Welcome to my website! I am a sixth year PhD candidate in Financial Economics at Duke University's Fuqua School of Business. 

My interests are in asset pricing, nominal rigidities, corporate debt, and macro-finance. 

I am on the 2023/2024 job market.

You can reach me at andrew.kane@duke.edu.

Download my curriculum vitae here.

Working Papers

Product Price Change Timing and Stock Returns

Firms with unresponsive product prices are risky. Firms that sell products whose prices are rigid in the face of substantial mispricing have average equity returns 4% higher than firms with more responsive product prices. This premium is not explained by unconditional price change frequency or a variety of other firm characteristics. I build a multisector model in which firms face heterogeneous nominal rigidities. Some firms change prices when doing so raises their cashflows substantially. Other firms are unable to time their price changes as effectively. When inflation is high, firms with unresponsive pricing have large cashflow losses, making investors demand a premium to hold these firms' equity. The model predicts the failure of the CAPM to account for differences in equity returns in the sample period.

Presented at Northern Finance Association (2023), Midwest Finance Association (2023), Federal Reserve Board (2023), Duke Macroeconomics Breakfast (2023), Fuqua Finance Brownbag (2023), USC Marshall PhD Conference in Finance (2022), Trans-Atlantic Doctoral Conference (2022), Macro Finance Research Program Summer Session Poster Presentation (2022), Inter-Finance PhD Seminar (2022)

Marking to Market Corporate Debt with Lorenzo Bretscher, Peter Feldhütter, and Lukas Schmid

Models of capital structure and credit risk make predictions about market valuations of debt, but are routinely tested on the basis of book debt from common data sources. In this paper, we propose to close this gap. We construct a rich data set on firm level debt market valuations by carefully matching data on corporate bond and loan secondary market transactions. We document significant discrepancies between market and book values, especially for distressed firms. We use our dataset to i) provide novel rules of thumb on how to adjust leverage and unlever returns using standard datasets, and ii) to revisit a number of prominent empirical patterns involving corporate debt. Using a market-based measure of Tobin's Q, we find little evidence for investment cash-flow sensitivity in our data. We find that using market debt values significantly improves default prediction, and do not detect a credit spread puzzle. In asset pricing tests, we find a leverage premium, but no evidence for a value premium after controlling for market leverage. Moreover, a novel measure of financial distress, namely market-to-book debt, predicts stock returns positively in the cross-section, inconsistent with a financial distress puzzle. 

Presented at European Finance Association Conference (2021), FIRS (2021), CICF (2021), Duke Finance Brownbag (2021), WFA* (2021), SFS Cavalcade* (2021), MFA* (2021), Adam Smith Workshop* (2021), ASU Sonoran Winter Finance Conference* (2021), 

Winner of the Jacob Gold & Associates Best Paper Award, ASU Sonoran Winter Finance Conference 2021.

Are US Monetary Surprises Surprising? Evidence from Global Markets with Sergey Sarkisyan and Tasaneeya Viratyosin

We show that FOMC announcement surprises are predicted by preceding ECB monetary policy announcement surprises. Specifically, a 1 p.p. ECB monetary policy surprise predicts a subsequent 0.25 p.p. FOMC surprise. We find little evidence that this predictability is due to the Fed using the ECB to update forecasts on the US economy or to the ECB releasing new information pertinent to near-term US macroeconomic conditions. Instead, we propose that the Fed responds to non-US economic conditions more strongly than investors expect. We find that the component of FOMC surprises predicted by ECB surprises has significant effects on the US economy. Our results suggest that the Fed’s response to non-US news is an important facet of monetary policy. 

Midwest Finance Association* (2023), MFA Doctoral Symposium* (2023), Trans-Atlantic Doctoral Conference (2023), Inter-Finance PhD Seminar (2023)

A New Test for an Old Puzzle with Lorenzo Bretscher, Peter Feldhütter, and Lukas Schmid

Traditional tests of the credit spread puzzle rely on default rates, recovery rates, and Sharpe ratios, all of which are measured with imprecision. We show that the difference between the Sharpe ratio of debt returns and the Sharpe ratio of equity returns provides a more precise test of the credit spread puzzle given the available sample sizes. After controlling for the unexpected decline in interest rates beginning in the 1990s, Sharpe ratios of equity and bonds are nearly identical, consistent with traditional default prediction models and inconsistent with a credit spread puzzle. However, loan returns have higher Sharpe ratios than bond returns, indicating a new avenue for future research.

Rules of Thumb for Market Leverage with Lorenzo Bretscher, Peter Feldhütter, and Lukas Schmid

Firm market leverage and asset return volatility are key inputs for a variety of models in the finance literature. However, market values of debt are not widely available and costly to obtain, forcing researchers to use publicly available book values as a substitute. Using a LASSO-based feature selection algorithm, we construct rules of thumb to approximate market leverage and asset volatility with publicly available data. When approximating market leverage in firms with low credit ratings, our rules of thumb reduce mean squared error by 19% out of sample compared to book-based variables. For asset volatility, the rules of thumb reduce mean squared error by 43% for firms with low credit ratings. We demonstrate the usefulness of our rules of thumb for default prediction and unlevering equity returns.

*Indicates presentation by coauthor

Work in Progress

What Causes State Dependence? Evidence from Scanner Data with Nuno Clara

Product Quality and Stock Returns with Joel David and Lukas Schmid


A New Analysis Strategy for Designs with Complex Aliasing with Abhyuday Mandal. Published in The American Statistician, 74 (3) 274-281.