Pricing Sin Stocks: Ethical Preference vs. Risk Aversion
Stefano Colonnello, Giuliano Curatola, Alessandro Gioffré
European Economic Review,
2019
Abstract
We develop an ethical preference-based model that reproduces the average return and volatility spread between sin and non-sin stocks. Our investors do not necessarily boycott sin companies. Rather, they are open to invest in any company while trading off dividends against ethicalness. When dividends and ethicalness are complementary goods and investors are sufficiently risk averse, the model predicts that the dividend share of sin companies exhibits a positive relation with the future return and volatility spreads. An empirical analysis supports the model’s predictions. Taken together, our results point to the importance of ethical preferences for investors’ portfolio choices and asset prices.
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A Capital Structure Channel of Monetary Policy
Benjamin Grosse-Rueschkamp, Sascha Steffen, Daniel Streitz
Journal of Financial Economics,
No. 2,
2019
Abstract
We study the transmission channels from central banks’ quantitative easing programs via the banking sector when central banks start purchasing corporate bonds. We find evidence consistent with a “capital structure channel” of monetary policy. The announcement of central bank purchases reduces the bond yields of firms whose bonds are eligible for central bank purchases. These firms substitute bank term loans with bond debt, thereby relaxing banks’ lending constraints: banks with low tier-1 ratios and high nonperforming loans increase lending to private (and profitable) firms, which experience a growth in investment. The credit reallocation increases banks’ risk-taking in corporate credit.
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What Does Peer-to-Peer Lending Evidence Say About the Risk-taking Channel of Monetary Policy?
Yiping Huang, Xiang Li, Chu Wang
Abstract
This paper uses loan application-level data from a Chinese peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.
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What Does Peer-to-Peer Lending Evidence Say About the Risk-taking Channel of Monetary Policy?
Yiping Huang, Xiang Li, Chu Wang
Abstract
This paper uses loan application-level data from a peer-to-peer lending platform to study the risk-taking channel of monetary policy. By employing a direct ex-ante measure of risk-taking and estimating the simultaneous equations of loan approval and loan amount, we are the first to provide quantitative evidence of the impact of monetary policy on the risk-taking of nonbank financial institution. We find that the search-for-yield is the main workhorse of the risk-taking effect, while we do not observe consistent findings of risk-shifting from the liquidity change. Monetary policy easing is associated with a higher probability of granting loans to risky borrowers and a greater riskiness of credit allocation, but these changes do not necessarily relate to a larger loan amount on average.
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A Factor-model Approach for Correlation Scenarios and Correlation Stress Testing
Natalie Packham, Fabian Wöbbeking
Journal of Banking and Finance,
April
2019
Abstract
In 2012, JPMorgan accumulated a USD 6.2 billion loss on a credit derivatives portfolio, the so-called “London Whale”, partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows for scenario-based stress testing of correlations. We derive a number of analytical results related to a portfolio of homogeneous assets. Using the concept of Mahalanobis distance, we show how to identify adverse scenarios of correlation risk. In addition, we demonstrate how correlation and volatility stress tests can be combined. As an example, we apply the factor-model approach to the “London Whale” portfolio and determine the value-at-risk impact from correlation changes. Since our findings are particularly relevant for large portfolios, where even small correlation changes can have a large impact, a further application would be to stress test portfolios of central counterparties, which are of systemically relevant size.
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Too Connected to Fail? Inferring Network Ties from Price Co-movements
Jakob Bosma, Michael Koetter, Michael Wedow
Journal of Business and Economic Statistics,
No. 1,
2019
Abstract
We use extreme value theory methods to infer conventionally unobservable connections between financial institutions from joint extreme movements in credit default swap spreads and equity returns. Estimated pairwise co-crash probabilities identify significant connections among up to 186 financial institutions prior to the crisis of 2007/2008. Financial institutions that were very central prior to the crisis were more likely to be bailed out during the crisis or receive the status of systemically important institutions. This result remains intact also after controlling for indicators of too-big-to-fail concerns, systemic, systematic, and idiosyncratic risks. Both credit default swap (CDS)-based and equity-based connections are significant predictors of bailouts. Supplementary materials for this article are available online.
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Banks Response to Higher Capital Requirements: Evidence from a Quasi-natural Experiment
Reint E. Gropp, Thomas Mosk, Steven Ongena, Carlo Wix
Review of Financial Studies,
No. 1,
2019
Abstract
We study the impact of higher capital requirements on banks’ balance sheets and their transmission to the real economy. The 2011 EBA capital exercise is an almost ideal quasi-natural experiment to identify this impact with a difference-in-differences matching estimator. We find that treated banks increase their capital ratios by reducing their risk-weighted assets, not by raising their levels of equity, consistent with debt overhang. Banks reduce lending to corporate and retail customers, resulting in lower asset, investment, and sales growth for firms obtaining a larger share of their bank credit from the treated banks.
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