Testing for a Single-Factor Stochastic Volatility in Bivariate Series

Journal of Risk and Financial Management

Masaru Chiba¹ 

[1] Faculty of Engineering, Fukui University of Technology, 3-6-1 Gakuen, Fukui 910-8505, Japan; E-Mail:

关键词: stochastic volatility model;    Kalman filter;    Lagrange multiplier test;   

DOI  :  10.3390/jrfm6010031

来源: mdpi

【 摘 要 】

This paper proposes the Lagrange multiplier test for the null hypothesis that the bivariate time series has only a single common stochastic volatility factor and no idiosyncratic volatility factor. The test statistic is derived by representing the model in a linear state-space form under the assumption that the log of squared measurement error is normally distributed. The empirical size and power of the test are examined in Monte Carlo experiments. We apply the test to the Asian stock market indices.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.