Demand is growing for a better understanding of how assets are priced in countries outside of the U.S. While financial data are available for many firms world-wide, it is important to have a reliable and replicable method of constructing high-quality systematic risk factors from these data. This...

Using data on 65,000 stocks from 23 countries, the authors re-evaluate the performance of the Fama-French (2015) factors in global markets. The results provide convincing evidence that the value, profitability, and investment factors are far less reliable than commonly thought. Their performance...

We examine the characteristics and the quality of equity data from Thomson Reuters Datastream (Datastream) to evaluate, whether Datastream can be used as the primary data source for academic studies on the German stock market. We document market coverage issues in Datastream before 1990....

Demand is growing for a better understanding of how assets are priced in countries outside of the U.S. While financial data are available for many firms world-wide, it is important to have a reliable and replicable method of constructing high-quality systematic risk factors from these data. This...

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...

In recent decades, low-risk stocks provide higher returns than riskier stocks. This contradicts a well-established market theory of higher risk-higher return. The distorted relationship between risk and return over the last few years has been attributed to factors such as the risk aversion...

This paper examines the effects of structural change, long-term TFP trend and marginal return to capital on China's economic growth, comparing such effects with those in the other East Asian economies. Our empirical results show that China's TFP converges to a higher level, and the marginal...

We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness among financial asset returns and volatilities. We also show that variance decompositions define weighted, directed networks, so...

We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency...

We investigate predictive abilities of nonlinear models for stock returns when density forecasts are evaluated and compared instead of the conditional mean point forecasts. The aim of this paper is to show whether the in-sample evidence of strong nonlinearity in mean may be exploited for...