ChatGPT o1-preview model python strategy made 432% profit (FULL tutorial)

Summary

In this video, the creator explores using OpenAI's new model, GPT-4 (01 Preview), to generate code for an algorithmic trading strategy in the Jesse framework. The strategy focuses on trend-following, using technical indicators for entry and exit signals, filtering ranging markets, and optimizing stop-loss/take-profit targets. Through testing and debugging, the creator improves the strategy’s performance by adjusting time frames and risk parameters, ultimately achieving better profits. The video ends with a giveaway for subscribers, encouraging engagement and feedback for future AI-related content and trading strategies.

Takeaways

• 🤖 OpenAI recently released its new '01 Preview' model, which is said to be PhD-level smart.
• 🧠 The user tested how well the AI model can write a trend-following algorithmic trading strategy in SUO code.
• 💻 The user utilized a custom GPT called 'Jesse' to convert the generated SUO code into Python for algorithmic trading.
• 📈 The strategy created used multiple indicators, including one baseline and another for confirmation, to filter out ranging markets.
• ⏰ The backtesting was performed using a 1-hour chart for entry/exit and a 4-hour chart for big trend analysis, initially leading to errors in execution.
• 🚨 The user encountered common issues during backtesting, such as mismatched names for strategies and incorrect properties like 'histo' instead of 'H'.
• 🔄 After fixing the errors, the algorithm started taking both long and short trades, improving results.
• ⚙️ The strategy was optimized by adjusting the ADX threshold to filter ranging markets, which improved profitability.
• 📊 The final optimization involved changing the trading timeframe to 4 hours and using a 6-hour chart for big trends, achieving 432% profit with a 31% max drawdown.
• 🎁 The video concluded with a giveaway announcement, offering 1 million BNK tokens to a random subscriber.

Q & A

What is the main goal of the video?

The main goal of the video is to demonstrate how OpenAI’s new '01 preview' model can be used to develop a trend-following trading strategy in Jesse by converting pseudo code into Python code.

What is the significance of the '01 preview' model mentioned?

The '01 preview' model by OpenAI is highlighted for its advanced capabilities, as it’s described to be at a PhD level of intelligence. This video explores its utility in creating algorithmic trading strategies.

Why does the presenter use pseudo code instead of direct Python code?

The presenter chose to use pseudo code because ChatGPT is more familiar with general concepts than Jesse-specific syntax, making the initial pseudo code easier to generate and then refine with custom tools.

What is the initial problem encountered when running the generated code in Jesse?

The initial problem encountered was an error related to the mismatch between the strategy name and class name, which is common for beginners using Jesse.

How does the presenter resolve the issue with the Binance exchange name in the code?

The presenter resolves the issue by updating the exchange name dynamically with 'self.exchange' instead of hardcoding 'binance,' which was incorrect for the desired trading environment.

What adjustment does the presenter make to avoid taking trades during a ranging market?

To avoid trades during a ranging market, the presenter adjusts the ADX threshold from 25 to 40, ensuring trades only execute in clearer trending conditions.

What results are achieved after optimizing the strategy with a 4-hour time frame and higher ADX threshold?

After these adjustments, the strategy shows an 87% profit with a maximum drawdown of 10%, indicating an effective trend-following approach and improved profitability.

Why does the presenter increase leverage, and what impact does it have on the results?

The presenter increases leverage to 4x to allow for more capital utilization per trade. This adjustment helps achieve a final result of 432% profit with a 31% maximum drawdown.

What additional plans does the presenter have for the strategy?

The presenter plans to continue refining the strategy, with intentions to release a premium version on the strategy index page of their website, as well as a free version for users to try.

What is the giveaway mentioned at the end of the video?

The giveaway offers a prize of 1 million BNK tokens to a random user who likes the video, posts a comment, and subscribes to the channel. The winner from the previous video is also announced in this segment.