Financial Analysis: Build A Chatgpt Pairs Trading Bot

Use ChatGPT for Algotrading, Forex, Stock Investing, Making Money Online, +More in Python

What you'll learn

Use ChatGPT to build a pairs trading bot in Python

Common mistakes when using ChatGPT for coding

Pairs trading, algorithmic trading, algotrading, stock trading strategies

Computing z-scores, returns and log returns, cumulative returns, portfolio returns

Apply data science to financial analysis

Trading strategies for stocks, forex, cryptocurrencies, Bitcoin, Ethereum, altcoins

Requirements

Decent understanding of Python and data science libraries (Numpy, Matplotlib, Pandas)

Basic understanding of finance (stock prices, returns, log returns, cumulative returns)

Description

Hello friends!As one of the original artificial intelligence and machine learning instructors on this platform, how could I not create a course on ChatGPT?ChatGPT and its successor, GPT-4, have already begun to change the world. People are excited about new opportunities, and terrified of the potential impacts on our society.This course combines 2 of my favorite topics: AI and finance (algorithmic trading).The premise of this course is simple: use ChatGPT to build a trading bot (specifically, using pairs trading which is what I was interested in at the time).Throughout the course, we will learn about the amazing capabilities of ChatGPT and GPT models in general, such as GPT-3, GPT-3.5, GPT-4, etc. We will learn about the many pitfalls of these models, and why you need to keep your guard up. These models do make mistakes, but we will learn how to deal with them. We will learn the best ways to make use of ChatGPT to help us be more efficient and productive.Important consideration: Why not just ask ChatGPT yourself and forego this course? Sure, you can tell ChatGPT if you get an error and maybe it'll fix it, but that only works for syntax errors (errors that break the rules of the Python language). What you'll miss, if you don't have foundational knowledge in Python, finance, and statistics, is semantic errors (errors in logic and reasoning), because you won't even notice them in the first place. That is what it means to "keep your guard up", and that is one of the major lessons in this course, which I'm already seeing is very easy for people to miss!So what are you waiting for? Join me now on this exciting journey! ( And maybe learn how to make some money in the process :) )Suggested Prerequisites:Decent understanding of Python and data science libraries (Numpy, Matplotlib, Pandas)Basic understanding of finance (stock prices, returns, log returns, cumulative returns)

Overview

Section 1: Welcome

Lecture 1 Introduction

Lecture 2 Project Scope

Lecture 3 Course Tools

Section 2: Getting Setup

Lecture 4 How to Succeed in this Course

Lecture 5 Where to Get the Code

Section 3: Pairs Trading with ChatGPT

Lecture 6 Pairs Trading Intuition

Lecture 7 The Initial Prompt

Lecture 8 Correcting the Trading Signal

Lecture 9 Correcting the Z-Score Computation

Lecture 10 Correcting the Return Computation

Lecture 11 Correcting How We Measure Strategy Performance

Lecture 12 Returns, Log Returns, Cumulative Returns

Lecture 13 More About Log Returns (Optional)

Lecture 14 Strategy Performance Computation (Optional)

Lecture 15 Asking ChatGPT for Pairs

Lecture 16 Testing the Strategy

Lecture 17 Benchmark Against Buy-and-Hold

Lecture 18 Fixing the Spread

Lecture 19 Extending the Position

Lecture 20 Extending the Position (Code)

Lecture 21 Asking ChatGPT to Fix an Error

Lecture 22 More Pairs

Lecture 23 Long-Only Strategy

Lecture 24 Long-Only Strategy (Code)

Lecture 25 Return Computation Revisited and Other Extensions (Optional)

Lecture 26 Return Computation Revisited (Code)

Section 4: Sanity Check

Lecture 27 Mean Reversion Test

Lecture 28 Pairs Trading Test

Section 5: Course Summary

Lecture 29 Conclusion and Lessons

Lecture 30 ChatGPT Knows Who I Am!?

Section 6: Setting Up Your Environment FAQ

Lecture 31 Anaconda Environment Setup

Lecture 32 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

Anyone who wants to learn how to use ChatGPT to build a pairs trading bot,Students and professionals in data science and machine learning with an interest in financial analysis