Priyank Gandhi

Financial Market Misconduct and Public Enforcement: The Case of Libor Manipulation

Using comprehensive data on London Interbank Offer Rate (Libor) submissions from 2001 through 2012, we document systematic evidence consistent with banks manipulating Libor to profit from Libor related positions and, to a degree, to signal their creditworthiness during the distressed times for banks. The evidence is initially stronger for banks that were eventually sanctioned by the regulators and disappears for all banks post-2010 in the aftermath of Libor investigations. Our findings suggest that public enforcement, with the threat of large penalties and the loss of reputation, can be effective in deterring financial market misconduct.Using data on Libor submissions from 1999 to 2012, wend weak support for the hypothesis that banks manipulate submissions to appear less risky and strong support for the hypothesis that banks manipulate Libor to generate higher cash ows. Our results are stronger for the manipulation period as identied by regulators (January 2005 to May 2009), for currencies and maturities with substantial notional amounts of interest-rate derivatives outstanding, for European banks, and for banks that have already paidnes related to manipulation. We calculate the cumulative gains in bank market capitalization due to manipulation to be

The Relationship between Credit Growth and the Expected Returns of Bank Stocks

16 to

Using Annual Report Sentiment as a Proxy for Financial Distress in U.S. Banks

19 billion.

Treasury Yield Implied Volatility and Real Activity

I find that a 1% increase in aggregate bank credit growth implies that the excess returns of bank stocks over the next one year are lower by nearly 3%. Unlike most other forecasting relationships, credit growth tracks bank stock returns over the business cycle and explains nearly 14% of the variation in bank stock returns over a 1-year horizon. This effect is robust to the exclusion of data from the crisis years and to the inclusion of several popular forecasting variables used in the literature. Credit growth also predicts returns of investment banks and of bank-dependent firms but does not predict returns for any other asset class. I show that this predictive variation in returns reflects the representative agent’s rational response to a small time-varying probability of a tail event that impacts banks and bank-dependent firms. Consistent with this hypothesis I show that the predictive power, as measured by the absolute magnitude of the coefficient on credit growth and the adjusted-R2 at the the 1-year horizon, depends systematically on variables that regulate exposure to tail risk. Historically, the probability of a tail event increases in a recession, therefore this mechanism also explains the observed correlation between variation in aggregate bank credit level and business conditions.

On Identifying Commercial Banks in CRSP

abstractCurrent measures of bank distress find marginal value in predictive variables beyond a capital adequacy ratio and tend to miss extreme events impacting the entire sector. The authors advoca...

Reply to Amit Goyal’s Comment, 'No Size Anomalies in U.S. Bank Stock Returns'

We show that at-the-money implied volatility of options on futures of 5-year Treasury notes (Treasury ‘yield implied volatility’) predicts both the growth rate and volatility of gross domestic product, as well as of other macroeconomic variables, like industrial production, consumption, and employment. This predictability is robust to controlling for the term spread, credit spread, stock returns, stock market implied volatility, and several other variables that prior literature showed to predict macroeconomic activity. Our results indicate that Treasury yield implied volatility is a useful forward-looking state variable to characterize risks and opportunities in the macro economy.

Counterparty Credit Risk and the Credit Default Swap Market

This note presents the details regarding the definition of commercial banks in Gandhi and Lustig (2014). We also explore some alternative methods for identifying commercial banks in CRSP. Finally, we check if alternative definitions of commercial banks in CRSP affect the quantitative results in Gandhi and Lustig.

Size Anomalies in U.S. Bank Stock Returns

Amit Goyal wrote a comment on our paper (Gandhi and Lustig (2014)) which misrepresents our study of the size effects in bank stock returns. This note shows that the size anomalies in bank stock returns documented by Gandhi and Lustig are robust to experimental design and are mostly driven by the largest banks (not the smallest ones) in the top three percentiles of the size distribution.