This paper presents a reinforcement learning approach for foreign exchange trading. Inspired by technical analysis methods, this makes use of indicators encoding them into Gramian Angular Fields and searches patterns that indicate price movements using convolutional neural networks (CNN). In addition to the policy determines action take, an extra regression head is utilized determine size marke...

We explore the foreign exchange and stock market networks for 48 countries from 1999 to 2012 and propose a model, based on complex Hilbert principal component analysis, for extracting significant lead-lag relationships between these markets. The global set of countries, including large and small countries in Europe, the Americas, Asia, and the Middle East, is contrasted with the limited scopes ...

This paper presents results from an in-depth analysis of the foreign exchange rate exposure of a large nonfinancial firm based on proprietary internal data including cash flows, derivatives and foreign currency debt, as well as external capital market data. While the operations of the multinational firm have significant exposure to foreign exchange rate risk due to foreign currency-based activi...