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

All supplementary material used by me while TA-ing CS3244: Machine Learning

Code repository for Semantic Terrain Classification for Off-Road Autonomous Driving

This repository contains codes of ICCV2021 paper: SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation

Vertex AI: Serverless framework for MLOPs (ESP / ENG)

FrankMocap: A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator

👐OpenHands : Making Sign Language Recognition Accessible (WiP 🚧👷‍♂️🏗)

3D Avatar Lip Syncronization from speech (JALI based face-rigging)

RoboDesk A Multi-Task Reinforcement Learning Benchmark

O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learning (CoRL 2021)

StarGAN - Official PyTorch Implementation (CVPR 2018)

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering (NAACL 2021)

CityLearn Challenge Multi-Agent Reinforcement Learning for Intelligent Energy Management, 2020, PikaPika team

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