Reinforcement Learning for Financial Trading

版本 1.0.2 (4.8 MB) 作者: David Willingham
MATLAB example on how to use Reinforcement Learning for developing a financial trading model
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更新时间 2024/3/7
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Reinforcement Learning For Financial Trading ?
How to use Reinforcement learning for financial trading using Simulated Stock Data using MATLAB.

Setup
To run:

Open RL_trading_demo.prj
Open workflow.mlx
Run workflow.mlx
Environment and Reward can be found in: myStepFunction.m

Overview:

The goal of the Reinforcement Learning agent is simple. Learn how to trade the financial markets without ever losing money.
Note, this is different from learn how to trade the market and make the most money possible.

The aim of this example was to show:

1. What reinforcement learning is
2. How it can be applied to trading the financial markets
3. Leave a starting point for financial professionals to use and enhance using their own domain expertise.

The example use an environment consisting of 3 stocks, $20000 cash & 15 years of historical data.

Stocks are:
Simulated via Geometric Brownian Motion or
Historical Market data (source: AlphaVantage: www.alphavantage.co)

Copyright 2020 The MathWorks, Inc.

引用格式

David Willingham (2024). Reinforcement Learning for Financial Trading (https://github.com/matlab-deep-learning/reinforcement_learning_financial_trading), GitHub. 检索来源 .

MATLAB 版本兼容性
创建方式 R2019b
兼容任何版本
平台兼容性
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版本 已发布 发行说明
1.0.2

Updated Description
1.0.1

Added MATLAB Live script version
1.0.0

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。