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AN ANALYTICAL APPROACH FOR VARIANCE SWAPS WITH AN ORNSTEIN–UHLENBECK PROCESS

Published online by Cambridge University Press:  19 July 2017

JIAN-PENG CAO
Affiliation:
School of Mathematics and Statistics, Ningxia University, Yinchuan, 750021, China email [email protected], [email protected]
YAN-BING FANG*
Affiliation:
School of Mathematics and Statistics, Ningxia University, Yinchuan, 750021, China email [email protected], [email protected]
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Abstract

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Pricing variance swaps have become a popular subject recently, and most research of this type come under Heston’s two-factor model. This paper is an extension of some recent research which used the dimension-reduction technique based on the Heston model. A new closed-form pricing formula focusing on a log-return variance swap is presented here, under the assumption that the underlying asset prices can be described by a mean-reverting Gaussian volatility model (Ornstein–Uhlenbeck process). Numerical tests in two respects using the Monte Carlo (MC) simulation are included. Moreover, we discuss a procedure of solving a quadratic differential equation with one variable. Our method can avoid the previously encountered limitations, but requires more time for calculation than other recent analytical discrete models.

MSC classification

Type
Research Article
Copyright
© 2017 Australian Mathematical Society 

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