One of the main challenges facing researchers and industry professionals for decades is the successful prediction of asset returns. This paper enriches this endeavor by an in-depth analysis of topological metrics of correlation networks applied to financial forecasting. While academic research...

Persistent homology is the workhorse of modern topological data analysis, which in recent years becomes increasingly powerful due to methodological and computing power advances. In this paper, after equipping the reader with the relevant background on persistent homology, we show how this tool...

This paper introduces novel financial predictors that are derived from the interaction profile of financial markets. These predictors utilize network-based and topological information. Since these predictors are derived from the inner dynamics (microstructure) of financial markets, they can be...

Turbulent financial market periods are characterized by low mean returns, high volatility and often by the disappearance of the diversification effect. Therefore, accurate predictions of financial turbulence can significantly improve the risk-reward-ratio of investment strategies and is...