In our approach, the conditional expectation of asset return quantities, under the real-world probability measure, can be expressed as a linear combination of the prices of the risk-free bond, the asset, and options on the asset. The method is free of distributional assumptions, and we use it to...

This paper proposes an approach that associates the risk-neutral probability measure with option prices and then computes the expectation of quantities under the real world probability measure, exploiting the form of the stochastic discount factor. This approach deviates from foundational...

Using a comprehensive database of corporate news, we examine how bond mutual funds trade on the sentiment of news releases. We find that bond funds trade against the direction of news sentiment (e.g., selling after good news about a firm). The results are more pronounced in bonds that lie within...

The VIX futures curve is most often in contango but displays backwardation during unfavorable market conditions. We construct an explanation based on the notion of stochastic orders of volatility uncertainty – meaning that investors view short-dated volatility uncertainty as being less likely...

The structural uncertainty model with Bayesian learning, advanced by Weitzman (AER 2007), provides a framework for gauging the effect of structural uncertainty on asset prices and risk premiums. This paper provides an operational version of this approach that incorporates realistic priors about...

This paper presents an option positioning that allows us to infer forward variances from option portfolios. The forward variances we construct from equity index options help to predict (i) growth in measures of real economic activity, (ii) Treasury bill returns, (iii) stock market returns, and...

We develop a new solution method for a broad class of discrete-time dynamic portfolio choice problems. The method efficiently approximates conditional expectations of the value function by using (i) a decomposition of the state variables into a component observable by the investor and a...

We propose and analyze a new nonlinear time series model based on local mixtures of linear regressions, referred to as experts, with thick-tailed disturbances. The mean function of each expert is an affine function of covariates that may include lags of the dependent variable and/or lags of...

This article presents evidence on the quality of Taylor series approximations to expected utility. To provide a transparent assessment in a broader setting, we assume that log portfolio returns follow a Gram--Charlier distribution that incorporates skewness and excess kurtosis and consider an...