Good Volatility, Bad Volatility and Option Pricing

44 Pages Posted: 4 Mar 2016 Last revised: 8 Dec 2016

Bruno Feunou

Bank of Canada

Cedric Okou

University of Quebec at Montreal (UQAM)

Date Written: December 1, 2016


Advances in variance analysis permit to split the total quadratic variation of a jump-diffusion process into upside and downside components, commonly referred to as good and bad volatilities. This decomposition yields enhanced volatility predictions over standard approaches, as documented by many recent studies. To appraise the economic gain of the decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semi-variances driven by their model-free empirical proxies and random innovations. This discrete-time option valuation framework outperforms common benchmark models in terms of fitting accuracy and likelihood improvements. The model also delivers realistic term structures of risk-neutral moments and variance risk premia.

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 (December 1, 2016). 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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