This paper finds evidence that stock returns vary with the physical climate change exposure of firms in a predictable manner. We construct measures of exposures to physical climate changes at the firm level, and find that firms with high climate change exposures experience lower future...

We use a sample of option prices, and the method of Bakshi, Kapadia and Madan (2003), to estimate the ex ante higher moments of the underlying individual securities' risk-neutral returns distribution. We find that individual securities' volatility, skewness, and kurtosis are strongly related to...

In this paper, we develop a novel model to forecast the volatility of S&P 500 futures returns by considering measures of limits to arbitrage. When arbitrageurs face constraints on their trading strategies, option prices can become disconnected from fundamentals, resulting in a distortion that...

We derive a model-free option-based formula to estimate the contribution of market frictions to expected returns (CFER) within an asset pricing setting. We estimate CFER for the U.S. optionable stocks. We document that CFER is sizable, it predicts stock returns and it subsumes the effect of...

Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

We re-visit a puzzling result that in U.S. post-WW II data the dividend price ratio can predict aggregate returns but not dividend growth. We find that predictive regressions are sensitive to the method used to aggregate firm-level data. Using value weighted firm-level data we find strong...

We combine self-collected historical data from 1867 to 1907 with CRSP data from 1926 to 2012, to examine the risk and return over the past 140 years of one of the most popular mechanical trading strategies — momentum. We find that momentum has earned abnormally high risk-adjusted returns — a...

This paper examines the volatility and covariance dynamics of cash and futures contracts that underlie the Optimal Hedge Ratio (OHR) across different hedging time horizons. We examine whether hedge ratios calculated over a short term hedging horizon can be scaled and successfully applied to...

Finance researchers keep producing increasingly complex and computationally-intensive models of stock returns. Separately, professional analysts forecast stock returns daily for their clients. Are the sophisticated methods of researchers achieving better forecasts or are we better off relying on...