Hitesh Doshi

Precarious Politics and Return Volatility

We examine how local and global political risks affect industry return volatility. Our central premise is that some industries are more sensitive to political events than others. We find that industries that are more dependent on trade, contract enforcement, and labor exhibit greater return volatility when local political risks are higher. Political uncertainty in countries of trading partners of trade-dependent industries similarly results in greater volatility. Volatility decomposition results indicate that while systematic volatility is associated with domestic political uncertainty, global political risks translate into larger idiosyncratic volatility. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Pricing Credit Default Swaps with Observable Covariates

Observable covariates are useful for predicting default, but several studies question their value for explaining credit spreads. We introduce a discrete-time no-arbitrage model with observable covariates, which allows for a closed-form solution for the value of credit default swaps (CDS). The default intensity is a quadratic function of the covariates, specified such that it is always positive. The model yields economically plausible results in terms of fit, the economic impact of the covariates, and the prices of risk. Risk premiums are large and account for a smaller percentage of spreads for firms with lower credit quality. Macroeconomic and firm-specific information can explain most of the variation in CDS spreads over time and across firms, even with a parsimonious specification. These findings resolve the existing disconnect in the literature regarding the value of observable covariates for credit risk pricing and default prediction. The Author 2013. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Managerial Activeness and Mutual Fund Performance

A closet indexer is more likely to meet a value-weighted investment benchmark by value-weighting the portfolio. Following this intuition, we introduce a simple measure of active management, the absolute difference between the value weights and the actual weights held by a fund, averaged across its holdings. This proxy captures managerial skill: Active funds outperform passive ones by 2.5% annually. Compared to known measures of skill, our proxy robustly predicts fund flows, asset growth, factor-adjusted performance, and value added. Its predictive ability is orthogonal to that of other measures and is robust to controlling for volatility timing, past performance, and style.

Pricing Structured Products with Economic Covariates

Financial institutions with exposure to structured products need to value these securities and undertake scenario analysis, specified in terms of changes in economic variables. We introduce a top-down no-arbitrage model for structured products, with losses governed by Cox processes whose intensities depend on economic variables. We estimate the model using CDO data and find that spreads decrease with higher interest rates and stock market returns, and increase with the VIX. The VIX is the primary determinant of variation in tranche spreads. Model-implied risk premiums, probabilities of tranche losses and values-at-risk increase substantially during the financial crisis.

Macroeconomic Determinants of the Term Structure: Long-Run and Short-Run Dynamics

We propose a no-arbitrage term structure model with a Taylor rule and two macroeconomic variables, real activity growth and inflation, that each contain long-run and short-run components. Variance decompositions indicate that the impact of macroeconomic variables on the term structure differs from existing models. For short maturities, inflation is relatively more important than real activity growth at short forecast horizons. For longer maturity yields, the long-run component of inflation explains most of the long-horizon forecast variance, but real activity growth matters for short forecast horizons. Unlike existing macro models, the model implies plausible term premia and expectations of short rates. The long-run components also improve the prediction of bond excess returns relative to information in the yield curve and macro variables. Measures of in-sample and out-of-sample fit confirm the benefits of allowing for long- and short-run components.

Information in the Term Structure: A Forecasting Perspective

Recent advances in the term structure literature focus on model specification and estimation. While forecasting is considered important, it is not explicitly taken into account at the estimation stage. We estimate affine term structure models by aligning in-sample and out-of-sample loss functions. Aligning loss functions provides substantial improvements in forecasting performance, especially for long forecast horizons. The resulting parameter estimates imply factors that differ from traditional term structure factors, especially for curvature. This suggests that the improvement in fit results from identification of the third factor, which captures information hidden to conventional loss functions, consistent with Cochrane and Piazzesi (2005).

Leverage and the Cross-Section of Equity Returns

Building on the theoretical asset pricing literature, we examine the role of market risk and the size, book-to-market (BTM), and volatility anomalies in the cross-section of unlevered equity returns. Compared with levered (stock) returns, the unlevered market beta plays a more important role in explaining the cross-section of unlevered equity returns, even when we control for size and BTM. The size effect is weakened, while the value premium and the volatility puzzle virtually disappear for unlevered returns. We show that leverage induces heteroskedasticity in returns. Unlevering returns removes this pattern, which is otherwise difficult to address by controlling for leverage in regressions.