EconPapers    
Economics at your fingertips  
 

Beyond Stochastic Volatility and Jumps in Returns and Volatility

Garland Durham and Yang-Ho Park

Journal of Business & Economic Statistics, 2013, vol. 31, issue 1, 107-121

Abstract: While a great deal of attention has been focused on stochastic volatility in stock returns, there is strong evidence suggesting that return distributions have time-varying skewness and kurtosis as well. Under the risk-neutral measure, for example, this can be observed from variation across time in the shape of Black--Scholes implied volatility smiles. This article investigates model characteristics that are consistent with variation in the shape of return distributions using a stochastic volatility model with a regime-switching feature to allow for random changes in the parameters governing volatility of volatility, leverage effect, and jump intensity. The analysis consists of two steps. First, the models are estimated using only information from observed returns and option-implied volatility. Standard model assessment tools indicate a strong preference in favor of the proposed models. Since the information from option-implied skewness and kurtosis is not used in fitting the models, it is available for diagnostic purposes. In the second step of the analysis, regressions of option-implied skewness and kurtosis on the filtered state variables (and some controls) suggest that the models have strong explanatory power for these characteristics.

Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2013.747800 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:31:y:2013:i:1:p:107-121

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1080/07350015.2013.747800

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:jnlbes:v:31:y:2013:i:1:p:107-121