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Published in: Journal of Financial Services Research 1/2017

13-01-2016

Non-interest Income, Trading, and Bank Risk

Authors: Carl R. Chen, Ying Sophie Huang, Ting Zhang

Published in: Journal of Financial Services Research | Issue 1/2017

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Abstract

This study examines the interaction of bank risk and non-interest income (trading and non-trading) controlling for the executive incentive compensation effect. We do not find executive stock option compensation (ESO) directly impacts bank risk. On the contrary, bank non-interest income, both trading and non-trading revenue components, positively and significantly affects bank risk. This result is robust to the difference-in-difference regressions, bank fixed effect, and the exclusion of too-big-to-fail banks. In a simultaneous equations setting, non-interest income activities affect bank risk of all types, while ESO does not. Moreover, idiosyncratic risk has a positive effect on bank non-interest income activities, but systematic risk has no effect. This result suggests that executives of banks with high idiosyncratic risk have more incentive to expand into the territory of non-interest income activities. Since high-risk banks pose more concern to investors and regulators, we further examine bank risk by means of quantile regressions which dissect the behavior of banks at the tail risk distribution. The findings point out that banks’ decision to diversify into non-traditional business lines is associated with risks in high-risk banks. The impact of non-interest income/trading revenues on bank risk increases in risk, and often the largest impact is spotted for banks with extreme risks. This implies that the leverage effect of non-interest income/trading activities is larger in high-risk banks.

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Footnotes
1
For example, Smith and Stulz (1985); Chen et al. (2006); and Larraza-Kintana et al. (2007).
 
2
Wall Street Journal, “Volcker Rule Delay is Likely,” by McGrane and Lucchetti, page C1, September 12, 2011.
 
3
There are 26,444 firm-CEO observations if we only retrieve the CEO compensations. After considering the highest compensation for executives, the sample size increases by 15.57 % to 30,561 observations.
 
4
We include time dummy and cluster the standard errors by firm in order to remove two sources of correlation (across firms and across time). This is done following Anderson and Reeb (2004) and Faulkender and Petersen (2006) because our dataset has more firms than years. In the robustness test, we include firm fixed effect and the results are consistent.
 
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Metadata
Title
Non-interest Income, Trading, and Bank Risk
Authors
Carl R. Chen
Ying Sophie Huang
Ting Zhang
Publication date
13-01-2016
Publisher
Springer US
Published in
Journal of Financial Services Research / Issue 1/2017
Print ISSN: 0920-8550
Electronic ISSN: 1573-0735
DOI
https://doi.org/10.1007/s10693-015-0235-9

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