28 citations · 74 across the 10 of their papers we have counts for
10 papers
Sequential asset ranking in nonstationary time series
Gabriel Borrageiro
We create a ranking algorithm, the naive Bayes asset ranker. Our algorithm computes the posterior probability that individual assets will be ranked higher than other portfolio cons…
Canonical Portfolios: Optimal Asset and Signal Combination
Nikan Firoozye, Vincent Tan, Stefan Zohren
This paper presents a novel framework for analyzing the optimal asset and signal combination problem. Our approach builds upon the dynamic portfolio selection problem introduced by…
The Recurrent Reinforcement Learning Crypto Agent
Gabriel Borrageiro, Nick Firoozye, Paolo Barucca
We demonstrate a novel application of online transfer learning for a digital assets trading agent. This agent uses a powerful feature space representation in the form of an echo st…
Reinforcement Learning for Systematic FX Trading
Gabriel Borrageiro, Nick Firoozye, Paolo Barucca
We explore online inductive transfer learning, with a feature representation transfer from a radial basis function network formed of Gaussian mixture model hidden processing units…
Online Learning with Radial Basis Function Networks
Gabriel Borrageiro, Nick Firoozye, Paolo Barucca
Financial time series are characterised by their nonstationarity and autocorrelation. Even if these time series are differenced, technically ensuring their stationarity, they exper…
QuantNet: Transferring Learning Across Systematic Trading Strategies
Adriano Koshiyama, Sebastian Flennerhag, Stefano B. Blumberg +2
Systematic financial trading strategies account for over 80% of trade volume in equities and a large chunk of the foreign exchange market. In spite of the availability of data from…
Optimal Dynamic Strategies on Gaussian Returns
Nick Firoozye, Adriano Koshiyama
Dynamic trading strategies, in the spirit of trend-following or mean-reversion, represent an only partly understood but lucrative and pervasive area of modern finance. Assuming Gau…
Avoiding Backtesting Overfitting by Covariance-Penalties: an empirical investigation of the ordinary and total least squares cases
Adriano Koshiyama, Nick Firoozye
Systematic trading strategies are rule-based procedures which choose portfolios and allocate assets. In order to attain certain desired return profiles, quantitative strategists mu…
Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination
Adriano Koshiyama, Nick Firoozye, Philip Treleaven
Systematic trading strategies are algorithmic procedures that allocate assets aiming to optimize a certain performance criterion. To obtain an edge in a highly competitive environm…
A Machine Learning-based Recommendation System for Swaptions Strategies
Adriano Soares Koshiyama, Nick Firoozye, Philip Treleaven
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their…