Die vorliegende Arbeit hat zwei wesentliche Ziele. Auf der einen Seite soll sie existierende Konzepte zum systematischen Faktorinvestieren erweitern, mögliche Problemstellungen aufdecken und Verbesserungen vorschlagen. Zweitens, untersucht diese Arbeit eine neue Form von FinTech Innovationen:...

In this paper, we document the importance of memory in machine learning (ML)-based models relying on firm characteristics for asset pricing. We find that predictive algorithms perform best when they are trained on long samples, with long-term returns as dependent variables. In addition, we...

In this paper, we document the importance of memory in machine learning (ML)-based models relying on firm characteristics for asset pricing. We come to three empirical conclusions. First, the pure out-of-sample fit of the models is often poor: we find that most R^2 measures are negative,...

In this article, we quantify the demand for sustainability at the sovereign level. We do so by estimating a longitudinal model, at the issue level, that captures net demand in sovereign ESG factors for both equity and fixed income markets. In spite of the surging interest in ethical investing,...