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