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Testing for a Single-Factor Stochastic Volatility in Bivariate Series
Faculty of Engineering, Fukui University of Technology, 3-6-1 Gakuen, Fukui 910-8505, Japan
Faculty of Economics, Yokohama National University, 79-4 Tokiwadai, Yokohama 240-8501, Japan
* Author to whom correspondence should be addressed.
Received: 4 October 2013; in revised form: 25 November 2013 / Accepted: 12 December 2013 / Published: 19 December 2013
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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Cite This Article
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.
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.
Chiba, Masaru; Kobayashi, Masahito. 2013. "Testing for a Single-Factor Stochastic Volatility in Bivariate Series." J. Risk Financial Manag. 6, no. 1: 31-61.