This paper suggests that changing risk conveys information useful to improve performance.

Using a latent variables approach, we estimate the dynamics of dividends and returns in a tractable present-value model with time-varying risks. Expected returns imply a similar return predictability as under homoskedasticity, while expected dividend growth is more persistent and explains a...

Conventional tests of present-value models over-reject the null of no predictability. In order to better account for the intrinsic probability of detecting predictive relations by chance alone, we develop a new nonparametric Monte Carlo testing method, which does not rely on distributional...

We study a new class of three-factor affine option pricing models with interdependent volatilitydynamics and a stochastic skewness component unrelated to volatility shocks. Theseproperties are useful in order (i) to model a term structure of implied volatility skews moreconsistent with the data...

A large literature studies the predictability of stock returns by other lagged nancialvariables in a predictive regression setting. A common feature of widely used testingprocedures is a failing robustness, which may lead to misleading conclusions determinedby the particular features of a small...

We introduce a new class of flexible and tractable matrix a±ne jump-diffusions (AJD) to modelmultivariate sources of financial risk. We first provide a complete transform analysis of this model class,which opens a range of new potential applications to, e.g., multivariate option pricing with...

This paper analyzes the relation between correlation risk and the cross-section of hedge fund returns.Legal framework and investment mandate imply that hedge funds can be severely exposed tocorrelation risk: Hedge funds ability to enter long-short positions can be useful to reduce marketbeta,...