Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/178541 
Year of Publication: 
2013
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 6 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2013 [Pages:] 31-61
Publisher: 
MDPI, Basel
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.
Subjects: 
stochastic volatility model
Kalman filter
Lagrange multiplier test
JEL: 
C12
C32
C58
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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