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.
| Original language | English |
|---|---|
| Pages (from-to) | 57-72 |
| Number of pages | 16 |
| Journal | The Banking and Finance Review |
| Volume | 2 |
| Issue number | 1 |
| Publication status | Published - 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 9 Industry, Innovation, and Infrastructure
-
SDG 10 Reduced Inequalities
Fingerprint
Dive into the research topics of 'Banks, risk, and the business cycle: an analysis based on real-time data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver