Translating overnight and intraday returns to improve daily volatility forecast accuracy

Recent research suggests the information content in overnight and intraday returns, unlike trading volume, improves the statistical accuracy of daily volatility forecasts.



Historical patterns in equity prices have been used extensively to devise active trading strategies such as, for instance, momentum1 and technical trading rules.2 However, a consensus view among forecasters is that daily returns are to a large extent unpredictable and it is easier to predict the conditional volatility of the daily return distribution due to persistence (clustering) in volatility.

In recent years a number of studies in high-frequency financial econometrics

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