This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive...

We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are based on averages of past futures returns, normalized by their volatility. We test these strategies on a universe of 64 liquid futures contracts and show that RAMOM strategies...

We consider a market where traders have asymmetric information regarding the distribution of asset return and study price discovery of derivatives. The informed trader has private information regarding arbitrary higher moments of asset return, such as volatility or skewness, and exploits her...

We derive closed form expressions for equilibrium asset prices and liquidity in an economy populated by a finite number of large, strategic, risk averse investors. The model allows for arbitrary risk preferences, any number of assets, and an arbitrary distribution of asset payoffs. In...

We show empirically that survey-based measures of expected inflation are significant and strong predictors of future aggregate stock returns in several industrialized countries both in-sample and out-of-sample. By empirically discriminating between competing sources of this return predictability...

A sizeable literature reports that financial market analysts and forecasters herd for reputational reasons. Using new data from a large survey of professional forecasters' expectations about stock market movements, we find strong evidence that the expected average of all forecasters' forecasts...

A major obstacle for research in international asset pricing and corporate finance has been a lack of reliable and publicly available data on international common risk factors and portfolios. To address this gap, we provide a step-by-step description of how appropriately screened data from...