​​​​The Low Energy Investor: Energy Risks, Investments and Stock Returns

We develop a new approach to determine investors' risk compensations for all distributional moments of a security. Using the concept of entropy, a summary of all moments of a risky security, we derive the exact link between expected returns and their compensation for entropy risk. Entropy risk premium (ERP), the difference of entropy under the physical and risk-neutral measures, indicates the cost to financially hedge against changes in all assets' risks. We find that ERP carries significant predictive power for the cross-section of commodity returns even after removing its variance and skewness risk components.

Publications

Working Papers

Willingness to pay and default uncertainty

We provide novel evidence that equity investors react to currency shocks with a delay. Using the cross-section of currency returns and the relative presence of U.S. multinational firms in foreign economies, we compute a foreign operations related exchange shock (FOREXS) measure. We find FOREXS to predict firms' future cash flows and stock returns, driving much of the previously documented underreaction to foreign information. A strategy that buys stocks with high FOREXS and shorts stocks with low FOREXS yields a 6.74% annualized abnormal return. We show that the predictive power comes from incomplete hedging by the firms and limited attention by the investors. Our results thus highlight the important role of investor attention in facilitating information transmission across asset classes.

We show that increasing energy risks endogenously decrease firms' investments, impacting expected returns. We empirically confirm this hypothesis in the cross-section of firms' capital expenditures and stock prices. We find that firms' exposure to energy risks differs from their exposure to crude oil returns or volatility, that not all energy risks are alike to investors, and that the negative comovement between energy risks and investments in the data is consistent with investors' specific preferences on uncertainty resolution. We document the important effects of information flows between partially segmented markets, as investors use relevant information from the commodity market to rebalance their equity portfolios.

We develop a dynamic production-based model and introduce a novel channel showing that cash-flow hedging by firms reduces asymmetry in their future stock return distribution, that is, moves the return distribution closer to normal. We empirically test the theoretical implications of the model using hand-collected hedging data from the oil and gas industry along with estimated option-implied moments. Consistent with the predictions of the model, firm-level hedging reduces return variance, excess negative skewness and excess kurtosis. We find this pull-to-normality effect of hedging to be stronger among firms with small size, high leverage, high rollover-risk, low profitability and low market-to-book ratios.

We specify and estimate a no-arbitrage model for sovereign CDS contracts in which countries’ default intensities depend on economic and financial indicators. To facilitate identification and to distinguish the importance of local and global covariates, we estimate a model with three global and four local covariates using CDS spreads for five maturities and twenty-five countries. The model provides a good fit. The impact of the economic and financial variables on spreads is consistent with economic intuition, and substantially varies across countries and over time. Estimated risk premiums are highly variable and peak during the 2008 financial crisis for most countries.

Competition and credit risk

The entropy risk premium of the equity risk premium

We study the implications of financial frictions for the distribution and dynamics of lending spreads. These spreads are determined endogenously by the interaction between lenders and borrowers. Small shocks to the distribution of borrowers' prospects amplify through the economy, generating feedback effects on spreads. The model captures the joint dynamics of economic and financial variables observed in the data. Increased uncertainty about borrowers' prospects increases default rates and lending spreads, and decreases total lending. The model matches the historical averages for economic indicators as well as the level and persistence of lending spreads, but it generates excess volatility of spreads.

Work in Progress

​​​​​​​​Digesting FOREXS (with Joon Woo Bae and Zhi Da)

​​​​​​​​​The Normal Firm: Corporate Hedging and the Distribution of Stock Returns (with Hitesh Doshi and Praveen Kumar)

Financial Frictions and Loan Spreads, Revise and Resubmit, Journal of Financial and Quantitative Analysis

​​​​​​​​Never a Dull Moment: Entropy Risk in Commodity Markets (with Fousseni Chabi-Yo and Hitesh Doshi), Revise and Resubmit, Review of Asset Pricing Studies