J. Risk Financial Manag. 2013, 6(1), 31-61; doi:10.3390/jrfm6010031
Article

Testing for a Single-Factor Stochastic Volatility in Bivariate Series

Received: 4 October 2013; in revised form: 25 November 2013 / Accepted: 12 December 2013 / Published: 19 December 2013
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption that the log of squared measurement error isnormally distributed. The empirical size and power of the test are examined in Monte Carloexperiments. We apply the test to the Asian stock market indices.
Keywords: stochastic volatility model; Kalman filter; Lagrange multiplier test
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MDPI and ACS Style

Chiba, M.; Kobayashi, M. Testing for a Single-Factor Stochastic Volatility in Bivariate Series. J. Risk Financial Manag. 2013, 6, 31-61.

AMA Style

Chiba M, Kobayashi M. Testing for a Single-Factor Stochastic Volatility in Bivariate Series. Journal of Risk and Financial Management. 2013; 6(1):31-61.

Chicago/Turabian Style

Chiba, Masaru; Kobayashi, Masahito. 2013. "Testing for a Single-Factor Stochastic Volatility in Bivariate Series." J. Risk Financial Manag. 6, no. 1: 31-61.

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