Learn to create custom financial technical indicators for a Python Reinforcement Learning trading bot in this advanced tutorial. Calculate relative strength index (RSI), simple moving average (SMA), and on-balance volume (OBV) indicators using the Finta package for technical analysis. Integrate these new trading indicators into the gym-anytrading environment for Reinforcement Learning, specifically focusing on trading Gamestop ($GME) stocks. Order trading data using Pandas, fix volume data issues, and customize the trading environment. Train a reinforcement learning model using the newly calculated indicators and evaluate its performance. Gain practical skills in leveraging custom indicators for various trading strategies and assets, applicable beyond just GME stocks.
Custom Indicators for Reinforcement Learning Trading Tutorial - GME Python Trading PT2
Overview
Syllabus
- Start
- Ordering Trading Data using Pandas
- Installing and Importing Dependencies - Finta
- Fixing Volume Data
- Calculating RSI, SMA and OBV using Pandas and Finta
- Customizing The Trading Environment
- Training the Reinforcement Learning Agent
- Evaluating Model Performance
Taught by
Nicholas Renotte
Related Courses
-
Reinforcement Learning for Trading Tutorial - GME RL Python Trading
-
Reinforcement Learning for Trading Strategies
-
Machine Learning for Trading
3.0 -
Reinforcement Learning Course - Full Machine Learning Tutorial
-
Python Reinforcement Learning using OpenAI Gymnasium – Full Course
-
Using Machine Learning in Trading and Finance
