Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Testing Option Pricing Models with Stochastic Volatility, Random Jumps and Stochastic Interest Rates

Testing Option Pricing Models with Stochastic Volatility, Random Jumps and Stochastic Interest Rates In this paper, we propose a parsimonious GMM estimation and testing procedure for continuous‐time option pricing models with stochastic volatility, random jump and stochastic interest rate. Statistical tests are performed on both the underlying asset return model and the risk‐neutral option pricing model. Firstly, the underlying asset return models are estimated using GMM with valid statistical tests for model specification. Secondly, the preference related parameters in the risk‐neutral distribution are estimated from observed option prices. Our findings confirm that the implied risk premiums for stochastic volatility, random jump and interest rate are overall positive and varying over time. However, the estimated risk‐neutral processes are not unique, suggesting a segmented option market. In particular, the deep ITM call (or deep OTM put) options are clearly priced with higher risk premiums than the deep OTM call (or deep ITM put) options. Finally, while stochastic volatility tends to better price long‐term options, random jump tends to price the short‐term options better, and option pricing based on multiple risk‐neutral distributions significantly outperforms that based on a single risk‐neutral distribution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Review of Finance Wiley

Testing Option Pricing Models with Stochastic Volatility, Random Jumps and Stochastic Interest Rates

Jiang, George J.
International Review of Finance , Volume 3 (3‐4) – Sep 1, 2002
Download PDF
40 pages

Loading next page...
 
/lp/wiley/testing-option-pricing-models-with-stochastic-volatility-random-jumps-sQwU5337uu

References (75)

Publisher
Wiley
Copyright
Copyright © 2002 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1369-412X
eISSN
1468-2443
DOI
10.1111/j.1369-412X.2002.00040.x
Publisher site
See Article on Publisher Site

Abstract

In this paper, we propose a parsimonious GMM estimation and testing procedure for continuous‐time option pricing models with stochastic volatility, random jump and stochastic interest rate. Statistical tests are performed on both the underlying asset return model and the risk‐neutral option pricing model. Firstly, the underlying asset return models are estimated using GMM with valid statistical tests for model specification. Secondly, the preference related parameters in the risk‐neutral distribution are estimated from observed option prices. Our findings confirm that the implied risk premiums for stochastic volatility, random jump and interest rate are overall positive and varying over time. However, the estimated risk‐neutral processes are not unique, suggesting a segmented option market. In particular, the deep ITM call (or deep OTM put) options are clearly priced with higher risk premiums than the deep OTM call (or deep ITM put) options. Finally, while stochastic volatility tends to better price long‐term options, random jump tends to price the short‐term options better, and option pricing based on multiple risk‐neutral distributions significantly outperforms that based on a single risk‐neutral distribution.

Journal

International Review of Finance – Wiley

Published: Sep 1, 2002

There are no references for this article.