Benchmark finance and macroeconomic models appear to deliver conflicting estimates of the natural rate and bond risk premia. This natural rate puzzle applies not only in the U.S. but across many advanced economies. We use a unified no-arbitrage macro- finance model with two trend factors to...

We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

Cross-sectional forecasts of conservative and optimistic biases in analyst earnings estimates predict a stock's future returns, especially for firms that are hard to value. Trading strategies--whether based on the component of analyst bias that is correlated with major return anomalies or the...

The historical returns on equity index options are well known to be strikingly negative. That is typically explained either by investors having convex marginal utility over stock returns (e.g. crash/variance aversion) or by intermediaries demanding a premium for hedging risk. This paper examines...

This paper reviews recent developments in macro and finance on the relationship between financial risk and the real economy. We focus on three specific topics: the term structure of uncertainty, time variation - and specifically the long-term decline - in the variance risk premium, and time...

We use arbitrage activity in equity, fixed income, and foreign exchange markets to characterize the frictions and constraints facing intermediaries. The average pairwise correlation between the 29 arbitrage spreads that we study is 21%. These low correlations are inconsistent with canonical...

For investors, gold is an asset without a yield that is attractive in times of low and negative real interest rates. Gold also has an embedded put option because investors can sell it to those who value its use as jewelry or as a productive input. This paper presents an approach for pricing gold...

We use a large cross-section of equity returns to estimate a rich affine model of equity prices, dividends, returns and their dynamics. Using the model, we price dividend strips of the aggregate market index, as well as any other well-diversified equity portfolio. We do not use any dividend...

Characteristic-based factors embed large unpriced components that depress Sharpe ratios and deviate from the mean-variance efficient (MVE) frontier. We discuss how to decompose tradable factor returns into priced (MVE) and unpriced components, showing that hedging unpriced variation realigns...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...