We quantify disagreement about the economy with ex-ante measures of divergence of opinion among economic forecasters and investigate if economic disagreement has a significant impact on the cross-sectional pricing of individual stocks. We find a significant disagreement premium of 7.2% per...

By employing large panels of survey data for the UK economy, we aim at reviewing linear approaches for regularisation and dimension reduction combined with techniques from the machine learning literature, like Random Forests, Support Vector Regressions and Neural Networks for forecasting GDP...

This collection of papers analyzes the versatility and predictive power of survey expectations data in asset pricing and macroeconomic forecasting. The first paper, Using Sentiment Surveys to Predict GDP Growth and Stock Returns sheds new light on the question of whether or not sentiment...

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...

This paper proposes a two-state predictive regression model and shows that stock market 12-month return (TMR), the time-series momentum predictor of Moskowitz, Ooi, and Pedersen (2012), forecasts the aggregate stock market negatively in good times and positively in bad times. The out-of-sample...

Lagged GNP growth rates are poor forecasts of future GNP growth rates in postwar US data, leading to the impression that GNP is nearly a random walk. However, other variables, and especially the lagged consumption/GNP ratio, do forecast long-horizon GNP growth, and show that GNP has temporary...

This paper examines the behaviour of the demand for money in Greece during 1976:1-2000:4, a period that included many of the influences that cause money-demand instability. Two empirical methodologies, vector error correction (VEC) modelling and second-generation random coefficient (RC)...

Macroeconomic data is often noisy, contradictory and lagging. These limitations render the data difficult to integrate into a robust quantitative investment strategy that generates excess returns. This paper outlines a new approach to macro investing that removes these inherent limitations in...

We show that news stories contain information about economic linkages between firms and document that information diffuses slowly across linked stocks. Specifically, we identify linked stocks from co-mentions in news stories and find that linked stocks cross-predict one another's returns in the...

We examine the predictive effect of sentiment on the cross-section of stock returns across different economic states. The degree of mispricing and the subsequent price correction can be different between economic expansion and recession because of the limits of arbitrage and short sale...