Search Results for author: Nick Firoozye

Found 8 papers, 1 papers with code

Limit Order Book Simulations: A Review

no code implementations27 Feb 2024 Konark Jain, Nick Firoozye, Jonathan Kochems, Philip Treleaven

Limit Order Books (LOBs) serve as a mechanism for buyers and sellers to interact with each other in the financial markets.

Algorithmic Trading

Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process

no code implementations14 Dec 2023 Konark Jain, Nick Firoozye, Jonathan Kochems, Philip Treleaven

We propose a novel methodology of using Compound Hawkes Process for the LOB where each event has an order size sampled from a calibrated distribution.

Reinforcement Learning for Systematic FX Trading

no code implementations10 Oct 2021 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 to a direct, recurrent reinforcement learning agent.

Position reinforcement-learning +2

QuantNet: Transferring Learning Across Systematic Trading Strategies

2 code implementations7 Apr 2020 Adriano Koshiyama, Sebastian Flennerhag, Stefano B. Blumberg, Nick Firoozye, Philip Treleaven

The encoder transforms market-specific data into an abstract latent representation that is processed by a global model shared by all markets, while the decoder learns a market-specific trading strategy based on both local and global information from the market-specific encoder and the global model.

Meta-Learning Transfer Learning

Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination

no code implementations7 Jan 2019 Adriano Koshiyama, Nick Firoozye, Philip Treleaven

Systematic trading strategies are algorithmic procedures that allocate assets aiming to optimize a certain performance criterion.

Time Series Time Series Analysis

A Machine Learning-based Recommendation System for Swaptions Strategies

no code implementations4 Oct 2018 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.

BIG-bench Machine Learning

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