We establish the out-of-sample predictability of monthly exchange rate changes via machine learning techniques based on 70 predictors capturing country characteristics, global variables, and their interactions. To guard against overfitting, we use the elastic net to estimate a high-dimensional...

Offshore assets present investors with an increased investment universe and additional opportunities for reward, but embedded exposure to exchange rates can result in additional risk. In this work, we consider a global equity portfolio of five equity indices (US, Japan, Europe, UK and Canada),...

Using the Tsay (1988) outlier identification methodology on daily log-returns of 16 commodity spot price series and 25 commodity index series, this study assesses the impact significant and unexpected news announcements had on volatility between January 1, 1997 and December 31, 2007. Results...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

Recent academic studies have shown that since the mid-nineties, the pass-through of exogenous oil shocks into headline inflation has been increasing while the pass through into core inflation seems to have ceased. This paper explores the implications in terms of commodity allocation for...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System...

Financial technologies, boosted by the availability of machine learning models, are expanding in all areas of finance: from payments (peer to peer lending) to asset management (robot advisors) to payments (blockchain coins). Machine learning models typically achieve a high accuracy at the...

Financial risk management is difficult at the best of times, but especially so in the presence of economic uncertainty and financial crises. The purpose of this special issue on "Advances in Financial Risk Management and Economic Policy Uncertainty" is to highlight some areas of research in...