Financial Analysis: Build a ChatGPT Pairs Trading Bot from Udemy

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)

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

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

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

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Financial Analysis: Build a ChatGPT Pairs Trading Bot with these activities:

Review general Python coding

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Review basic Python syntax and coding patterns to ensure course readiness.

Browse courses on Python

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Install Python and set up your development environment
Review basic data structures like lists, dictionaries, and sets
Practice writing simple functions and classes

Review basic statistics and probability

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Review fundamental statistical principles and methods to strengthen understanding for the course's quantitative aspects.

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Review concepts like mean, median, and standard deviation
Practice calculating probability and distributions
Explore basic regression techniques

Explore ChatGPT tutorials and documentation

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Familiarize yourself with ChatGPT capabilities and limitations through official resources.

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Read the ChatGPT documentation and tutorials
Watch video tutorials on using ChatGPT for coding tasks

Five other activities

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Read 'Machine Learning for Algorithmic Trading' by Stefan Jansen

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Expand your knowledge by reading an authoritative book on algorithmic trading and machine learning, complementing the course material.

View Machine Learning for Algorithmic Trading:... on Amazon

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Code simple trading strategies in Python

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Apply your coding skills to develop and test basic trading strategies, solidifying your understanding of the process.

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Create a simple moving average strategy
Implement a trading bot using a pre-defined strategy
Backtest your strategies on historical data

Attend a workshop on algorithmic trading

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Gain practical insights and network with experts by attending a workshop focused on algorithmic trading.

Browse courses on Algorithmic Trading

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Write a blog post or article on ChatGPT for trading

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Cement your understanding and share your knowledge by writing a blog post or article that discusses ChatGPT applications specifically in the trading domain.

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Outline key points and arguments
Write the first draft
Edit and refine the content

Build a pairs trading strategy using ChatGPT and Python

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Integrate your knowledge of ChatGPT and coding to create a functional pairs trading strategy, demonstrating your mastery of the course concepts.

Browse courses on Pairs Trading

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Use ChatGPT to generate a pairs trading strategy
Code the strategy in Python
Test the strategy on historical data
Present your findings in a report

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.

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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.

See salaries and explore the career path for Financial Risk Manager

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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