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A high-low model of daily stock price ranges

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Author Info
Yan-Leung Cheung (Department of Economics and Finance, City University of Hong Kong, Kowloon, Hong Kong)
Yin-Wong Cheung (Department of Economics, University of California, Santa Cruz, California, USA; School of Economics and Finance, University of Hong Kong, Hong Kong)
Alan T. K. Wan (Department of Management Sciences, City University of Hong Kong, Kowloon, Hong Kong)

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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 to 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 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 forecast. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1087
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 2 ()
Pages: 103-119
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:jof:jforec:v:28:y:2009:i:2:p:103-119

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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