A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...

This paper empirically examines the theoretically ambivalent relationship between socially responsible investing (SRI) and stock performance. It extends the existing literature by considering both the US and the entire European stock markets as well as by using consistent world-wide corporate...

Assessments of investors' risk appetite/aversion stance via indicators often yields results which seem unsatisfactory (see e.g. Illing and Aaron (2005)). Understanding how such indicators work therefore seems essential for further improvements. The present paper seeks to contribute to this...

Technical trading strategies assume that past changes in prices help predict future changes. This makes sense if the past price trend reflects fundamental information that has not yet been fully incorporated in the current price. However, if the past price trend only reflects temporary pricing...

We integrate liquidity risk measured by the weighted spread into a Value-at-Risk (VaR) framework. The weighted spread measure extracts liquidity costs by order size from the limit order book. We show that it is precise from a risk perspective in a wide range of clearly defined situations. Using...

We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock's hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...

A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....

Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...