The main goal of this paper is to introduce a new financial stress indicator, signaling regime transitions from stability to turbulence. This indicator is based on the combination of a wide range of market prices of risk, properly normalized to make them comparable across markets and time...

We consider a gradient boosting decision trees (GBDT) approach to predict large S&P 500 price drops from a set of 150 technical, fundamental and macroeconomic features. We report an improved accuracy of GBDT over other machine learning (ML) methods on the S&P 500 futures prices. We show that...