PRICING VARIANCE SWAPS USING EXTENDED HESTON MODEL

Authors

• Semere Gebresilasie, School of Computing and Data Science, Wentworth Institute of Technology, Boston, MA 02115, USAFollow
• Mulue Gebreslasie, North Dakota State UniversityFollow
• Indranil SenGupta, City University of New YorkFollow

Abstract

Abstract. In this study, we introduce a variance swap for the underlying asset utilizing the Heston model, incorporating a long-term variance that is treated as a stochastic function of time. We develop a closed-form solution for the variance swap under this framework, where the log returns are driven by a compound Poisson process. Our analysis of historical data reveals that long-term variance is not constant; instead, it fluctuates over time, reflecting market dynamics more accurately. By integrating this time-varying long-term variance into the model, we achieve an improvement in prediction performance of approximately 60%. Furthermore, we perform model calibration using a nonlinear least squares estimator, ensuring the robustness and accuracy of our approach. This work not only enhances the understanding of variance swaps in financial markets but also contributes to more effective risk management strategies.

Recommended Citation

Gebresilasie, Semere; Gebreslasie, Mulue; and SenGupta, Indranil (2026) "PRICING VARIANCE SWAPS USING EXTENDED HESTON MODEL," Journal of Stochastic Analysis: Vol. 7: No. 1, Article 1.
DOI: 10.31390/josa.7.1.01
Available at: https://repository.lsu.edu/josa/vol7/iss1/1

DOI

10.31390/josa.7.1.01