Time-varying Betas of the Banking Sector
AbstractThis paper analyses the evolution of systematic risk of banking industries in eight advanced countries using weekly data from 1990 to 2012. The estimation of time-varying betas is done 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 largely across countries. Finally, our results do not support the previous findings that systematic risk of the banking sector was underestimated before the last financial crisis.
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Bibliographic InfoPaper provided by Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its series Working Papers IES with number 2012/23.
Date of creation: Jul 2012
Date of revision: Jul 2012
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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-10-06 (All new papers)
- NEP-BAN-2012-10-06 (Banking)
- NEP-CBA-2012-10-06 (Central Banking)
- NEP-ORE-2012-10-06 (Operations Research)
- NEP-RMG-2012-10-06 (Risk Management)
You can help add them by filling out this form.
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