Developing a ChatGPT-Powered Trading Bot for Financial Analysis Online Course

Developing a ChatGPT-Powered Trading Bot for Financial Analysis Online Course

This course introduces financial analysis with ChatGPT using pairs trading, blending AI capabilities with financial expertise to generate smarter investment decisions, risk assessments, and planning strategies. You’ll start with an overview of ChatGPT, project scope, and course tools before diving into pairs trading—covering trading intuition, signal correction, z-score computation, returns analysis, and strategy testing. Through building a trading bot, you’ll explore concepts like log returns, cumulative returns, and long-only strategies. By the end, you’ll know how to leverage ChatGPT effectively for financial analysis, enhancing productivity, decision-making, and trading performance with pairs trading.

Who should take the course?

This course is ideal for traders, financial analysts, developers, and tech enthusiasts who want to combine AI with finance to build intelligent trading solutions. It’s well-suited for those with a basic understanding of Python and financial markets who are eager to explore how ChatGPT can be integrated into trading strategies and market analysis. Whether you’re a finance professional aiming to automate insights or a developer interested in AI-driven trading systems, this course will equip you with practical skills to design and implement a ChatGPT-powered trading bot.

What you will learn

• Learn to use ChatGPT to build a pairs trading bot in Python
• Learn the common mistakes when using ChatGPT for coding
• Develop Pairs, algorithmic, algo-trading, and stock trading strategies
• Compute z-scores, log, cumulative returns, and portfolio returns
• Understand how to apply data science strategies to financial analysis
• Learn trading strategies for stocks, forex, cryptos, Bitcoin, Ethereum

Course Outline

Welcome

• Introduction
• Project Scope
• Course Tools

Getting Set Up

• How to Succeed in This Course
• Where to Get the Code

Pairs Trading with ChatGPT

• Pairs Trading Intuition
• The Initial Prompt
• Correcting the Trading Signal
• Correcting the Z-Score Computation
• Correcting the Return Computation
• Correcting How We Measure Strategy Performance
• Returns, Log Returns, Cumulative Returns
• More about Log Returns (Optional)
• Strategy Performance Computation (Optional)
• Asking ChatGPT for Pairs
• Testing the Strategy
• Benchmark Against Buy-and-Hold
• Fixing the Spread
• Extending the Position
• Extending the Position (Code)
• Asking ChatGPT to Fix an Error
• More Pairs
• Long-Only Strategy
• Long-Only Strategy (Code)
• Return Computation Revisited and Other Extensions (Optional)
• Return Computation Revisited (Code)
• Suggestion Box

Sanity Check

• Mean Reversion Test
• Pairs Trading Test

Course Summary

• Conclusion and Lessons
• ChatGPT Knows Who I Am

Setting Up Your Environment (Appendix/FAQ by Student Request)

• Anaconda Environment Setup
• How to Install NumPy, SciPy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

Extra Help with Python Coding for Beginners (Appendix/FAQ by Student Request)

• How to Code Yourself (Part 1)
• How to Code Yourself (Part 2)
• Proof that Using Jupyter Notebook Is the Same as Not Using It
• How to Use GitHub and Extra Coding Tips (Optional)

Effective Learning Strategies for Machine Learning (Appendix/FAQ)

• How to Succeed in This Course (Long Version)
• Is This for Beginners or Experts? Academic or Practical? Fast or Slow-Paced?
• What Order Should I Take Your Courses In? (Part 1)
• What Order Should I Take Your Courses In? (Part 2)

Appendix / FAQ Finale

• What Is the Appendix?