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Figure 1 shows my current investment portfolio, which is a strategy that uses AI to screen and track the trading of company insiders for short-term trading. The core idea is to filter out truly valuable buy signals from a large amount of useless information.
First, focus only on small-cap companies, typically those with a market capitalization below $500 million. This is because large companies have transparent information and are fully priced in by institutions, while smaller companies are more prone to information asymmetry.
Secondly, focus on situations where "multiple people buy at the same time." If two or more senior executives (such as the CEO, CFO, etc.) buy company stock within 30 days, this is usually more valuable than a single person's purchase, as it is more likely to represent a unified positive outlook within the company.
Third, we need to exclude "routine purchases." Some executives buy company stock at fixed times every year, but this kind of behavior is not very meaningful. What's truly valuable are non-routine, sudden purchases.
Fourth, assess the scale of the purchase. The key is not the absolute amount, but how important this purchase is to the executive personally. For example, if it accounts for 5% to 10% or more of their annual income, or significantly increases their holding ratio, this kind of behavior is more worthy of attention. Essentially, it's about judging whether they are expressing confidence with real money.
At the execution level, this strategy relies on AI to automatically process data, including scanning publicly disclosed internal transaction information daily and filtering it according to set conditions; otherwise, manual operation would be too inefficient.
After screening, a simple scoring system can be established, taking into account factors such as purchase amount and identity, number of participants, purchase price position, and proximity to the financial report date. The higher the score, the stronger the signal.
In trading, it's generally advisable to buy stocks directly rather than options. Stop-loss orders can be set at recent lows, and the holding period is typically around several weeks to a month, with gradual exits after a significant price increase.
It's important to note that this is not a high-frequency strategy; opportunities are limited, with perhaps only one or two suitable targets appearing every two to three weeks. Furthermore, this method does not guarantee profitability; rather, it aims to improve the win rate by enhancing signal quality.
Overall, the essence of this method is to use AI to screen stocks that are at relatively low prices and where many people within the company have expressed confidence with real funds, and then participate in a possible short-term rise.
Every week I review potential opportunities, track my screening list, and share my market observations and risk analysis. All content I share is free, I do not sell trading signals, subscriptions, or tools.
If you are interested in this research method and discussion, please leave a message or contact me. I am also happy to exchange ideas and learn from each other.