292 citations · 760 across the 55 of their papers we have counts for
4 papers · 1 filter
Deep Inception Networks: A General End-to-End Framework for Multi-asset Quantitative Strategies
Tom Liu, Stephen Roberts, Stefan Zohren
We introduce Deep Inception Networks (DINs), a family of Deep Learning models that provide a general framework for end-to-end systematic trading strategies. DINs extract time serie…
Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity
Daniel Poh, Stephen Roberts, Stefan Zohren
Cross-sectional strategies are a classical and popular trading style, with recent high performing variants incorporating sophisticated neural architectures. While these strategies…
Building Cross-Sectional Systematic Strategies By Learning to Rank
Daniel Poh, Bryan Lim, Stefan Zohren +1
The success of a cross-sectional systematic strategy depends critically on accurately ranking assets prior to portfolio construction. Contemporary techniques perform this ranking s…
Extending Deep Learning Models for Limit Order Books to Quantile Regression
Zihao Zhang, Stefan Zohren, Stephen Roberts
We showcase how Quantile Regression (QR) can be applied to forecast financial returns using Limit Order Books (LOBs), the canonical data source of high-frequency financial time-ser…