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

Testing for a Single-Factor Stochastic Volatility in Bivariate Series

1
Faculty of Engineering, Fukui University of Technology, 3-6-1 Gakuen, Fukui 910-8505, Japan
2
Faculty of Economics, Yokohama National University, 79-4 Tokiwadai, Yokohama 240-8501, Japan
*
Author to whom correspondence should be addressed.
Received: 4 October 2013 / Revised: 25 November 2013 / Accepted: 12 December 2013 / Published: 19 December 2013
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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. View Full-Text
Keywords: stochastic volatility model; Kalman filter; Lagrange multiplier test stochastic volatility model; Kalman filter; Lagrange multiplier test
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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

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