Dependence Modelling using GARCH, EGARCH, and Copula Models:

Approximating the GJR-GARCH and EGARCH Option Pricing Models Analytically

In Duan, Gauthier and Simonato (1999), an analytical approximate formula for European options in the GARCH framework was developed. The formula is however restricted to the nonlinear asymmetric GARCH model. This paper extends the same approach to two other important GARCH specifications GJR-GARCH and EGARCH. We provide the corresponding formulas and study their numerical performance. keywords: ...

Risk Management in Oil Market: A Comparison between Multivariate GARCH Models and Copula-based Models

H igh price volatility and the risk are the main features of commodity markets. One way to reduce this risk is to apply the hedging policy by future contracts. In this regard, in this paper, we will calculate the optimal hedging ratios for OPEC oil. In this study, besides the multivariate GARCH models, for the first time we use conditional copula models for modelling dependence struc...

Dynamic Tail Dependence in Copula-GARCH Models: an Application to Stock-Index Returns

1. Methods and application Several studies in empirical finance literature have highlighted the importance of allowing for skewness, tail-fatness, non normality of returns for asset allocation and pricing models. Moreover, the dependence between returns, that can impact portfolio decisions, often exhibits nonlinear structures and asymmetric extremal behavior that the usual correlation coefficie...

Dependence Modelling via the Copula Method

Optimal dynamic hedging via copula-threshold-GARCH models

The contribution of this paper is twofold. First, we exploit copula methodology, with two threshold GARCH models as marginals, to construct a bivariate copula-threshold-GARCH model, simultaneously capturing asymmetric nonlinear behaviour in univariate stock returns of spot and futures markets and bivariate dependency, in a flexible manner. Two elliptical copulas (Gaussian and Student’s-t) and t...