TrendFi – I built AI trading signals that self-optimize
Hey HN, For the past few years, I've been obsessed with trying to get AI to produce accurate trading signals. The main challenges I found with AI trading models are lack of consistency, context window bottlenecks, hard to backtest, and high cost. Asking ChatGPT "Should I buy Bitcoin today?" doesn't work well because the LLM doesnt have a set trading strategy to opperate from. In addition, the small context window makes it challenging to fit enough historical data into. Not to mention it gets very expensive as well. My solution is a hybrid approach. Instead of having the LLM make direct…
In plain words
TrendFi is an AI trading signal platform that addresses limitations in traditional AI trading models by using a hybrid approach. Rather than relying on large language models to make direct predictions, it uses AI as a conductor to run backtesting simulations on high-performance servers, then self-optimizes parameters after each trade based on results. The system is designed for traders seeking consistent signals that adapt to changing markets while avoiding context window constraints and high costs associated with standard AI approaches.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, For the past few years, I've been obsessed with trying to get AI to produce accurate trading signals. The main challenges I found with AI trading models are lack of consistency, context window bottlenecks, hard to backtest, and high cost. Asking ChatGPT "Should I buy Bitcoin today?" doesn't work well because the LLM doesnt have a set trading strategy to opperate from. In addition, the small context window makes it challenging to fit enough historical data into. Not to mention it gets very expensive as well. My solution is a hybrid approach. Instead of having the LLM make direct predictions, I use AI as the "conductor" in the system that has the ability to run a series of backtesting simulations on high thread count AMD EPYC servers. The AI then processes the results, identifies optimal parameter changes, and can self-optimize after every trade (as needed) to adapt to changing market conditions. This setup uses LLMs for high-level reasoning and CPU cores for what they do best. I should mention that TrendFi is designed as a trend based model. It's not for day trading or catching every small market fluctuation. Its goal is to accurately identify major trend changes and provide clear alerts for those key moments. Check it out: https://trend.fi – Michael
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