A high-low model of daily stock price ranges

Stephen Y L CHEUNG, Yin Wong Cheung*, Alan T.K. Wan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)103-119
Number of pages17
JournalJournal of Forecasting
Volume28
Issue number2
DOIs
Publication statusPublished - Mar 2009

Scopus Subject Areas

  • Modelling and Simulation
  • Computer Science Applications
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research

User-Defined Keywords

  • Daily high
  • Daily low
  • Forecast performance
  • Implied volatility
  • VECM model

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