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Financial Analysis

Build a ChatGPT Pairs Trading Bot

Lazy Programmer Inc. and Lazy Programmer Team

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?

Read more

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)

Enroll now

What's inside

Learning objectives

  • 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

Syllabus

Welcome
Introduction
Project Scope
Course Tools
Read more
Getting Setup
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
Why So Many Errors?
ChatGPT Knows Who I Am!?
Setting Up Your Environment (Appendix/FAQ by Student Request)
Pre-Installation Check
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 & 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?
BONUS

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Well-suited for learners with some foundational knowledge in Python, data science libraries, and finance
Taught by instructors who have experience in artificial intelligence, machine learning, algorithmic trading, and finance
Builds a strong foundation for beginners in understanding ChatGPT, trading strategies, and data science
Develops skills in using ChatGPT to build a trading bot and utilizing data science for financial analysis
May require additional background knowledge in certain areas for learners to fully grasp the concepts
Assumes familiarity with essential Python libraries and concepts, including Numpy, Pandas, and Matplotlib

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Activities

Coming soon We're preparing activities for Financial Analysis: Build a ChatGPT Pairs Trading Bot. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Financial Analysis: Build a ChatGPT Pairs Trading Bot will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine learning engineers apply machine learning models to real-world problems, including in finance. This course may help build foundational knowledge in machine learning and its applications in trading and algorithmic finance.
Financial Risk Manager
Financial risk managers develop and implement strategies to manage and mitigate financial risks. This course may help build the foundational skills in financial risk assessment and management, particularly in the context of automated trading.
Investment Advisor
Investment advisors provide financial advice and services to individuals and families. This course may be helpful to investment advisors who are interested in staying up-to-date on the latest financial analysis and trading techniques, including the use of AI.
Financial Planner
Financial planners help individuals and families create and implement financial plans to meet their financial goals. This course may be helpful to financial planners who are interested in using algorithmic trading to optimize investment strategies.
Data Scientist
Data scientists use their knowledge in mathematics, statistics, and programming to extract insights from data, which is essential in financial analysis and trading. This course may help build the data science skills needed to apply to data science roles in the finance industry.
Software Engineer
Software engineers build and maintain software applications, including for financial institutions. This course may be helpful to software engineers who are interested in specializing in developing applications for financial analysis.
Actuary
Actuaries use mathematical and statistical skills to assess and manage risks, which is often applied to financial matters. This course may be helpful to actuaries who are interested in building a foundation in financial analysis and trading using machine learning.
Business Analyst
Business analysts help organizations improve their performance by using data analysis techniques, including in the financial sector. Taking this course may help build the skills needed to use emerging technologies like ChatGPT in financial data analysis.
Economist
Economists study economic data and trends to make predictions about the economy. This course may help build the analytical skills needed for economic modeling, particularly in the financial sector.
Auditor
Auditors examine financial records and provide assurance on the accuracy of financial statements. This course may be helpful to auditors who are interested in specializing in financial analysis and trading.
Portfolio Manager
Portfolio managers are responsible for managing and growing investment portfolios on behalf of clients. This course may be helpful to aspiring portfolio managers who wish to understand the technical applications of machine learning in algorithmic trading.
Investment Banker
Investment bankers help companies raise capital and advise them on mergers and acquisitions. Courses like this may be helpful for aspiring investment bankers who are interested in building a foundation in algorithmic trading strategies for modern finance.
Market Researcher
Market researchers gather and analyze data on consumer behavior, including in the financial sector. This course may be helpful to market researchers who are interested in specializing in financial analysis and trading.
Financial Analyst
Financial analysts use statistical analysis, financial ratios, and market research to make investment decisions. Taking this course may help an aspiring financial analyst build a foundation in using statistical analysis, particularly for algorithmic trading of stocks and cryptocurrencies.
Quantitative Analyst
Quantitative analysts leverage advanced mathematical and statistical expertise, which ChatGPT may help build, to develop and test financial models for firms and investment banks. This course may be helpful in building the skills needed to land and excel in a quantitative analyst role.

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Financial Analysis: Build a ChatGPT Pairs Trading Bot.
Explores the theoretical underpinnings of pairs trading and provides practical guidance on implementing different pairs trading strategies. Useful as a reference for understanding the concepts and techniques involved in pairs trading, but may not be as helpful for the practical implementation of a trading bot using ChatGPT.
Provides an overview of algorithmic trading strategies, including pairs trading, and discusses the rationale behind their implementation. Useful for gaining a broader understanding of algorithmic trading and its applications, but may not be as directly relevant to the specific task of building a pairs trading bot using ChatGPT.
An introduction to Python programming for data analysis, covering topics such as data manipulation, visualization, and statistical modeling. Useful for gaining the necessary programming skills to implement the pairs trading bot using Python.
An introduction to natural language processing using Python, covering topics such as text processing, machine learning, and deep learning. Useful for gaining the necessary NLP skills to interact effectively with ChatGPT and improve the accuracy of the trading bot.
A comprehensive introduction to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. Useful for gaining a deeper understanding of the underlying technology behind ChatGPT and how to use it for advanced algorithmic trading strategies.
A comprehensive introduction to statistical learning, covering topics such as linear regression, logistic regression, and decision trees. Provides a strong foundation for understanding the statistical concepts behind pairs trading and evaluating the performance of the trading bot.
A comprehensive guide to data science using Python, covering topics such as data manipulation, visualization, and machine learning. Useful for gaining the necessary data science skills to implement the pairs trading bot using Python.
A leading Python library for natural language processing, providing a wide range of tools for text processing, machine learning, and deep learning. Useful for gaining the necessary NLP skills to interact effectively with ChatGPT and improve the accuracy of the trading bot.
An introduction to statistical learning using R, covering topics such as linear regression, logistic regression, and decision trees. Provides a strong foundation for understanding the statistical concepts behind pairs trading and evaluating the performance of the trading bot.
Provides a comprehensive overview of machine learning in finance, covering topics such as risk management, portfolio optimization, and trading strategies. Useful for gaining a broader understanding of the applications of machine learning in the financial industry.

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