Reinforcement Learning for Portfolio Management

Last update: Jan 01, 2023

Overview

qtrader

Reinforcement Learning for Portfolio Management

Why Reinforcement Learning?

Learns the optimal action, rather than models the market.
Adaptive to temporary changes of the market, due to its online training.
Optimizes the long-term (cumulative) reward, rather than the instantaneous benefit.

Setup

Exclusively Python 3 compatible, because of typings

macOS

source scripts/setup.sh

Documentation

Interim Report: Introduction to qtrader
Papers Review: Motivation, pros & cons of existing methods
Resources: List of relevant resources
Final Report: Master's Thesis
Presentation: 15 minutes project presentation

Owner

Angelos Filos

Machine Learning at the University of Oxford.

GitHub Repository

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Reinforcement Learning for Portfolio Management

Related tags

Overview

qtrader

Why Reinforcement Learning?

Setup

macOS

Documentation

Owner

Angelos Filos

The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation

Algebraic effect handlers in Python

Spearmint Bayesian optimization codebase

Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021)

Implementation of the paper "Fine-Tuning Transformers: Vocabulary Transfer"

This repository contains small projects related to Neural Networks and Deep Learning in general.

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(CVPR2021) Kaleido-BERT: Vision-Language Pre-training on Fashion Domain

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