When everyone can use AI to look up information, analyze stocks, and even generate investment strategies, where will the real gap between investors come from? The true difference is no longer just about 'whether or not you’re using AI,' but rather these three things:Whether your data is reliable, whether your process is traceable, and whether you’ve set clear rules for your AI.
It was my honor to be invited by Futu to participate in an offline seminar, where I shared insights on Futubull AI Expert Edition and Skills, demonstrating in detail how toseamlessly integrate real-time market data, community sentiment, unusual capital flows, technical indicators, and your personal investment methodologyinto a customized AI-powered investment research workflow.
1. The first step in AI-driven investing isn’t asking whether a stock will go up or down
There’s an ever-growing flood of information in the market—news, social media, KOL opinions, company announcements, real-time quotes, and countless technical indicators—generating new signals almost every second.The problem is no longer a lack of data, but rather too much of it—and with highly inconsistent sources and quality.Even if a model gives an 'upside probability of 70%' or a 'confidence score of 65 out of 100,' investors still need to know:
① What data did the model use?
② Is the data sufficiently up to date?
③ How are the indicators calculated?
④ Why does it predict an upward move rather than a decline?
⑤ If the result is wrong, which step can be traced back to?
Therefore,When using AI for financial analysis, the first step isn’t to directly ask ‘Which stock should I buy?’ but to first verify whether the data sources and analytical process are reliable.
Futubull Skills...