 Impact of volatility jumps in a mean-reverting model: Derivative pricing and empirical evidenceHsin-Yu Chiu and Ting-Fu Chen The North American Journal of Economics and Finance, 2020, vol. 52, issue C Abstract: This paper investigates the critical role of volatility jumps under mean reversion models. Based on the empirical tests conducted on the historical prices of commodities, we demonstrate that allowing for the presence of jumps in volatility in addition to price jumps is a crucial factor when confronting non-Gaussian return distributions. By employing the particle filtering method, a comparison of results drawn among several mean-reverting models suggests that incorporating volatility jumps ensures an improved fit to the data. We infer further empirical evidence for the existence of volatility jumps from the possible paths of filtered state variables. Our numerical results indicate that volatility jumps significantly affect the level and shape of implied volatility smiles. Finally, we consider the pricing of options under the mean reversion model, where the underlying asset price and its volatility both have jump components. Keywords: Mean reversion; Stochastic volatility; Volatility jumps; Particle filtering; Implied volatility smiles (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940819300026 DOI: 10.1016/j.najef.2019.101112 Access Statistics for this article The North American Journal of Economics and Finance is currently edited by Hamid Beladi More articles in The North American Journal of Economics and Finance from Elsevier |
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