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Testing for a single-factor stochastic volatility in bivariate series
- Source :
- Journal of Risk and Financial Management, Volume 6, Issue 1, Pages 31-61, Journal of Risk and Financial Management, Vol 6, Iss 1, Pp 31-61 (2013)
- Publication Year :
- 2013
- Publisher :
- Basel: MDPI, 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.
- Subjects :
- Score test
lcsh:Risk in industry. Risk management
jel:E
Bivariate analysis
jel:C
jel:G
stochastic volatility model
lcsh:Finance
lcsh:HG1-9999
Statistics
Test statistic
Forward volatility
Economics
Econometrics
ddc:330
C58
Kalman filter
Lagrange multiplier test
C32
C12
Stochastic volatility
Stock market index
lcsh:HD61
jel:F2
jel:F3
Volatility (finance)
Null hypothesis
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Journal of Risk and Financial Management, Volume 6, Issue 1, Pages 31-61, Journal of Risk and Financial Management, Vol 6, Iss 1, Pp 31-61 (2013)
- Accession number :
- edsair.doi.dedup.....da4729ac194b799a1b5284cd3531d4e8