Publications

We analyze drivers of the EUR/CHF exchange rate in different regimes between 2000 and 2020, where structural breaks are detected in an integrated way.

In this paper, we develop a novel, intuitive and objective measure of time-varying parameter uncertainty (PU) based on a simple statistical test.

A cross-country factor momentum strategy yields highly sigtnificant risk-adjusted returns and subsumes national

We use unsupervised machine learning to cluster stocks into equally weighted portfolios which in turn are plugged into minimum variance optimization.

We empirically proof that investors shy away from assets with recent structural breaks which we use as a proxy for parameter uncertainty.

We quantify performance measures distortions in a cryptocurrency sample truncated by survivorship and delisting bias.

Ranking assets based on their expected returns and subsequently optimizing portfolios on the reduced amount of information produces pobetter forecasts and significantly improved out-of-sample performance related to the plug-in portfolio.

Based on the sensitivity of stocks to changes in winning probabilities observed before the election, we show how the stock market’s assessment of the unobserved post-election winning probabilities can be backed out from stock prices.

We examine the effect of populism on financial markets around national elections.

In this paper we investigate the predictive power of cross-sectional volatility, skewness and kurtosis for future stock returns.

This paper investigates herding behavior in the crypto market. We consider the full, survivorship-bias free cross-section of cryptocurrencies, and document - against existing evidence - significant herding in this dataset. The effect is stronger, when using bitcoin as a ‘transfer currency’.

We use data from betting markets to analyze the sensitivity of stock returns to potential outcomes of political events such as elections. By classifying stocks into expected conditional winners and losers prior to such an event, we form portfolios that generate large positive returns after the event date, conditional on correctly anticipating the outcome. We illustrate this using data from the 2016 US presidential election and the 2016 Brexit referendum.

This paper introduces a novel measure of global macro-financial uncertainty and examines the state-dependent transmission of uncertainty to economic activity.

In an unbalanced cross-country panel covering 169 nations and time-series records of up to 52 years we analyze drivers behind beer consumption.

We show that parameter uncertainty based on the turbulence withing each cross-section of factor portfolios produces a significant out-of-sample forecast for six out of seven tested Fama-French risk factors.

This paper explores the statistical and economical significance of intraday and -week patterns in bid-ask spreads.

This study investigates the effectiveness of different hedging strategies, given the large rollover jumps of EuroStoxx 50 futures contracts.

The purpose of this paper is to create a universal (asset-class-independent) portfolio risk index for a global private investor.

Based on a multidisciplinary literature review, we discuss the assumptions implicit in the prevalent Black-Scholes model and argue for relaxed assumptions that better represent characteristics of uncertain IT projects.

Do forecasting errors from direct predictions of market components out-way the additional errors introduced by an intermediary asset pricing model?

This paper explores the statistical and economical significance of intraday and -week patterns in bid-ask spreads.

We describe existing and potential financial applications of the Mahalanobis distance.

Das vorliegende Kapitel soll einen kurzen Überblick über die mathematischen Grundlagen der Riemannschen Vermutung und insbesondere ihre Bedeutung für die Verteilung der Primzahlen geben.