Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/339197 
Year of Publication: 
2025
Series/Report no.: 
Working Paper No. 14/2025
Publisher: 
Örebro University School of Business, Örebro
Abstract: 
We propose a high-frequency stochastic volatility model that integrates persistent component, intraday periodicity, and volume-driven time-of-day effects. By allowing intraday volatility patterns to respond to lagged trading activity, the model captures economically and statistically relevant departures from traditional intraday seasonality effects. We find that the volumedriven component accounts for a substantial share of intraday volatility for futures data across equity indexes, currencies, and commodities. Out-of-sample, our forecasts achieve near-zero intercepts, unit slopes, and the highest R2 values in Mincer-Zarnowitz regressions, while horserace regressions indicate that competing forecasts add little information once our predictions are included. These statistical improvements translate into economically meaningful gains, as volatility-managed portfolio strategies based on our model consistently improve Sharpe ratios. Our results highlight the value of incorporating lagged trading activity into high-frequency volatility models.
Subjects: 
Intraday volatility
high-frequency
volume
periodicity
JEL: 
C11
C22
C53
C58
Document Type: 
Working Paper

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