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A High-Low Model of Daily Stock Price Ranges Author info | Abstract | Publisher info | Download info | Related research | Statistics 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)
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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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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 2009Date of revision:
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Keywords: Daily High ; Daily Low ; VECM Model ; Forecast Performance ; Implied Volatility ; Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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