This article provides a portfolio optimization approach that takes into account extreme events. By merging a (downside only) panic copula with the empirical marginal distributions, panic-awareness is attained for the optimization process. This approach includes the likelihood of highly...

This paper employs a deep learning approach for linking stock market fundamentals to trading signals via neural networks. With an average accuracy of ~54% the model predicts whether markets go up or down on the subsequent trading day. Coupling the prediction to a binary long/cash strategy yields...

Common research suggests that investor sentiment is negatively related to future stock returns and positively related to future volatility. I incorporate this idea in the asset allocation process by blending both views on the expected return and the conditional value at risk (CVaR) based on...

This article demonstrates how to directly incorporate common value investing ideas in the portfolio optimization process. Through minimizing the relative entropy, multiple value rankings are merged with the historical return distribution. This approach yields performance improvements both from a...

Common predictors variables for the equity premium such as financial ratios exhibit high persistence and thus are borderline non-stationary. This article sheds light on the possibility of fractional differencing those ratios in order to attain stationarity yet preserving the long-run memory....

We test the predictability of international (sub-) sector industry returns using common fundamental ratios. For the majority of sector returns we find pervasive predictive relationships using the global price to cash-flow ratio. Furthermore, we stress the cross-dependencies between sectors and...

We extract information on relative shopping interest from Google search volume and provide a genuine and economically meaningful approach to directly incorporate this data into a portfolio optimization technique. By generating a firm ranking based on a Google search volume metric, we can predict...

In order to identify the economic driver of negative investment-cash flow sensitivities (ICFS), we derive testable predictions from extending a theoretical investment model with endogenous financing costs ("revenue effect") and contrast them with the corporate life-cycle hypothesis. We find that...

Warum einfach, wenn's auch umständlich geht? Anmerkungen zum Basler IRB-Ansatz Eine der wesentlichen Neuerungen im Konsultationspapier zur Neuen Basler Eigenkapitalverordnung (Basel II) stellt der auf internen Ratings basierte Ansatz (IRB-Ansatz) dar. Er kann als eine konzeptionelle Innovation...