Assessments of investors' risk appetite/aversion stance via indicators often yields results which seem unsatisfactory (see e.g. Illing and Aaron (2005)). Understanding how such indicators work therefore seems essential for further improvements. The present paper seeks to contribute to this...

Deviations from normality in financial return series have led to the development of alternative portfolio selection models. One such model is the downside risk model, whereby the investor maximizes his return given a downside risk constraint. In this paper we empirically observe the...

Der deutsche Aktienmarkt sah sich in den letzten 15 Jahren substantiellen Veränderungen gegenüber, welche unter anderem in eine zunehmende Internationalisierung und deutlich erhöhten Streubesitz mündeten. In der vorliegenden Arbeit untersuchen wir, inwieweit dies die aus klassischen...

The recent increase in passive investment products has provided investors with easy access to international markets. The basic motivation of this paper is to offer new tools to investors who want to allocate assets across countries. This study investigates the performance of equity country...

During the global financial crisis, stressed market conditions led to skyrocketing corporate bond spreads that could not be explained by conventional modeling approaches. This paper builds on this observation and sheds light on time-variations in the relationship between systematic risk factors...

Asset pricing in its essence is a very controversial topic. Despite numerous research papers criticising traditional approaches, such as linear factor models, practitioners as well as academics repeatedly return to the milestone models such as the Capital Asset Pricing Model (CAPM), mainly due...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

This paper tests the performance of the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor and Carhart four-factor models on the Polish market. We use stock level data from April 2001 to January 2014 and find strong evidence for value and momentum effects, but only weak evidence...

We examine the predictability of expected stock returns across horizons using machine learning. We use neural networks, and gradient boosted regression trees on the U.S. and international equity datasets. We find that predictability of returns using neural networks models decreases with longer...

Deviations from normality in financial return series have led to the development of alternative portfolio selection models. One such model is the downside risk model, whereby the investor maximizes his return given a downside risk constraint. In this paper we empirically observe the...