A large literature finds evidence that pricing kernels nonparametrically estimated from option prices and historical returns are not monotonically decreasing in market index returns. We argue that existing estimation methods are inconsistent and propose a new nonparametric estimator of the pricing kernel that reflects the information available to investors who set asset prices. In simulations, the estimator outperforms existing techniques. Our empirical estimates using S&P 500 index option data from 1996 to 2014 and FTSE 100 index option data from 2002 to 2014 suggest that the “pricing kernel puzzle” is due to flaws in existing estimators rather than a behavioral or economic phenomenon.

We use a random forest model to classify firms’ financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment.

A large literature finds evidence that pricing kernels nonparametrically estimated from option prices and historical returns are not monotonically decreasing in market index returns. We argue that existing estimation methods are inconsistent and propose a new nonparametric estimator of the pricing kernel that reflects the information available to investors who set asset prices. In simulations, the estimator outperforms existing techniques. Our empirical estimates using S&P 500 index option data from 1996 to 2014 and FTSE 100 index option data from 2002 to 2014 suggest that the “pricing kernel puzzle” is due to flaws in existing estimators rather than a behavioral or economic phenomenon. Received August 2, 2015; editorial decision April 15, 2017 by Editor Andrew Karolyi.

We show that a common component governs volatility dynamics across a wide range of traded equity factors. This “common factor volatility” (CFV) exists even among orthogonal factors. CFV occurs in both cash-flow and discount-rate components of factor returns and derives from market responses to fundamental news rather than underlying commonality in news volatility. Incorporating CFV improves factor volatility forecasts relative to models that include only own-factor volatility. CFV allows us to characterize stochastic discount factor (SDF) volatility dynamics in a very general sense and we show that many popular models imply SDFs with time-varying volatility that correlates strongly with CFV.