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Impacts of Interval Computing on Stock Market Variability Forecasting

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  • Ling He
  • Chenyi Hu

Abstract

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Suggested Citation

  • Ling He & Chenyi Hu, 2009. "Impacts of Interval Computing on Stock Market Variability Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 33(3), pages 263-276, April.
    • Handle: RePEc:kap:compec:v:33:y:2009:i:3:p:263-276
    DOI: 10.1007/s10614-008-9159-x
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    References listed on IDEAS

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    1. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-473, Sept.-Oct.
    2. Ling T. He & Chenyi Hu, 2007. "Impacts of interval measurement on studies of economic variability: Evidence from stock market variability forecasting," Journal of Risk Finance, Emerald Group Publishing, vol. 8(5), pages 489-507, November.
    3. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
    6. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    7. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    8. Everette S. Gardner, Jr., 1988. "A Simple Method of Computing Prediction Intervals for Time Series Forecasts," Management Science, INFORMS, vol. 34(4), pages 541-546, April.
    9. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    10. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Javier Arroyo & Rosa Espínola & Carlos Maté, 2011. "Different Approaches to Forecast Interval Time Series: A Comparison in Finance," Computational Economics, Springer;Society for Computational Economics, vol. 37(2), pages 169-191, February.
    2. Černý, Michal & Hladík, Milan, 2014. "The complexity of computation and approximation of the t-ratio over one-dimensional interval data," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 26-43.
    3. Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.

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    More about this item

    Keywords

    Interval forecast; Interval computing; The OLS lower and upper bound forecasting; Accuracy ratio; C53; C82;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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