We construct an empirical model for daily highs and daily lows of US stock indexes based on the intuition that highs and lows do not drift apart over time. Our empirical results show that daily highs and lows of three main US stock price indexes are cointegrated. Data on openings, closings, and trad
A high–low model of daily stock price ranges
✍ Scribed by Yan-Leung Cheung; Yin-Wong Cheung; Alan T. K. Wan
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 163 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1087
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✦ Synopsis
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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