Mid-Curve Recommendation System: a Stacking Approach Through Neural Networks. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (IJCNN, 2018)

A Machine Learning-based Recommendation System for Swaptions Strategies. - Adriano Soares Koshiyama; Nick Firoozye; Philip C. Treleaven (CoRR, 2018)

Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (CoRR, 2019)

A derivatives trading recommendation system: The mid-curve calendar spread case. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (Intell. Syst. Account. Finance Manag., 2019)

Algorithms in future capital markets: a survey on AI, ML and associated algorithms in capital markets. - Adriano S. Koshiyama; Nick Firoozye; Philip C. Treleaven (ICAIF, 2020)

QuantNet: Transferring Learning Across Systematic Trading Strategies. - Adriano S. Koshiyama; Sebastian Flennerhag; Stefano B. Blumberg; Nick Firoozye; Philip C. Treleaven (CoRR, 2020)

Online Learning with Radial Basis Function Networks. - Gabriel Borrageiro; Nick Firoozye; Paolo Barucca (CoRR, 2021)

Sequential asset ranking in nonstationary time series. - Gabriel Francisco Borrageiro; Nick Firoozye; Paolo Barucca (ICAIF, 2022)

Reinforcement Learning for Systematic FX Trading. - Gabriel Borrageiro; Nick Firoozye; Paolo Barucca (IEEE Access, 2022)

The Recurrent Reinforcement Learning Crypto Agent. - Gabriel Borrageiro; Nick Firoozye; Paolo Barucca (IEEE Access, 2022)

Sequential Asset Ranking within Nonstationary Time Series. - Gabriel Borrageiro; Nick Firoozye; Paolo Barucca (CoRR, 2022)

Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process. - Konark Jain; Nick Firoozye; Jonathan Kochems; Philip C. Treleaven (CoRR, 2023)