Working Papers
Inferring Intermediary Risk Exposure from Trade (with Weiling Liu)
We propose a novel measure of intermediary risk exposure based on the fraction of interdealer trade. Intuitively, when aggregate risk exposure rises, dealers trade more with each other to redistribute customer orders. In the U.S. Treasury market, our measure has a 0.72 correlation with dealers' interest rate Value at Risk, and a one standard deviation increase in our measure forecasts a 1.8 percentage point higher annual excess return on a five-year bond. Extending our analysis to the FX market, a one standard deviation increase in our measure forecasts a 3.2 percentage point higher annual return on carry trades.
Consumption-Based Asset Pricing When Consumers Make Mistakes
I analyze the implications of allowing consumers to make mistakes on the risk-return relationships predicted by consumption-based asset pricing models. I allow for consumption mistakes using a model in which a portfolio manager selects a portfolio on a consumer's behalf. The consumer has an arbitrary consumption policy which could reflect a wide range of mistakes. In the case of power utility, expected returns may no longer depend on exposure to single-period consumption shocks, but will robustly depend on exposure to long-run consumption and expected return shocks. My results generalize and I show that expected return shocks are empirically important.
Other Work
Evaluating Banks' Value at Risk Models During the COVID-19 Crisis (with Dennis Mawhirter)
We examine how banks' Value at Risk (VaR) models performed during the COVID-19 crisis using regulatory trading desk-level data. We first evaluate whether banks' VaR models were incomplete by checking whether various factors predict backtesting exceptions. Backtesting exceptions from the past 10 business days and the level of the VIX forecast future exceptions. Predictability from past backtesting exceptions rises during the COVID-19 crisis relative to 2019. We don't find any single market factor that related to contemporaneous backtesting exceptions. These results hold both in the aggregate and across asset classes.
Older Working Papers
Are the Borrowing Costs of Large Financial Firms Unusual? (with Javed Ahmed and Rebecca Zarutskie)
Estimates of investor expectations of government support of large financial firms are often based on large financial firms' lower borrowing costs relative to smaller financial firms. Using pricing data on credit default swaps (CDS) and corporate bonds over the period 2004 to 2013, however, we find that the CDS and bond spreads of financial firms are no more sensitive to borrower size than the spreads of non-financial firms. Outside of the financial crisis period, spreads are more sensitive to borrower size in several non-financial industries. We find that size-related differences in spreads are partially driven by higher liquidity and recovery rates of larger borrowers. Prior to the financial crisis, we also find that financial firms exhibited generally lower spreads that were less sensitive to size than spreads for several other industries. Our results suggest that estimates of implicit government guarantees to financial firms may overemphasize size-related borrowing cost differentials. However, our analysis also suggests that, prior to the financial crisis, investor expectations of government support, or generally reduced risk perceptions, may have reduced borrowing costs for the financial industry, as a whole.
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