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A High-Low Model of Daily Stock Price Ranges

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Author Info

  • Yan-Leung Cheung

    (City University of Hong Kong)

  • Yin-Wong Cheung

    (University of California, Santa Cruz)

  • Alan T. K. Wan

    (City University of Hong Kong)

Abstract

We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance of incorporating high-low interactions in modeling the range variable. In evaluating the out-of-sample forecast performance using both mean-squared forecast error and direction of change criteria, it is found that the VECM-based low and high forecasts offer some advantages over some alternative forecasts. The VECM-based range forecasts, on the other hand, do not always dominate - the forecast rankings depend on the choice of evaluation criterion and the variables being forecasted.

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Bibliographic Info

Paper provided by Hong Kong Institute for Monetary Research in its series Working Papers with number 032009.

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Length: 42 pages
Date of creation: Jan 2009
Date of revision:
Handle: RePEc:hkm:wpaper:032009

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Keywords: Daily High; Daily Low; VECM Model; Forecast Performance; Implied Volatility;

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References

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Citations

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Cited by:
  1. Tao Xiong & Yukun Bao & Zhongyi Hu, 2014. "Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting," Papers 1401.1916, arXiv.org.
  2. He, Angela W.W. & Kwok, Jerry T.K. & Wan, Alan T.K., 2010. "An empirical model of daily highs and lows of West Texas Intermediate crude oil prices," Energy Economics, Elsevier, vol. 32(6), pages 1499-1506, November.
  3. Caporin, Massimiliano & Ranaldo, Angelo & Santucci de Magistris, Paolo, 2013. "On the predictability of stock prices: A case for high and low prices," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5132-5146.

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