The economic value of volatility timing with realized jumps

Ingmar Nolte and Qi Xu

Journal of Empirical Finance, 2015, vol. 34, issue C, 45-59

Abstract: This paper comprehensively investigates the role of realized jumps detected from high frequency data in predicting future volatility from both statistical and economic perspectives. Using seven major jump tests, we show that separating jumps from diffusion improves volatility forecasting both in-sample and out-of-sample. Moreover, we show that these statistical improvements can be translated into economic value. We find that a risk-averse investor can significantly improve her portfolio performance by incorporating realized jumps into a volatility timing based portfolio strategy. Our results hold true across the majority of jump tests, and are robust to controlling for microstructure effects and transaction costs.

Keywords: High frequency data; Jumps; Nonparametric tests; Asset allocation; Volatility forecasting; Realized volatility (search for similar items in EconPapers)
JEL-codes: C53 C58 G11 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:34:y:2015:i:c:p:45-59

DOI: 10.1016/j.jempfin.2015.03.019

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