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Good Volatility, Bad Volatility, and Option Pricing

Published online by Cambridge University Press:  13 September 2018

Bruno Feunou  and
Cédric Okou
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Abstract

Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. To appraise the economic gain of this decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semivariance dynamics driven by the model-free proxies of the variances. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 54 , Issue 2 , April 2019 , pp. 695 - 727
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2018 

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Footnotes

1

We are indebted to Jennifer Conrad (the editor) and an anonymous referee for helpful comments that improved the article. We pay a special tribute to Peter Christoffersen, colleague and friend, who passed away on June 22, 2018, and whose guidance and support greatly shaped this research agenda. Our hearts and thoughts go out to his family. We also thank Diego Amaya, Christian Dorion, Yoontae Jeon, and seminar participants at HEC Montréal and Université Paris Nanterre for fruitful discussions. We gratefully acknowledge financial support from the Bank of Canada, the Université du Québec à Montréal (UQAM) research funds, and the Canadian Derivatives Institute (CDI). The views expressed in this article are those of the authors. No responsibility for them should be attributed to the Bank of Canada.

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