In the era of AI quantification, are retail traders' technical analyses in BTC still "naked"?

In the high-volatility 24-hour arena of BTC and gold, if you're still watching MACD or buying on golden crosses, you might already be seen as a "liquidity snack" in the eyes of AI algorithms.

Recently, there has been much discussion about restrictions on quantitative trading. From domestic Fantom Quant's hundreds of billions in annual profits to global trillion-dollar-scale quantitative models, one reality is clear: quant trading is no longer just about speed, but has evolved into a "deep learning" dimensionality reduction attack.

1. Why do regulators want to "cage" quant trading?
Many people don't understand why, since quant provides liquidity, restrictions are necessary.

The reason is simple: algorithm resonance. When BTC hits a key support level, all the quant bots across the network might trigger sell signals simultaneously. This sudden selling pressure can cause market depth to vanish instantly, triggering a chain of liquidations.

Regulatory restrictions on quant are not meant to suppress technology but to prevent this high-performance harvesting machine from pulling out the market’s "roots."

2. What exactly is AI quant trading doing now?
If you think quant is just running fixed indicators, you're very mistaken. Taking the current top AI algorithms as an example:

Emotion detection: They can scan Twitter, Telegram, Reddit for sentiment in milliseconds. Before the news reaches your eyes, positions are already set.

Nonlinear decision-making: AI no longer looks at simple price rises or falls. It calculates the logical relationships among thousands of tiny factors, uncovering entry opportunities that human eyes simply cannot see.

Emotionless betting: BTC markets are easily influenced by emotions, but AI has no fear. While you're hesitating over whether to cut losses, AI calmly executes reverse arbitrage.

3. The truth about retail competition: Cold weapons versus cruise missiles
Liang Wenfeng’s Fantom Quant can earn hundreds of billions, relying on top-tier computing power and talent. In the BTC market, this gap will only become more exaggerated.

As a retail trader, you're watching technical indicators, while quant is calculating your liquidation price; you're waiting for positive news, while quant is using good news to offload. In a trillion-dollar-scale machine game, a retail investor’s "experience" is just a bunch of predictable data to the algorithm.

4. Is a 10% profit share expensive?
I also use quant tools focused on gold and BTC, and many people think 10% profit sharing is expensive.

But in the crypto world, we need to do some math:

Manual retail trading: Due to emotional decision-making errors, drawdowns can reach 30%-50%, or even result in liquidation.

AI quant trading: The goal is a long-term stable curve. Even if 10% of profits are taken, the remaining 90% is still obtained under risk-controlled conditions.

This 10% "technology toll" is essentially your purchase of "algorithm insurance" and a "computing power ticket." In the 24/7 crypto market, fighting AI with human brains is inherently a very high cost.

5. The future belongs to algorithms
Restrictions on quant are for more stable development, but AI replacing manual trading is an inevitable trend.

Future traders will only be two types: those who use AI tools, and those who become AI data samples. In this trillion-dollar game arena, recognizing reality and embracing technology may be the only way out for ordinary people.