High-low range in GARCH models of stock return volatility

ABSTRACT We suggest a simple and general way to improve the GARCH volatility models using the intraday range between the highest and the lowest price to proxy volatility. We illustrate the method by modifying a GARCH(1,1) model to a range-GARCH(1,1) model. Our empirical analysis conducted on stocks, stock indices and simulated data shows that the range-GARCH(1,1) model performs significantly better than the standard GARCH(1,1) model both in terms of in-sample fit and out-of-sample forecasting ability.

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