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Periodic Stochastic Volatility and Fat Tails

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  • Ilias Tsiakas

Abstract

This article provides a comprehensive analysis of the size and statistical significance of the day of the week, month of the year, and holiday effects in daily stock index returns and volatility. We employ data from the Dow Jones Industrial Average (DJIA), the S&P 500, the S&P MidCap 400, and the S&P SmallCap 600 in order to test whether the seasonal patterns of medium and small firms are similar to those of large firms. Using formal hypothesis tests based on bootstrapping, we demonstrate that there are more significant calendar effects in volatility than in expected returns, especially for the two large cap indices. More importantly, we introduce the periodic stochastic volatility (PSV) model for characterizing the observed seasonal patterns of daily financial market volatility. We analyze the interaction between seasonal heteroskedasticity and fat tails by comparing the performance of Gaussian PSV and fat-tailed PSVt specifications to the plain vanilla SV and SVt benchmarks. Consistent with our model-free results, we find strong evidence of seasonal periodicity in volatility, which essentially eliminates the need for a fat-tailed conditional distribution, and is robust to the exclusion of the crash of 1987 outliers. Copyright 2006, Oxford University Press.

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Bibliographic Info

Article provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.

Volume (Year): 4 (2006)
Issue (Month): 1 ()
Pages: 90-135

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Handle: RePEc:oup:jfinec:v:4:y:2006:i:1:p:90-135

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Cited by:
  1. Imtiaz Mazumder, M. & Chu, Ting-Heng & Miller, Edward M. & Prather, Larry J., 2008. "International day-of-the-week effects: An empirical examination of iShares," International Review of Financial Analysis, Elsevier, Elsevier, vol. 17(4), pages 699-715, September.
  2. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series, University of Pavia, Department of Economics and Management 015, University of Pavia, Department of Economics and Management.
  3. Amélie Charles, 2010. "The day-of-the week effects on the volatility: The role of the asymmetry," Post-Print, HAL hal-00771136, HAL.
  4. Ilias Tsiakas, 2004. "Analysis of the predictive ability of information accumulated over nights, weekends and holidays," Econometric Society 2004 Australasian Meetings, Econometric Society 208, Econometric Society.
  5. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2014. "Information ratio analysis of momentum strategies," Papers, arXiv.org 1402.3030, arXiv.org, revised Jul 2014.
  6. Tsiakas, Ilias, 2008. "Overnight information and stochastic volatility: A study of European and US stock exchanges," Journal of Banking & Finance, Elsevier, Elsevier, vol. 32(2), pages 251-268, February.
  7. Hüseyin Kaya & Sadullah Çelik, 2009. "Empirical Evidence For Day Of The Week Effect In An Emerging Market: The Turkish Case," 2009 Meeting Papers, Society for Economic Dynamics 219, Society for Economic Dynamics.
  8. Bidarkota, Prasad V. & Dupoyet, Brice V. & McCulloch, J. Huston, 2009. "Asset pricing with incomplete information and fat tails," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 33(6), pages 1314-1331, June.
  9. David Yermack, 2012. "Tailspotting: Identifying and profiting from CEO vacation trips," NBER Working Papers 17940, National Bureau of Economic Research, Inc.

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