Don’t understand computer code, but want to do crypto quantitative trading like a scientist?
Don’t understand Python language and want to automate buying and selling through different trading strategies?
Through the powerful code compilation capabilities of GPT4, automated trading becomes possible! And you only need to use natural language and enter Chinese characters! And we are using it to implement complex multi-factor model code compilation! #GPT4 It is possible to make money by helping you trade!
This year we have been committed to the research of #GPT4 . For this purpose, we purchased the H800#AIchip to build Web3-related data models and achieved good results. Targets can be purchased automatically through event driving, and AI trading robots can capture opportunities in real time. In the future, artificial intelligence trading will become mainstream, analyzing data, generating signals, and executing transactions. Its computing speed is faster than humans, 24/7, and has no emotional bias.
This time we use GPT4 to simply demonstrate a strategy used in cryptocurrency: the intraday T+0 momentum trading model. Momentum strategies feature multiple indicators: Moving Averages, MACD, RSI, KDJ, etc. Question: Provide a list of successful cryptocurrency momentum day trading strategies Result: Figure
Come up with the momentum model range I want. Question: Create a momentum trading strategy based on MACD signal on 1 hour time frame. Calculate the winning rate based on a risk-reward ratio of about 1:3, and the final return rate should be at least 20%.
Set a stop loss. Let #GPT4 provide a suggested stop loss range. Question: What is your recommended stop loss level using this MACD based strategy (risk to reward ratio of 1:3 and return of at least 20%)? Strategy: Entry (Buy) Criteria: MACD line crosses above the signal line. Exit (Sell) Criteria: When the MACD line crosses below the signal line, or when Stop Loss or Take Profit is hit.
After the requirements are set up, next, let #GPT4 out of the code. What is required here is the Tradingview Pinecone compiler. You can also request the Python API interface to connect to the exchange. Question: Generate code for this trading strategy for implementation on Tradingview using Pine Editor.
Let #GPT4 suggest some improvements. You can also continuously optimize the code situation. Or add a factor model. Finally, copy and paste the above code directly into Tradingview for implementation. Question: Any ideas to improve this trading strategy?
The above is a complete case of obtaining a quantitative strategy model through (only for simple display). If you like today's article and it is helpful to you, please support it, which is our greatest encouragement. grateful
