Asset market liquidity risk is a significant and perplexing subject and though the term market liquidity risk is used quite chronically in academic literature it lacks an unambiguous definition, let alone understanding of the proposed risk measures. To this end, this paper presents a review of...

Financial institutes have to be in a position to describe and to analyze the networks of obligors in their credit portfolios. If one obligor defaults who is numerously connected with other obligors in the portfolio there can be effects of credit contagion. We suggest a graph-based modeling of...

Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging strategies. Unfortunately, due to the curse of...

Corporate FX risk management has gained complexity with increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this...

This paper analyses the properties of two popular portfolio strategies. They are the Buy and Hold strategy and the Discretely Rebalanced strategy. It is assumed that the underlying stocks have a multivariate lognormal distribution. The distribution of the sum of correlated lognormals plays a...

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of...

Based on a robustness concept adapted from mathematical statistics, we investigate robust optimal investment strategies for worst-case crash scenarios when the maximum crash height is not known a priori. We specify an efficiency criterion in terms of the certainty equivalents of optimal terminal...

Deep learning is a powerful tool, which is becoming increasingly popular in financial modeling. However, model validation requirements such as SR 11-7 pose a significant obstacle to the deployment of neural networks in a bank's production system. Their typically high number of (hyper-)parameters...

Many sophisticated investors rely on scenario analysis to select a portfolio. These investors define prospective economic scenarios, assign probabilities to them, translate the scenarios into expected asset class returns, and select the portfolio with the highest expected return or expected...