AI Trading 2024: From Black Technology to Everyday Tool

AI trading has transformed from a geek's toy into a standard on Wall Street. According to Deloitte's latest report, if 14 top investment banks globally adopt generative AI, front-office productivity could increase by 27%-35%, which means each employee's output could rise by 3.5 million USD by 2026.

What is AI trading actually doing?

In simple terms: algorithms replace the human brain and execute trades at millisecond levels. Machine learning absorbs historical data, market news, and on-chain indicators to identify patterns invisible to the human eye. For example, if you want to track stocks that break through SMA/EMA, AI can directly tell you what the most profitable options strategy was historically—this is a true game changer.

Three Core Technology Stacks:

• Machine Learning: Recognizing price patterns and trends
• Natural Language Processing: Analyzing news and market sentiment
• Real-time Big Data Analysis: Second-level response to market changes

What is the strongest use case? Data processing capability. These platforms can handle 1000 times the amount of data that can be analyzed manually, directly saving 80% of the preliminary work.

But don't overestimate it: Black swan events cannot be predicted, models are too complex to explain, and multiple AIs reacting simultaneously can amplify fluctuations… These pitfalls truly exist.

Future Trend: Deep learning algorithms will become increasingly intelligent, but market regulation will also keep pace. The key is to treat AI as a tool, not as a deity.