cover image: Good Volatility, Bad Volatility and Option Pricing /

Premium

20.500.12592/m9csj9

Good Volatility, Bad Volatility and Option Pricing /

4 Dec 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'--Abstract, p. ii.
economics estimation theory mathematics prices cov volatility covariance likelihood function likelihood black–scholes model log-likelihood autoregressive conditional heteroskedasticity mathematical and quantitative methods (economics) option valuation volatilities likelihood-ratio test greeks (finance) implied volatility gaussian copula (probability theory) vix likelihoods
ISSN
17019397
Pages
48
Published in
Ottawa, ON, CA

Related Topics

All