Most central banks effect changes to their target or policy rate in discrete increments (e.g., multiples of 0.25%) following public announcements on scheduled dates. Still, for most applications, researchers rely on the assumption that the policy rate changes linearly with economic conditions...

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...

Through extending a standard Grossman and Stiglitz (1980) noisy rational expectations economy by a heterogeneous signal structure with signal-specific differences in uncertainty, we show that price momentum as well as reversal are not intrinsically at odds with rational behavior. Differences in...

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 introduce an asymptotic expansion for forward start options in a multi-factor local-stochastic volatility model. We derive explicit approximation formulas for the so-called forward implied volatility which can be useful to price complex path-dependent options, as cliquets. The expansion...

Recent evidence indicates that market model alphas are stronger predictors of mutual fund flows than alphas with other models. Berk and van Binsbergen (2016) claim that this evidence indicates CAPM is the best asset pricing model but Barber, Huang and Odean (2016) (BHO) claim it is evidence...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

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...

We study the out-of-sample and post-publication return-predictability of 97 variables that academic studies show to predict cross-sectional stock returns. Portfolio returns are 26% lower out-of-sample and 58% lower post-publication. The out-of-sample decline is an upper bound estimate of data...

I argue that academic research often inadequately accounts for alpha decay. As an anomaly's alpha (i.e., the risk-adjusted expected excess return) and realized returns are negatively related, alpha decay coincides with positive realized returns. If the alpha decays at publication, observers may...