Time-Varying Betas of Banking Sectors
AbstractThis paper analyzes the evolution of the systematic risk of the banking industries in eight advanced countries using weekly data from 1990 to 2012. Time-varying betas are estimated by means of a Bayesian state-space model with stochastic volatility, whose results are contrasted with those of the standard M-GARCH and rolling-regression models. We show that both country-specific and global events affect the perceived systematic risk, while the impact of the latter differs considerably across countries. Finally, our results do not support the previous findings that the systematic risk of the banking sector was underestimated before the last financial crisis.
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Bibliographic InfoArticle provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.
Volume (Year): 62 (2012)
Issue (Month): 6 (December)
CAPM; time-varying beta; multivariate GARCH; Bayesian state-space models; stochastic volatility;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
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