Option pricing under autoregressive random variance models

Tak Kuen Siu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The autoregressive random variance (ARV) model introduced by Taylor (1980, 1982, 1986) is a popular version of stochastic volatility (SV) models and a discrete-time simplification of the continuous-time diffusion SV models. This paper introduces a valuation model for options under a discrete-time ARV model with general stock and volatility innovations. It employs the discrete-time version of the Esscher transform to determine an equivalent martingale measure under an incomplete market. Various parametric cases of the ARV models, are considered, namely, the log-normal ARV models, the jump-type Poisson ARV models, and the gamma ARV models, and more explicit pricing formulas of a European call option under these parametric cases are provided. A Monte Carlo experiment for some parametric cases is also conducted.

Original languageEnglish
Pages (from-to)62-75
Number of pages14
JournalNorth American Actuarial Journal
Issue number2
Publication statusPublished - Apr 2006


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