Center for Economic Research.

    Cited by:

    1. Guorui Bian & Michael McAleer & Wing-Keung Wong, 2013. "Robust Estimation and Forecasting of the Capital Asset Pricing Model," Tinbergen Institute Discussion Papers 13-036/III, Tinbergen Institute.
    2. Ågren, Martin, 2005. "Myopic Loss Aversion, the Equity Premium Puzzle, and GARCH," Working Paper Series 2005:11, Uppsala University, Department of Economics.
    3. Ravi Bansal & Dana Kiku & Amir Yaron, 2012. "Risks For the Long Run: Estimation with Time Aggregation," NBER Working Papers 18305, National Bureau of Economic Research, Inc.
    4. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques.
    5. Gourieroux, Christian & Le Fol, Gaëlle, 1997. "Modes de négociation et caractéristiques de marché," CEPREMAP Working Papers (Couverture Orange) 9714, CEPREMAP.
    6. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    7. Nijman, T. & Sentana, E., 1993. "Marginalization and Contemporaneous Aggregation in Multivariate Garch Processes," Papers 9312, Tilburg - Center for Economic Research.
    8. 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.
    9. Meddahi, N., 2001. "A Theoretical Comparison Between Integrated and Realized Volatilies," Cahiers de recherche 2001-26, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    10. Xinli Yu & Zheng Chen & Yuan Ling & Shujing Dong & Zongyi Liu & Yanbin Lu, 2023. "Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting," Papers 2306.11025, arXiv.org.
    11. M, El Babsiri & Jean-Michel Zakoïan, 1997. "Contemporaneous Asymmetry in GARCH Processes," Working Papers 97-03, Center for Research in Economics and Statistics.
    12. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, December.
    13. Angela Black & David McMillan, 2004. "Long run trends and volatility spillovers in daily exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 14(12), pages 895-907.
    14. Kim, Jihyun & Meddahi, Nour, 2020. "Volatility regressions with fat tails," Journal of Econometrics, Elsevier, vol. 218(2), pages 690-713.
    15. Phornchanok Cumperayot, 2003. "Dusting off the Perception of Risk and Returns in FOREX Markets," CESifo Working Paper Series 904, CESifo.
    16. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    17. Cook, Steven, 2006. "The impact of GARCH on asymmetric unit root tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 745-752.
    18. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    19. Mark D. Flood & John C. Liechty & Thomas Piontek, 2015. "Systemwide Commonalities in Market Liquidity," Working Papers 15-11, Office of Financial Research, US Department of the Treasury.
    20. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    21. Steven Cook, 2006. "The robustness of modified unit root tests in the presence of GARCH," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 359-363.
    22. Torben G. Anderson & Tim Bollerslev & Ashish Das, 1998. "Testing for Market Microstructure Effects in Intraday Volatility: A Reassessment of the Tokyo FX Experiment," NBER Working Papers 6666, National Bureau of Economic Research, Inc.
    23. Macaro, Christian, 2010. "Bayesian non-parametric signal extraction for Gaussian time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 381-395, August.
    24. Sucarrat, Genaro, 2020. "garchx: Flexible and Robust GARCH-X Modelling," MPRA Paper 100301, University Library of Munich, Germany.
    25. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
    26. John Cotter, 2004. "Minimum capital requirement calculations for UK futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(2), pages 193-220, February.
    27. Sucarrat, Genaro, 2020. "Identification of Volatility Proxies as Expectations of Squared Financial Return," MPRA Paper 101953, University Library of Munich, Germany.
    28. Long H. Vo, 2017. "Estimating Financial Volatility with High-Frequency Returns," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 2(2), pages 84-114, October.
    29. Phoebe Koundouri & Nikolaos Kourogenis & Nikitas Pittis & Panagiotis Samartzis, 2015. "Factor Models as 'Explanatory Unifiers' versus 'Explanatory Ideals' of Empirical Regularities of Stock Returns," DEOS Working Papers 1507, Athens University of Economics and Business.
    30. David McMillan & Alan Speight, 2005. "Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(3), pages 199-226, September.
    31. Odening, Martin & Hinrichs, Jan, 2003. "Die Quantifizierung von Marktrisiken in der Tierproduktion mittels Value-at-Risk und Extreme-Value-Theory," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(02), pages 1-11.
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Articles

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  2. I. Gaia Becheri & Feike C. Drost & Bas J.M. Werker, 2016. "Asymptotic Inference for Jump Diffusions with State-Dependent Intensity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 520-542, June.

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    1. Jakobsen, Nina Munkholt & Sørensen, Michael, 2019. "Estimating functions for jump–diffusions," Stochastic Processes and their Applications, Elsevier, vol. 129(9), pages 3282-3318.

  3. Gaia Becheri, I. & Drost, Feike C. & Akker, Ramon van den, 2015. "Asymptotically Ump Panel Unit Root Tests—The Effect Of Heterogeneity In The Alternatives," Econometric Theory, Cambridge University Press, vol. 31(3), pages 539-559, June.

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    1. Samuel Brien & Michael Jansson & Morten Ørregaard Nielsen, 2022. "Nearly Efficient Likelihood Ratio Tests of a Unit Root in an Autoregressive Model of Arbitrary Order," Working Paper 1429, Economics Department, Queen's University.
    2. Norkutė, Milda & Westerlund, Joakim, 2021. "The factor analytical approach in near unit root interactive effects panels," Journal of Econometrics, Elsevier, vol. 221(2), pages 569-590.
    3. Skrobotov, Anton (Скроботов, Антон) & Turuntseva, Marina (Турунцева, Марина), 2017. "Testing the Hypothesis of a Unit Root for Independent Panels [Тестирование Гипотезы О Наличии Единичного Корня Для Независимых Панелей]," Working Papers 021707, Russian Presidential Academy of National Economy and Public Administration.
    4. Westerlund, Joakim & Larsson, Rolf, 2015. "New tools for understanding the local asymptotic power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 188(1), pages 59-93.
    5. Becheri, I. Gaia & Drost, Feike C. & van den Akker, Ramon & Wichert, Oliver, 2016. "The power envelope of panel unit root tests in case stationary alternatives offset explosive ones," Statistics & Probability Letters, Elsevier, vol. 108(C), pages 1-8.

