Financial Analysis - Build a ChatGPT Pairs Trading Bot

This course on financial analysis with ChatGPT and pairs trading integrates AI with financial expertise for insightful investment decisions, risk assessments, and financial planning. - Participants will build a trading bot using pairs trading, starting with an introduction to ChatGPT, project scope, and necessary tools. - The course covers pairs trading intuition, initial prompts, trading signal correction, and z-score computation, along with returns analysis and strategy testing. - Emphasis is placed on leveraging ChatGPT for efficient financial decision-making and trading. - Key learnings include algorithmic trading strategies and applying data science to finance. Designed for those with a foundational understanding of Python, finance, and statistics, the course aims to enhance skills in using ChatGPT for coding, pairs trading, and trading strategies across various markets like stocks, forex, and cryptocurrencies.

• Welcome
• In this module, we will introduce the course objectives, outline the scope of the project you will be working on, and provide an overview of the tools and resources you will need to succeed.
• Getting Set Up
• In this module, we will explore key strategies for succeeding in this course and guide you on where to find the code needed for your project. These foundational steps will ensure you are well-prepared for the journey ahead.
• Pairs Trading with ChatGPT
• In this module, we will delve into pairs trading, beginning with understanding its core principles and intuition. You will learn how to leverage ChatGPT for developing and refining trading strategies, correct various aspects of these strategies, and measure their performance. Additionally, we'll explore advanced topics such as log returns, long-only strategies, and iterative improvements using feedback and suggestions.
• Sanity Check
• In this module, we will focus on validating the robustness of our trading strategies. You'll conduct a mean reversion test to verify the foundational assumptions and a pairs trading test to ensure the practical reliability of the strategies developed in the previous sections.
• Course Summary
• In this module, we will conclude the course by summarizing the key lessons and insights you have gained. Additionally, we will reflect on how ChatGPT has contributed to personalizing your learning journey, enhancing your understanding and application of pairs trading strategies.
• Setting Up Your Environment (Appendix/FAQ by Student Request)
• In this module, we will guide you through setting up your development environment using Anaconda. You will learn how to install crucial libraries like NumPy, SciPy, Matplotlib, Pandas, IPython, Theano, and TensorFlow, ensuring you have all the necessary tools to work effectively on your projects.
• Extra Help with Python Coding for Beginners (Appendix/FAQ by Student Request)
• In this module, we will provide additional support for beginners in Python coding. You'll go through a two-part series on how to code independently, explore the similarities between using Jupyter Notebook and traditional coding environments, and learn how to use GitHub along with other valuable coding tips to enhance your programming skills.
• Effective Learning Strategies for Machine Learning (Appendix/FAQ)
• In this module, we will explore strategies to maximize your success in the course, providing an in-depth guide for effective learning. You will understand whether the course is designed for beginners, experts, academic purposes, or practical application. Additionally, we will guide you on the best sequence to take our courses to align with your personal learning objectives and background.
• Appendix / FAQ Finale
• In this module, we will clarify the role of the appendix in the course. You'll learn what information is included in the appendix and how it can be used as a resource for further understanding and reference throughout your learning journey.