Banks, risk, and the business cycle: an analysis based on real-time data
Banks, risk, and the business cycle: an analysis based on real-time data
An important question for stock market investors and bank supervisors is to which extent the stock returns of banks reflect business-cycle-sensitive risk in the banking industry. In order to answer this question, we used the stochastic discount factor model to derive a multivariate exponential GARCH-in-mean model. We used monthly U.S. data for the period from 1980 to 2006, for both real-time and revised macroeconomic data to estimate the model. Our empirical results show that using real-time rather than revised macroeconomic data can significantly alter estimates of the risk premium that stock market investors require for bearing business-cycle-sensitive risk in the banking industry.
57-72
Kizys, Renatas
9d3a6c5f-075a-44f9-a1de-32315b821978
Pierdzioch, Christian
60eb79c6-d98e-4ceb-a634-9acaf7ebc451
2010
Kizys, Renatas
9d3a6c5f-075a-44f9-a1de-32315b821978
Pierdzioch, Christian
60eb79c6-d98e-4ceb-a634-9acaf7ebc451
Kizys, Renatas and Pierdzioch, Christian
(2010)
Banks, risk, and the business cycle: an analysis based on real-time data.
The Banking and Finance Review, 2 (1), .
Abstract
An important question for stock market investors and bank supervisors is to which extent the stock returns of banks reflect business-cycle-sensitive risk in the banking industry. In order to answer this question, we used the stochastic discount factor model to derive a multivariate exponential GARCH-in-mean model. We used monthly U.S. data for the period from 1980 to 2006, for both real-time and revised macroeconomic data to estimate the model. Our empirical results show that using real-time rather than revised macroeconomic data can significantly alter estimates of the risk premium that stock market investors require for bearing business-cycle-sensitive risk in the banking industry.
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Published date: 2010
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Local EPrints ID: 434456
URI: http://eprints.soton.ac.uk/id/eprint/434456
ISSN: 1947-7945
PURE UUID: 86bb2a9c-c26c-4b72-aaf2-005e064a87cc
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Date deposited: 24 Sep 2019 16:30
Last modified: 16 Mar 2024 04:41
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Author:
Christian Pierdzioch
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