We address whether analysts bias earnings forecast revisions and convey the bias using forecast revision consistency, i.e., the extent to which analyst reports with earnings forecast revisions include stock recommendation and target price revisions consistent in sign with the earnings forecast...

In this paper we address a challenging aspect that arises in the regulatory requirement of back-testing the accuracy of distributional forecasts. The latter are core to measurement and capitalization of counterparty risk for banks under the IMM (Internal Models Method). The problem is very...

To their credit, empirical legal scholars try to live up to the highest methodological standards from the social sciences. But these standards do not always match the legal research question. This paper focuses on normative legal argument based on empirical evidence. Whether there is a normative...

We propose a general simulation-based procedure for estimating quality of approximate policies in heterogeneous-agent equilibrium models, which allows to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future...

Standard equity valuation approaches (i.e., DDM, RIM, and DCF model) are derived under the assumption of ideal conditions, such as infinite payoffs and clean surplus accounting. Because these conditions are hardly ever met, we extend the standard approaches, based on the fundamental principle of...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which is consistent with nearly integrated regressors and...

Quantitative investment strategies are often selected from a broad class of candidate models estimated and tested on historical data. Standard statistical technique to prevent model overfitting such as out-sample back-testing turns out to be unreliable in the situation when selection is based on...