In this research I empirically study the effects of information acquisition by investors or traders on analysts' forecast bias. Based on the theoretical literature on sell-side analysts, I argue that forecast bias is correlated to investors' information gathering, in two opposite directions. On...

Noisy markets need extensive descriptions that are noisy themselves, such as deep regression trees that capture many data-local nonlinear anomalies and that do not require arbitrary weighting schemes like traditional linear multifactor models often do. Simple tools allow extraction of general...

We study equity premium out-of-sample predictability by extracting the information contained in a high number of macroeconomic predictors via large dimensional factor models. We compare the well known factor model with a static representation of the common components with a more general model...

We seek fundamental risks from news text. Conceptually, news is closely related to the idea of systematic risk, in particular the "state variables" in the ICAPM. News captures investors' concerns about future investment opportunities, and hence drives the current pricing kernel. This paper...

This paper develops a rare disaster asset pricing model with EZ preferences, in particular including the impact of macroeconomic consequences of the COVID-19 disaster. I estimate the probability of disaster, disaster states, and the duration of disaster to shed light on the frequency and size of...

Purpose: The main aim of this research was to discuss the relationship between the patents and the performance of listed companies, more particularly, to find out whether China patent's claim impacted on China listed company's stock return rate or not. It was because the claim played the most...

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...

We study regime-specific systematic comovement between two large panels of variables that exhibit an approximate factor structure. Within each panel we identify threshold-type regimes through shifts in the factor loadings. For the resulting regimes, and with regard to the relation between any...

In this paper, we build estimation error in mean returns into the mean-variance (MV) portfolio theory under the assumption that returns on individual assets follow a joint normal distribution. We derive the conditional sampling distribution of the MV portfolio along with its mean and risk return...