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Runs tests for assessing volatility forecastability in financial time series

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  • Bellini, Fabio
  • Figa-Talamanca, Gianna

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  • Bellini, Fabio & Figa-Talamanca, Gianna, 2005. "Runs tests for assessing volatility forecastability in financial time series," European Journal of Operational Research, Elsevier, vol. 163(1), pages 102-114, May.
    • Handle: RePEc:eee:ejores:v:163:y:2005:i:1:p:102-114
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    References listed on IDEAS

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    1. Peter F. Christoffersen & Francis X. Diebold, 2000. "How Relevant is Volatility Forecasting for Financial Risk Management?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February.
    2. Wendy Lou, W. Y., 1997. "An application of the method of finite Markov chain imbedding to runs tests," Statistics & Probability Letters, Elsevier, vol. 31(3), pages 155-161, January.
    3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    4. Han, Qing & Aki, Sigeo, 1998. "Formulae and recursions for the joint distributions of success runs of several lengths in a two-state Markov chain," Statistics & Probability Letters, Elsevier, vol. 40(3), pages 203-214, October.
    5. Harvey, Campbell R & Whaley, Robert E, 1991. "S&P 100 Index Option Volatility," Journal of Finance, American Finance Association, vol. 46(4), pages 1251-1261, September.
    6. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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    Cited by:

    1. Lin, Yao-San & Li, Der-Chiang, 2010. "The Generalized-Trend-Diffusion modeling algorithm for small data sets in the early stages of manufacturing systems," European Journal of Operational Research, Elsevier, vol. 207(1), pages 121-130, November.
    2. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    3. Doyle, John R. & Chen, Catherine H., 2013. "Patterns in stock market movements tested as random number generators," European Journal of Operational Research, Elsevier, vol. 227(1), pages 122-132.
    4. Ma, T. & Fraser-Mackenzie, P.A.F. & Sung, M. & Kansara, A.P. & Johnson, J.E.V., 2022. "Are the least successful traders those most likely to exit the market? A survival analysis contribution to the efficient market debate," European Journal of Operational Research, Elsevier, vol. 299(1), pages 330-345.
    5. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2014. "An Evolving Fuzzy-Garch Approach Forfinancial Volatility Modeling And Forecasting," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 138, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    6. repec:ipg:wpaper:2014-053 is not listed on IDEAS
    7. Hua, Zhongsheng & Zhang, Bin, 2008. "Improving density forecast by modeling asymmetric features: An application to S&P500 returns," European Journal of Operational Research, Elsevier, vol. 185(2), pages 716-725, March.

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