150 citations · 416 across the 41 of their papers we have counts for
5 papers · 1 filter
Taming the Greeks: Option Portfolios with Inductive Biases
Wee Ling Tan, Stephen Roberts, Stefan Zohren
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures. Wh…
Stacking the Deck: Tunable Trainability in Stacked LCUs
Nikhil Khatri, Stefan Zohren, Gabriel Matos
Variational quantum circuits have been central to many proposed near-term applications of quantum computing, but a growing body of evidence suggests that trainability and quantum a…
DeRegiME: Deep Regime Mixtures for Probabilistic Forecasting under Distribution Shift
Kieran Wood, Stefan Zohren, Stephen J. Roberts
We introduce DeRegiME -- Deep Regime Mixture of Experts -- a direct multi-horizon probabilistic forecaster that separates latent uncertainty regimes from the underlying signal and…
Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks
Kunihiro Miyazaki, Takanobu Kawahara, Stephen Roberts +1
The advancement of large language models (LLMs) has accelerated the development of autonomous financial trading systems. While mainstream approaches deploy multi-agent systems mimi…
DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management
Kieran Wood, Stephen J. Roberts, Stefan Zohren
We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three…