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We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, in some cases doubling the performance of leading regression-based strategies from the literature. We identify the best-performing methods (trees and neural networks) and trace their predictive gains to allowing nonlinear predictor interactions missed by other methods. All methods agree on the same set of dominant predictive signals, a set that includes variations on momentum, liquidity, and volatility.

Given the positive bias toward attractive people in society, online sellers are justifiably apprehensive about perceptions of their profile pictures. Although the existing literature emphasizes the “beauty premium” and the “ugliness penalty,” the current studies of seller profile pictures on customer-to-customer e-commerce platforms find a U-shaped relationship between facial attractiveness and product sales (i.e., both beauty and ugliness premiums and, thus, a “plainness penalty”). By analyzing two large data sets, the authors find that both attractive and unattractive people sell significantly more than plain-looking people. Two online experiments reveal that attractive sellers enjoy greater source credibility due to perceived sociability and competence, whereas unattractive sellers are considered more believable on the basis of their perceived competence. While a beauty premium is apparent for appearance-relevant products, an ugliness premium is more pronounced for expertise-relevant products and for female consumers evaluating male sellers. These findings highlight the influence of facial appearance as a key vehicle for impression formation in online platforms and its complex effects in e-commerce and marketing.

Lou and Shu decompose Amihud’s illiquidity measure (ILLIQ) proposing that its component, the average of inverse dollar trading volume (IDVOL), is sufficient to explain the pricing of illiquidity. Their decomposition misses a component of ILLIQ that is related to illiquidity. We find that this component affects stock returns significantly, both in the crosssection and in time-series. We show that the ILLIQ premium is significantly positive after controlling for mispricing, sentiment, and seasonality. In addition, the aggregate market ILLIQ outperforms market IDVOL in estimating the effect of market illiquidity shocks on realized stock returns.

I derive a lower bound on the equity premium in terms of a volatility index, SVIX, that can be calculated from index option prices. The bound implies that the equity premium is extremely volatile and that it rose above 20% at the height of the crisis in 2008. The time-series average of the lower bound is about 5%, suggesting that the bound may be approximately tight. I run predictive regressions and find that this hypothesis is not rejected by the data, so I use the SVIX index as a proxy for the equity premium and argue that the high equity premia available at times of stress largely reflect high expected returns over the very short run. I also provide a measure of the probability of a market crash, and introduce simple variance swaps, tradable contracts based on SVIX that are robust alternatives to variance swaps.

Macro-finance theory implies that trend inflation and the equilibrium real interest rate are fundamental determinants of the yield curve. However, empirical models of the term structure of interest rates generally assume that these fundamentals are constant. We show that accounting for time variation in these underlying long-run trends is crucial for understanding the dynamics of Treasury yields and predicting excess bond returns. We introduce a new arbitrage-free model that captures the key role that long-run trends play in determining interest rates. The model also provides new, more plausible estimates of the term premium and accurate out-of-sample yield forecasts.

The uncovered interest parity puzzle concerns the empirical regularity that high interest rate countries tend to have high expected returns on short term deposits. A separate puzzle is that high real interest rate countries tend to have currencies that are stronger than can be accounted for by the path of expected real interest differentials under uncovered interest parity. These two findings have apparently contradictory implications for the relationship of the foreign-exchange risk premium and interest-rate differentials. We document these puzzles, and show that existing models appear unable to account for both. A model that might reconcile the findings is discussed.

This article examines the pricing of a firm’s carbon risk in the corporate bond market. Contrary to the “carbon risk premium” hypothesis, bonds of more carbon-intensive firms earn significantly lower returns. This effect cannot be explained by a comprehensive list of bond characteristics and exposure to known risk factors. Investigating sources of the low carbon alpha, we find the underperformance of bonds issued by carbon-intensive firms cannot be fully explained by divestment from institutional investors. Instead, our evidence is most consistent with investor underreaction to the predictability of carbon intensity for firm cash-flow news, creditworthiness, and environmental incidents.

We document large average excess returns on U.S. equities in anticipation of monetary policy decisions made at scheduled meetings of the Federal Open Market Committee (FOMC) in the past few decades. These pre-FOMC returns have increased over time and account for sizable fractions of total annual realized stock returns. While other major international equity indices experienced similar pre-FOMC returns, we find no such effect in U.S. Treasury securities and money market futures. Other major U.S. macroeconomic news announcements also do not give rise to preannouncement excess equity returns. We discuss challenges in explaining these returns with standard asset pricing theory.

Fixing the investment horizon, the returns to currency carry trades decrease as the maturity of the foreign bonds increases. Across developed countries, the local currency term premia, which increase with the maturity of the bonds, offset the currency risk premia. Similarly, in the time-series, the predictability of foreign bond returns in dollars declines with the bonds’ maturities. Leading no-arbitrage models in international finance do not match the downward term structure of currency carry trade risk premia. We derive a simple preference-free condition that no-arbitrage models need to reproduce in the absence of carry trade risk premia on long-term bonds.

A consensus has recently emerged that variables beyond the level, slope, and curvature of the yield curve can help predict bond returns. This paper shows that the statistical tests underlying this evidence are subject to serious small-sample distortions. We propose more robust tests, including a novel bootstrap procedure specifically designed to test the spanning hypothesis. We revisit the analysis in six published studies and find that the evidence against the spanning hypothesis is much weaker than it originally appeared. Our results pose a serious challenge to the prevailing consensus.