Financial Analysis - Build a ChatGPT Pairs Trading Bot - Pairs Trading Intuition

The video tutorial explores the use of ChatGPT to generate a pairs trading algorithm in Python. It highlights the importance of understanding and analyzing code, identifying mistakes, and correcting them. The tutorial covers key concepts such as Z-scores, spread, Bollinger Bands, and trading signals. It also discusses the calculation of portfolio returns and common errors in code. The instructor emphasizes the need for critical thinking and understanding the limitations of AI-generated code.

What is the initial prompt used to generate the pairs trading algorithm?

What are the two assets mentioned in the context of loading data?

Explain the significance of the Z score in the pairs trading algorithm.

What mistake does the algorithm make regarding the calculation of the mean and standard deviation?

Describe the concept of Bollinger Bands as used in the algorithm.

How does the algorithm determine when to set long and short signals?

What is the error in the way portfolio returns are computed in the algorithm?

What is the correct method to compute total returns when using returns as percentages?

What additional factors could be incorporated to improve the pairs trading algorithm?

Why is it important to understand the thought process behind using ChatGPT for coding?