Bivariate Options Pricing with Copula-Based GARCH Model -Empirical Analysis
Date Issued
2009
Date
2009
Author(s)
Hsu, Kai-Wen
Abstract
Multivariate options have experienced significant development in the last decade, due to their excellent abilities for hedging the risk of multiple assets. The most important issue in the valuation of multivariate options is the dependence structure among these underlying assets. In this paper, we use copula-based GARCH model as pricing device to describe the dependence structures of underlying assets, rather than the traditional linear correlation and Gaussian assumptions to price multivariate claims. Particularly, the skewed-t GARCH model is applied to capture the marginal distributions of underlying financial assets. To compare the impact of difference dependence structures on option pricing, we perform Monte-Carlo simulation to simulate the bivariate option prices, and observe the error of option prices caused from different model dependence structures, time-to-maturities, strike prices and option payoff functions. We use goodness-of-fit tests to choose one dependence model that fit the empirical distributions best, and then the paired t-test is also implemented to determine whether the pricing errors are significant enough.
Subjects
Bivariate Option
Copula
Dependent Structure
GARCH
Monte Carlo
Parameter Estimation
Type
thesis
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