Good Volatility, Bad Volatility and Option Pricing

44 Pages Posted: 4 Mar 2016 Last revised: 30 Nov 2017

See all articles by Bruno Feunou

Bruno Feunou

Bank of Canada

Cedric Okou

University of Quebec at Montreal (UQAM)

Date Written: November 29, 2017


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 semi-variance dynamics driven by their model-free proxies. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

Keywords: Dynamic Upside Volatility, Dynamic Downside Volatility, Dynamic Skewness, Realized Downside Volatility, Realized Upside Volatility

JEL Classification: G12

Suggested Citation

Feunou, Bruno and Okou, Cedric, Good Volatility, Bad Volatility and Option Pricing (November 29, 2017). Journal of Financial and Quantitative Analysis (JFQA), Forthcoming, Available at SSRN: or

Bruno Feunou (Contact Author)

Bank of Canada ( email )

234 Wellington Street
Ottawa, Ontario K1A 0G9
613-782-8302 (Phone)


Cedric Okou

University of Quebec at Montreal (UQAM) ( email )

PB 8888 Station DownTown
Succursale Centre Ville
Montreal, Quebec H3C3P8
514-987-3000 Ext. 5521 (Phone)

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