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Volatility clustering in monthly stock returns

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  • Jacobsen, Ben
  • Dannenburg, Dennis

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  • Jacobsen, Ben & Dannenburg, Dennis, 2003. "Volatility clustering in monthly stock returns," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 479-503, September.
    • Handle: RePEc:eee:empfin:v:10:y:2003:i:4:p:479-503
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    1. Drost, Feike C & Nijman, Theo E, 1993. "Temporal Aggregation of GARCH Processes," Econometrica, Econometric Society, vol. 61(4), pages 909-927, July.
    2. Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
    3. Whitney K. Newey & Douglas G. Steigerwald, 1997. "Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models," Econometrica, Econometric Society, vol. 65(3), pages 587-600, May.
    4. Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-1435, November.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. Poon, Ser-Huang & Taylor, Stephen J., 1992. "Stock returns and volatility: An empirical study of the UK stock market," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 37-59, February.
    7. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    8. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    9. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
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    Cited by:

    1. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02312186, HAL.
    2. Beggs, William & DeVault, Luke, 2022. "Mutual fund (sub)advisor connections and crowds," Journal of Empirical Finance, Elsevier, vol. 67(C), pages 231-252.
    3. Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
    4. Nikolaos Sariannidis & Grigoris Giannarakis & Eleni Zafeiriou & Ioannis Billias, 2016. "The Effect of Crude Oil Price Moments on Socially Responsible Firms in Eurozone," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 356-363.
    5. Brännäs, Kurt, 2003. "Temporal Aggregation of the Returns of a Stock Index Series," Umeå Economic Studies 614, Umeå University, Department of Economics.
    6. Fabrice Hervé, 2006. "Les fonds de pension protègent-ils les investisseurs des évolutions du marché?," Working Papers CREGO 1060101, Université de Bourgogne - CREGO EA7317 Centre de recherches en gestion des organisations.
    7. Koulakiotis, Athanasios & Dasilas, Apostolos & Papasyriopoulos, Nicholas, 2009. "Volatility and error transmission spillover effects: Evidence from three European financial regions," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 858-869, August.
    8. Dimitrios Dadakas & Christos Karpetis & Athanasios Fassas & Erotokritos Varelas, 2016. "Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta," IJFS, MDPI, vol. 4(4), pages 1-13, December.
    9. Camilleri, Silvio John, 2006. "An Analysis of Stock Index Distributions of Selected Emerging Markets," MPRA Paper 62490, University Library of Munich, Germany.
    10. Hong Miao & Sanjay Ramchander & Marc W. Simpson, 2011. "Return and Volatility Transmission in U.S. Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 39(4), pages 701-741, December.
    11. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02000726, HAL.
    12. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2022. "The conditional impact of investor sentiment in global stock markets: A two-channel examination," Journal of Banking & Finance, Elsevier, vol. 138(C).
    13. Bartłomiej Lisicki, 2023. "Sektorowe zróżnicowanie efektu interwału akcji spółek z GPW w dobie pandemii COVID-19," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 174-194.
    14. Coqueret, Guillaume, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 180-201.
    15. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.
    16. Jan Jakub Szczygielski & Chimwemwe Chipeta, 2023. "Properties of returns and variance and the implications for time series modelling: Evidence from South Africa," Modern Finance, Modern Finance Institute, vol. 1(1), pages 35-55.
    17. Zhang, Cherry Y. & Jacobsen, Ben, 2021. "The Halloween indicator, “Sell in May and Go Away”: Everywhere and all the time," Journal of International Money and Finance, Elsevier, vol. 110(C).
    18. Lu, Helen & Jacobsen, Ben, 2016. "Cross-asset return predictability: Carry trades, stocks and commodities," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 62-87.
    19. Vanden, Joel M., 2005. "Equilibrium analysis of volatility clustering," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 374-417, June.

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