alphaQ

A Q-learing based portfolio trading system built using OpenAI Gym and Stable-Baselines3.

Requirements

• Python 3.7

Installation

1. Clone this repository: git clone https://github.com/mannmann2/alphaQ.git
2. cd alphaQ
3. pip install -r requirements.txt

Usage

For learning how to train and evaluate the agents, follow the starter notebook provided with this repository.

• main.ipynb

Or view it in Jupyter's online notebook viewer:

• Nbviewer

Results

Models

Below is a list of all the pre-trained models provided.

Best models for [AAPL, JPM, MSFT, V]

DQN_best
DDPG_best

Alternate models for [AAPL, JPM, MSFT, V]

DQN:DQN 5, DQN 6, DQN 7, DQN 8
DDPG:DDPG 7, DDPG 8

Variant Models

DQN AAXP, CVX, DIS, KO
DQN BJNJ, MCD, MMM, WMT
DQN CCAT, CSCO, HD, IBM

DDPG AJNJ, MCD, MMM, WMT
DDPG BAMGN, NKE, UNH, VZ
DDPG CGS, NKE, PG, UNH

Documentation

Project Proposal
Progress Slides 1
Progress Slides 2
Progress Slides 3
Progress Slides 4
Preliminary Report
MSc Final Report

• Free software: MIT license