We introduce a new measure of stock misevaluation, 𝑄, which is consistent with the Gordon growth model for firm valuation. In our empirical application, we use 𝑄 to relate analyst forecasts to stock returns and measure the profitability of investment strategies that rely on information in...

This study examines the stock-price reactions to analyst forecast revisions around earnings announcements to test whether pre-announcement forecasts reflect analysts' private information or piggybacking on confounding events and news. We find that management earnings forecasts influence the...

The purpose of this paper is to determine whether time weighted consensus estimates offer a more effective method for predicting company actual EPS figures than simple mean or median analysis. The study aims to construct a more comprehensive earnings forecast signal using analyst earnings...

In the prediction of quantiles of daily Standard&Poor’s 500 (S&P 500) returns we consider how to use high-frequency 5-minute data. We examine methods that incorporate the high frequency information either indirectly, through combining forecasts (using forecasts generated from returns sampled...

This article aims to highlight the degree of suitability of theinformation issued in the annual report with the conception ofthe usefulness of 49 volunteers and forecast information byTunisian financial analysts. Our questionnaire with 50 financialTunisian analysts aims to analyze the degree of...

This paper applies linear and neural network-based "thick" models for forecasting inflation based on Phillips-curve formulations in the USA, Japan and the euro area. Thick models represent "trimmed mean" forecasts from several neural network models. They outperform the best performing linear...