Assessing Day-To-Day Volatility: Doesthe Trading Time Matter?
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- José Valentim Machado Vicente & Gustavo Silva Araujo & Paula Baião Fisher de Castro & Felipe Noronha Tavares, 2014. "Assessing Day-to-Day Volatility: Does the Trading Time Matter?," Brazilian Review of Finance, Brazilian Society of Finance, vol. 12(1), pages 41-66.
References listed on IDEAS
- Michael McAleer & Marcelo Medeiros, 2008.
"Realized Volatility: A Review,"
Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 10-45.
- Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
- Bekaert, Geert & Engstrom, Eric & Xing, Yuhang, 2009.
"Risk, uncertainty, and asset prices,"
Journal of Financial Economics, Elsevier, vol. 91(1), pages 59-82, January.
- Geert Bekaert & Eric Engstrom & Yuhang Xing, 2005. "Risk, uncertainty, and asset prices," Finance and Economics Discussion Series 2005-40, Board of Governors of the Federal Reserve System (U.S.).
- Geert Bekaert & Eric Engstrom & Yuhang Xing, 2006. "Risk, Uncertainty and Asset Prices," NBER Working Papers 12248, National Bureau of Economic Research, Inc.
- Bekaert, Geert & Xing, Yuhang & Engstrom, Eric, 2006. "Risk, Uncertainty and Asset Prices," CEPR Discussion Papers 5947, C.E.P.R. Discussion Papers.
- 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.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- Lockwood, Larry J & Linn, Scott C, 1990. "An Examination of Stock Market Return Volatility during Overnight and Intraday Periods, 1964-1989," Journal of Finance, American Finance Association, vol. 45(2), pages 591-601, June.
- Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
- Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
- Day, Theodore E. & Lewis, Craig M., 1988. "The behavior of the volatility implicit in the prices of stock index options," Journal of Financial Economics, Elsevier, vol. 22(1), pages 103-122, October.
- Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
- Harris, Lawrence, 1986. "A transaction data study of weekly and intradaily patterns in stock returns," Journal of Financial Economics, Elsevier, vol. 16(1), pages 99-117, May.
- Harrison Hong & Jiang Wang, 2000. "Trading and Returns under Periodic Market Closures," Journal of Finance, American Finance Association, vol. 55(1), pages 297-354, February.
- Amihud, Yakov & Mendelson, Haim, 1987. "Trading Mechanisms and Stock Returns: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 42(3), pages 533-553, July.
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- Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
- Dicle, Mehmet F. & Levendis, John, 2020. "Historic risk and implied volatility," Global Finance Journal, Elsevier, vol. 45(C).
- James W. Taylor, 2005. "Generating Volatility Forecasts from Value at Risk Estimates," Management Science, INFORMS, vol. 51(5), pages 712-725, May.
- Sergey S. Stepanov, 2009. "Resilience of Volatility," Papers 0911.5048, arXiv.org.
- Chernov, Mikhail, 2007. "On the Role of Risk Premia in Volatility Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 411-426, October.
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JEL classification:
- G1 - Financial Economics - - General Financial Markets
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This paper has been announced in the following NEP Reports:- NEP-MST-2014-03-15 (Market Microstructure)
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