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The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility

Rodrigo Hizmeri, Marwan Izzeldin, Anthony Murphy () and Mike Tsionas

No 1902, Working Papers from Federal Reserve Bank of Dallas

Abstract: We propose a novel approach to decompose realized jump measures by type of activity (finite/infinite) and sign, and also provide noise-robust versions of the ABD jump test (Andersen et al., 2007b) and realized semivariance measures. We find that infinite (finite) jumps improve the forecasts at shorter (longer) horizons; but the contribution of signed jumps is limited. As expected, noise-robust measures deliver substantial forecast improvements at higher sampling frequencies, although standard volatility measures at the 300-second frequency generate the smallest MSPEs. Since no single model dominates across sampling frequency and forecasting horizon, we show that model averaged volatility forecasts—using time-varying weights and models from the model confidence set—generally outperform forecasts from both the benchmark and single best extended HAR model. Finally, forecasts using volatility and jump measures based on transaction sampling are inferior to the forecasts from clock-based sampling.

Keywords: Volatility Forecasts; Realized Volatility; Finite Activity Jumps; Infinite Activity Jumps; Signed Jumps; Noise-Robust Realized Volatility; Model Averaging (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 C58 (search for similar items in EconPapers)
Pages: 52
Date: 2019-03-28, Revised 2022-12-17
New Economics Papers: this item is included in nep-for and nep-ore
Note: A previous version of this paper circulated under the title "The Contribution of Jump Activity and Sign to Forecasting Stock Price Volatility."
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Published in Journal of Empirical Finance

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Related works:
Journal Article: The contribution of jump signs and activity to forecasting stock price volatility (2023) Downloads
Working Paper: The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility (2021) Downloads
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DOI: 10.24149/wp1902r2

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