3 papers
q-fin.TR2026
Hierarchical Graph Learning for Calendar Spread Strategies in Commodity Futures Markets
Yoonsik Hong, Diego Klabjan
Commodity futures can be represented hierarchically, with underlying assets at the upper level and individual futures contracts at the lower level. Entities at each level can be co…
q-fin.PR2025
Statistical Arbitrage in Options Markets by Graph Learning and Synthetic Long Positions
Yoonsik Hong, Diego Klabjan
Statistical arbitrages (StatArbs) driven by machine learning has garnered considerable attention in both academia and industry. Nevertheless, deep-learning (DL) approaches to direc…
q-fin.TR2025
Graph Learning for Foreign Exchange Rate Prediction and Statistical Arbitrage
Yoonsik Hong, Diego Klabjan
We propose a two-step graph learning approach for foreign exchange statistical arbitrages (FXSAs), addressing two key gaps in prior studies: the absence of graph-learning methods f…