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Overnight information and stochastic volatility: A study of European and US stock exchanges

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  • Tsiakas, Ilias

Abstract

This paper provides a comprehensive evaluation of the predictive ability of information accumulated during nontrading hours for a set of European and US stock indexes. We introduce a stochastic volatility model, which conditions on lagged overnight information, distinguishes between the nontrading periods of weeknights, weekends, holidays and long weekends, and allows for an asymmetric leverage effect on the impact of overnight news. We implement Bayesian methods for estimation and ranking of the empirical models, and find two key results: (i) there is substantial predictive ability in financial information accumulated during nontrading hours; and (ii) the performance of stochastic volatility models improves considerably by separating the asymmetric impact of positive and negative news made available over weeknights, weekends, holidays and long weekends.

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  • 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.
  • Handle: RePEc:eee:jbfina:v:32:y:2008:i:2:p:251-268
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    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. 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(02), pages 517-533, June.
    3. Masulis, Ronald W. & Shivakumar, Lakshmanan, 2002. "Does Market Structure Affect the Immediacy of Stock Price Responses to News?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(04), pages 617-648, December.
    4. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    5. Jeff Fleming & Chris Kirby, 2003. "A Closer Look at the Relation between GARCH and Stochastic Autoregressive Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(3), pages 365-419.
    6. Ilias Tsiakas, 2006. "Periodic Stochastic Volatility and Fat Tails," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 90-135.
    7. Marquering, Wessel & Verbeek, Marno, 2004. "The Economic Value of Predicting Stock Index Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 407-429, June.
    8. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    9. Jason T. Greene & Susan G. Watts, 1996. "Price Discovery on the NYSE and the NASDAQ: The case of Overnight Daytime News Releases," Financial Management, Financial Management Association, vol. 25(1), Spring.
    10. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. " An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    11. Sofianos, George & Werner, Ingrid M., 2000. "The trades of NYSE floor brokers," Journal of Financial Markets, Elsevier, vol. 3(2), pages 139-176, May.
    12. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 249-286, November.
    13. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
    14. Josef Lakonishok, Seymour Smidt, 1988. "Are Seasonal Anomalies Real? A Ninety-Year Perspective," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 403-425.
    15. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    16. Kehr, Carl-Heinrich & Krahnen, Jan P. & Theissen, Erik, 2001. "The Anatomy of a Call Market," Journal of Financial Intermediation, Elsevier, vol. 10(3-4), pages 249-270, July.
    17. West, Kenneth D. & Edison, Hali J. & Cho, Dongchul, 1993. "A utility-based comparison of some models of exchange rate volatility," Journal of International Economics, Elsevier, vol. 35(1-2), pages 23-45, August.
    18. Bruno Biais & Isabelle Martinez, 2004. "Price Discovery across the Rhine," Review of Finance, European Finance Association, vol. 8(1), pages 49-74.
    19. Taylor, Nicholas, 2007. "A note on the importance of overnight information in risk management models," Journal of Banking & Finance, Elsevier, vol. 31(1), pages 161-180, January.
    20. Jeff Fleming, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, February.
    21. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    22. Manabu Asai & Michael McAleer, 2005. "Dynamic Asymmetric Leverage in Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 317-332.
    23. Hentschel, Ludger, 1995. "All in the family Nesting symmetric and asymmetric GARCH models," Journal of Financial Economics, Elsevier, vol. 39(1), pages 71-104, September.
    24. Abhyankar, Abhay & Sarno, Lucio & Valente, Giorgio, 2005. "Exchange rates and fundamentals: evidence on the economic value of predictability," Journal of International Economics, Elsevier, vol. 66(2), pages 325-348, July.
    25. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    26. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    27. Michael J. Barclay, 2003. "Price Discovery and Trading After Hours," Review of Financial Studies, Society for Financial Studies, vol. 16(4), pages 1041-1073.
    28. Madhavan, Ananth, 1992. " Trading Mechanisms in Securities Markets," Journal of Finance, American Finance Association, vol. 47(2), pages 607-641, June.
    29. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 5(1), pages 31-67.
    30. Ilias Tsiakas, 2010. "The Economic Gains Of Trading Stocks Around Holidays," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 1-26.
    31. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
    32. Madhavan, Ananth & Panchapagesan, Venkatesh, 2000. "Price Discovery in Auction Markets: A Look Inside the Black Box," Review of Financial Studies, Society for Financial Studies, vol. 13(3), pages 627-658.
    33. Peter Hansen & Asger Lunde, 2003. "Testing the Significance of Calendar Effects," Working Papers 2003-03, Brown University, Department of Economics.
    34. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    35. Bruno Biais & Pierre Hillion & Chester Spatt, 1999. "Price Discovery and Learning during the Preopening Period in the Paris Bourse," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1218-1248, December.
    36. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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    Cited by:

    1. Blanc, Pierre & Chicheportiche, Rémy & Bouchaud, Jean-Philippe, 2014. "The fine structure of volatility feedback II: Overnight and intra-day effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 58-75.
    2. Kapetanios, George, 2009. "Testing for strict stationarity in financial variables," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2346-2362, December.
    3. Ilias Tsiakas, 2010. "The Economic Gains Of Trading Stocks Around Holidays," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(1), pages 1-26.
    4. 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.
    5. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    6. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    7. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2016. "Forecasting stock volatility using after-hour information: Evidence from the Australian Stock Exchange," Economic Modelling, Elsevier, vol. 52(PB), pages 592-608.
    8. Choudhry, Taufiq, 2010. "World War II events and the Dow Jones industrial index," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1022-1031, May.
    9. Umberto Triacca & Fulvia Focker, 2014. "Estimating overnight volatility of asset returns by using the generalized dynamic factor model approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 235-254, October.
    10. Liu, Qingfu & An, Yunbi, 2014. "Risk contributions of trading and non-trading hours: Evidence from Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 17-29.
    11. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.
    12. Chen, Chun-Hung & Yu, Wei-Choun & Zivot, Eric, 2012. "Predicting stock volatility using after-hours information: Evidence from the NASDAQ actively traded stocks," International Journal of Forecasting, Elsevier, vol. 28(2), pages 366-383.
    13. Pierre Blanc & R'emy Chicheportiche & Jean-Philippe Bouchaud, 2013. "The fine structure of volatility feedback II: overnight and intra-day effects," Papers 1309.5806, arXiv.org, revised May 2014.
    14. Kristjanpoller Rodríguez Werner, 2013. "Anomalías en la autocorrelación de rendimientos y la importancia de los periodos de no transacción en mercados latinoamericanos," Contaduría y Administración, Accounting and Management, vol. 58(1), pages 37-62, enero-mar.
    15. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    16. Liu, Qingfu & Wong, Ieokhou & An, Yunbi & Zhang, Jinqing, 2014. "Asymmetric Information and Volatility Forecasting in Commodity Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 79-97.

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