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Author:Koutmos, G.
Knif, J.
Title:Estimating Systematic Risk Using Time Varying Distributions
Journal:European Financial Management
2002 : MAR, VOL. 8:1, p. 59-73
Index terms:RISK MEASUREMENT
RISK
RISK ANALYSIS
ESTIMATION
DISTRIBUTION
Language:eng
Abstract:This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days.
SCIMA record nr: 235750
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