The slope coefficient estimator in predictive regressions for stock returns is biased by a lagged stochastic regressor. There is also a spurious regression if the underlying expected return is highly persistent. This paper studies how the interactions between the two biases affect inferences...

We evaluate the performance of several linear and nonlinear machine learning models in forecasting the realized volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a dataset which includes past values of the RV and additional...

This study examines the predictive power of comprehensive income and its individual components within the homogenous institutional setting of German IFRS firms. The results could be relevant for the standard setters IASB and FASB and their joint project “Financial Statement Presentation”. We...

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...