A high-low model of daily stock price ranges

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 2387

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Forecasting Models; Simulation Methods ; General Financial Markets: General (includes Measurement and Data)
• Subject: Daily high ; daily low ; VECM model ; forecast performance ; implied volatility ; Börsenkurs ; Wertpapierhandel ; Volatilität ; Prognoseverfahren ; VAR-Modell ; Schätzung ; Welt

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Cheung, Yan-Leung ; Cheung, Yin-Wong ; Wan, Alan Tze Kin
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2008

Further information

• Handle: http://hdl.handle.net/10419/26432
• Last update: 10.03.2025, 11:42 AM CET