Pricing CBOE VIX in non-affine GARCH models with variance risk premium

被引：2

作者：

Tong, Chen ^{[1
,2
,3
,4
]}

机构：

[1] Xiamen Univ, Sch Econ, Dept Finance, Xiamen, Peoples R China

[2] Xiamen Univ, Wang Yanan Inst Studies Econ WISE, Xiamen, Peoples R China

[3] Xiamen Univ, Sch Econ, Dept Finance, Xiamen 361005, Fujian, Peoples R China

[4] Xiamen Univ, Wang Yanan Inst Studies Econ WISE, Xiamen 361005, Fujian, Peoples R China

来源：

FINANCE RESEARCH LETTERS | 2024年 / 62卷

基金：

中国国家自然科学基金;

关键词：

Generalized LRNVR; VIX pricing; Non-affine GARCH; Variance risk premium; Risk neutralization; VOLATILITY; RETURNS; FUTURES;

D O I：

10.1016/j.frl.2024.105115

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

The commonly used local risk -neutral valuation relationship (LRNVR) for non-affine GARCH models only compensates for the equity risk premium. In this paper, we propose a direct approach to bridge the physical and risk -neutral measures for non-affine GARCH models, explicitly accounting for the variance risk premium. This method avoids the need to specify a particular form of pricing kernel when it is potentially complex. The closed -form CBOE VIX pricing formulas can be easily derived for several popular non-affine GARCH models, including EGARCH, GJR-GARCH, and NGARCH. Empirical results demonstrate that the newly proposed framework yields superior pricing performance for CBOE VIX.

引用

页数：8

共 24 条

[1] Non-affine GARCH Option Pricing Models, Variance-Dependent Kernels, and Diffusion Limits* [J].