Recently, I've been pondering a question: why do AI trading bots trained on historical data perform so poorly under special market conditions?

I've noticed that many people are overly optimistic about automated trading tools in the crypto market. These trading bots seem very intelligent, but in reality, they all share a fatal flaw—over-reliance on historical data. When the market encounters unprecedented conditions, all historical patterns become invalid.

Imagine if a model is only trained on bull market data; what happens when it suddenly faces a crash? Or when a policy changes abruptly, or market sentiment flips instantly—those algorithms built on past regularities are completely at a loss. Crypto markets are so volatile, and black swan events happen so frequently, that the reference value of historical data isn't that great.

This is also why purely machine learning-based trading systems tend to fail at critical moments. When a new normal in the market emerges, trading bots are like drivers using outdated maps—they simply can't find the way.

So if you're still relying on some hyped-up automation tools, you might need to reconsider. In the unpredictable world of crypto, machine intelligence is far less reliable than staying alert and responding flexibly.