Long short-term memory (LSTM) networks are a state-of-the-art technique for sequence learning. They are less commonly applied to financial time series predictions, yet inherently suitable for this domain. We deploy LSTM networks for predicting out-of-sample directional movements for the...

There are many methods for explaining why a machine learning model produces a given output in response to a given input. The relative merits of these methods are often debated using theoretical arguments and illustrative examples. This paper provides a large-scale empirical test of four widely...

Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. This paper introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables...