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Modelling the Impact of Overnight Surprises on Intra-daily Volatility

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Abstract

In this paper we evaluate the impact that stock returns recorded between market closing and opening the next business day have on intra-daily volatility. A simple test shows that the estimated volatility clustering of the intra-daily returns may be affected by a market opening surprise bias. An extension of the standard GARCH model is suggested here to include the effect of this surprise and is applied on a sample of largely traded US stocks. The performance of two specifications in which this effect is included is evaluated in an out-of-sample forecasting exercise relative to their standard counterparts.

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File URL: http://local.disia.unifi.it/ricerca/pubblicazioni/working_papers/2001/wp2001_02.pdf
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Bibliographic Info

Paper provided by Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" in its series Econometrics Working Papers Archive with number wp2001_02.

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Length: 23 pages
Date of creation: 2001
Date of revision:
Handle: RePEc:fir:econom:wp2001_02

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Keywords: Volatility forecasting; univariate GARCH; market opening surprise bias.;

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References

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  1. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  2. Romer, David, 1993. "Rational Asset-Price Movements without News," American Economic Review, American Economic Association, vol. 83(5), pages 1112-30, December.
  3. Gerety, Mason S & Mulherin, J Harold, 1994. "Price Formation on Stock Exchanges: The Evolution of Trading within the Day," Review of Financial Studies, Society for Financial Studies, vol. 7(3), pages 609-29.
  4. Amihud, Yakov & Mendelson, Haim, 1987. " Trading Mechanisms and Stock Returns: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 42(3), pages 533-53, July.
  5. Gallo, G.M. & Pacini, B., 1998. "Early News Is Good News. The Effects of Market Opening on Market Volatility," Economics Working Papers eco98/3, European University Institute.
  6. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
  7. Stoll, Hans R & Whaley, Robert E, 1990. "Stock Market Structure and Volatility," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 37-71.
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Cited by:
  1. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
  2. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  3. Hiroki Masuda & Takayuki Morimoto, 2009. "An Optimal Weight for Realized Variance Based on Intermittent High-Frequency Data," Global COE Hi-Stat Discussion Paper Series gd08-033, Institute of Economic Research, Hitotsubashi University.
  4. 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.
  5. Christian T. Brownlees & Giampiero Gallo, 2008. "Comparison of Volatility Measures: a Risk Management Perspective," Econometrics Working Papers Archive wp2008_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".

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