Good Volatility, Bad Volatility, and Option Pricing

Bruno Feunou and Cédric Okou

Advances in variance analysis permit to split 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 stock price distribution’s asymmetry. 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-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.