  4. Feike C. Drost & Ramon van den Akker & Bas J. M. Werker, 2009. "Efficient estimation of auto‐regression parameters and innovation distributions for semiparametric integer‐valued AR(p) models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 467-485, April.

    Cited by:

    1. Mohamed Sadoun & Mohamed Bentarzi, 2021. "Locally asymptotically efficient estimation for parametric PINAR(p) models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(3), pages 257-289, August.
    2. Weiß, Christian H. & Zhu, Fukang, 2024. "Conditional-mean multiplicative operator models for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    3. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    4. Raju Maiti & Atanu Biswas & Samarjit Das, 2016. "Coherent forecasting for count time series using Box–Jenkins's AR(p) model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 123-145, May.
    5. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    6. Jentsch, Carsten & Leucht, Anne, 2014. "Bootstrapping Sample Quantiles of Discrete Data," Working Papers 14-15, University of Mannheim, Department of Economics.
    7. Yao Rao & David Harris & Brendan McCabe, 2022. "A semi‐parametric integer‐valued autoregressive model with covariates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 495-516, June.
    8. Tianqing Liu & Xiaohui Yuan, 2013. "Random rounded integer-valued autoregressive conditional heteroskedastic process," Statistical Papers, Springer, vol. 54(3), pages 645-683, August.
    9. Frazier, David T. & Maneesoonthorn, Worapree & Martin, Gael M. & McCabe, Brendan P.M., 2019. "Approximate Bayesian forecasting," International Journal of Forecasting, Elsevier, vol. 35(2), pages 521-539.
    10. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    11. Bisaglia, Luisa & Canale, Antonio, 2016. "Bayesian nonparametric forecasting for INAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 70-78.
    12. Germán Aneiros, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 439-441, September.
    13. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    14. Ali Ahmad & Christian Francq, 2015. "Poisson QMLE of Count Time Series Models," Post-Print hal-01533548, HAL.
    15. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2022. "Bias-correction of some estimators in the INAR(1) process," Statistics & Probability Letters, Elsevier, vol. 187(C).
    16. Vance L. Martin & Andrew R. Tremayne & Robert C. Jung, 2014. "Efficient Method Of Moments Estimators For Integer Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 491-516, November.
    17. Jentsch, Carsten & Weiß, Christian, 2017. "Bootstrapping INAR models," Working Papers 17-02, University of Mannheim, Department of Economics.
    18. Robert C. Jung & Andrew R. Tremayne, 2020. "Maximum-Likelihood Estimation in a Special Integer Autoregressive Model," Econometrics, MDPI, vol. 8(2), pages 1-15, June.
    19. Luisa Bisaglia & Margherita Gerolimetto, 2019. "Model-based INAR bootstrap for forecasting INAR(p) models," Computational Statistics, Springer, vol. 34(4), pages 1815-1848, December.

  5. Drost, Feike C. & van den Akker, Ramon & Werker, Bas J.M., 2008. "Note on integer-valued bilinear time series models," Statistics & Probability Letters, Elsevier, vol. 78(8), pages 992-996, June.
    See citations under working paper version above.
  6. Feike C. Drost & Ramon Van Den Akker & Bas J. M. Werker, 2008. "Local asymptotic normality and efficient estimation for INAR(p) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 783-801, September.
    See citations under working paper version above.
  7. Boes, Mark-Jan & Drost, Feike C. & Werker, Bas J. M., 2007. "The Impact of Overnight Periods on Option Pricing," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(2), pages 517-533, June.
    See citations under working paper version above.
  8. Drost, Feike C & Werker, Bas J M, 2004. "Semiparametric Duration Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 40-50, January.
    See citations under working paper version above.
  9. Gonzalez-Rivera, Gloria & Drost, Feike C., 1999. "Efficiency comparisons of maximum-likelihood-based estimators in GARCH models," Journal of Econometrics, Elsevier, vol. 93(1), pages 93-111, November.
    See citations under working paper version above.
  10. Drost, Feike C & Nijman, Theo E & Werker, Bas J M, 1998. "Estimation and Testing in Models Containing Both Jump and Conditional Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 237-243, April.
    See citations under working paper version above.
  11. Drost, Feike C. & Klaassen, Chris A. J., 1997. "Efficient estimation in semiparametric GARCH models," Journal of Econometrics, Elsevier, vol. 81(1), pages 193-221, November.
    See citations under working paper version above.
  12. Drost, Feike C. & Werker, Bas J. M., 1996. "Closing the GARCH gap: Continuous time GARCH modeling," Journal of Econometrics, Elsevier, vol. 74(1), pages 31-57, September.
    See citations under working paper version above.
  13. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    See citations under working paper version above.
  14. Drost F. C. & Kallenberg W. C. M. & Oosterhoff J., 1990. "The Power Of Edf Tests Of Fit Under Non-Robust Estimation Of Nuisance Parameters," Statistics & Risk Modeling, De Gruyter, vol. 8(2), pages 167-182, February.

    Cited by:

    1. Simos Meintanis & Bojana Milošević & Marko Obradović, 2023. "Bahadur efficiency for certain goodness-of-fit tests based on the empirical characteristic function," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 723-751, October.

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