AI Cryptocurrency Trading is currently nowhere near the threshold of trading systems. Six models running simultaneously ended up with two companies not losing, which is essentially equivalent to rolling dice for a good outcome, rather than having a systematic advantage. Especially strategies like deepseek that are almost never short; as long as the market fluctuates slightly upwards during the cycle, it naturally appears decent, but once there is a downward trend, it exposes the fatal flaw of lacking a stop loss mechanism, making it no different from human traders. However, this is very suitable for self-media to generate traffic. Currently, there is not a single large model that can profit stably; I am referring to 'stability' as being able to survive through multiple market cycles. It can summarize the market but does not know how to survive in it, and you can see that the publicly available strategies are all losing. Do not easily follow open-source strategies on GitHub that claim to be profitable; if they could make stable profits, why would they share them with you? Moreover, every time AI generates an answer, even with fixed prompts and temperature parameters, there remains a slight randomness in the model's token sampling, leading to decisions that cannot be reproduced, making it completely a black box. In a highly volatile market, it is inevitable for AI to confidently spout nonsense.

Instead of collecting your own trading data, use LoRA fine-tuning to solidify your trading logic into the model parameters. There is no need to input historical data each time; the model itself has the ability to remember your trading rules, which won't lead to decision drift due to conversation length. Compared to the indiscriminate decisions of general models, your model will accurately mimic your entry preferences, position habits, and risk control logic.