Good Volatility, Bad Volatility, and Option Pricing

Autor: Bruno Feunou, Cedric Okou
Rok vydání: 2018
Předmět:
Zdroj: Journal of Financial and Quantitative Analysis. 54:695-727
ISSN: 1756-6916
0022-1090
Popis: 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-variance dynamics. In our setup, both semi-variances are state variables driven by their model-free empirical proxies and random innovations. Our option valuation model belongs to the discrete-time-affine family, thus delivering convenient closed-form pricing expressions and allowing for direct filtering and estimation. When fitted to S&P 500 index options, realized upside and downside variances, and returns, the new specification outperforms common benchmark models in terms of fitting accuracy and likelihood improvements.
Databáze: OpenAIRE