A 12-year-old poor student clutched 20 Hong Kong dollars in his hand as lunch money. Every day, at a small convenience store, he bought boxed meals for 12 Hong Kong dollars, and kept the remaining 8 Hong Kong dollars because he was reluctant to spend it. Watching his classmates freely pick out whatever they liked, he felt a build-up of pressure in his heart—how could he change this situation?

This was Cai Jiamin’s earliest introduction to trading. With no capital of his own, he started studying Hong Kong Mark Six by using $5 to buy lottery tickets and dream of an $8 million jackpot. After spending two months analyzing historical data from more than 100 rounds, he finally realized that it was completely a game of randomness. At 14, he borrowed his older brother’s securities account and began trading Hong Kong stocks with red envelope money. That year, he gained 30-plus percentage points—he tasted the sweetness.

But the market soon gave him a lesson. At 16, Cai Jiamin used 10x and 20x leverage to trade bull-and-bear warrants and turbos. The principal of more than 40,000 Hong Kong dollars shrank to only a few hundred overnight. He thought his account had been hacked, and he even didn’t dare tell his family. Later, when chatting with friends, a single sentence from a friend changed his life perspective: “You don’t have kids to raise, and you don’t have a family to take care of—this money doesn’t make much difference to you.” In that moment, he realized that youth was the biggest capital, and the cost of losses was the lowest.

By age 19, Cai Jiamin had accumulated 150,000 Hong Kong dollars through tutoring and entered the market again. This time, he was completely liquidated once more due to aggressive operations. The two experiences of going to zero made him start reflecting—why was he still losing money even after reading the news, looking at charts, and analyzing fundamentals? He began to realize that manual trading was essentially gambling with gut feelings and emotions.

The turning point came. Cai Jiamin discovered the four words “quantitative trading.” He realized he had been ignoring the most critical point all along—using historical data to verify whether a strategy could truly make money. From then on, he gave up fantasies of getting rich overnight and turned to a rigorous, data-driven approach. He began teaching himself to code and backtested every strategy using historical data. If it worked, he invested real money; if it didn’t, he iterated and optimized. “Quantitative trading may waste time, but it won’t waste money.” This became his trading creed.

During university, Cai Jiamin participated in quantitative trading competitions and won awards. With these achievements, he entered a proprietary trading firm. Later, he also joined a hedge fund, working in traditional finance for five years. During those five years, he learned the two most important things: first, data needs to be examined more closely and in greater volume; second, how to manage clients’ expectations—something you can never learn by trading at home on your own.

In 2020, Cai Jiamin began transplanting quantitative strategies from traditional finance into the crypto market. He used medium- to high-frequency CTA strategies (trend trading), judging the direction of Bitcoin and Ethereum based on hourly indications. From May 2021 to January 2023, his account grew from several million Hong Kong dollars to 1 billion Hong Kong dollars—within 1.5 years, a 20x return. After that, his average annual profit stayed around 1 billion Hong Kong dollars, and the annualized return rate exceeded 100%.

Cai Jiamin’s methodology is simple but strict. Step one: determine the trading factors and rules. Step two: use historical data from three to five years for backtesting to verify risk metrics such as the Sharpe ratio, Calmar ratio, and others. Step three: simulate trading for one to two weeks to ensure the system is stable. Only then does he move into live trading, gradually adding positions from small amounts.

He particularly emphasizes the importance of risk management. The drawdowns of CTA strategies can reach 20%-30%, which can make investors nervous. His approach is to distribute the weights of each factor as evenly as possible, to avoid an overall collapse caused by a single factor failing. At the same time, he won’t allow an overly profitable factor to take an excessively large weight—he would rather sacrifice some returns to maintain the stability of the portfolio.

In the 2022 bear market, Cai Jiamin achieved 240% returns by using short-selling strategies. When LUNA blew up, he discovered the risks of the Anchor protocol in advance and carried out precise hedging operations. All of this comes from his sharp insights into data—he looks at things others overlook, such as on-chain data and community sentiment, instead of blindly following charts.

When the AI wave arrived, Cai Jiamin also started experimenting. He trained machine learning models to build two- to three-layer strategies to generate trading signals, and it worked—he made money too. Meanwhile, AI tools greatly improved programming efficiency: what used to require 10 hours of code could now be done in five minutes with ChatGPT. But he also saw the risks: when everyone uses the same AI tools, competitors will become stronger as well. In the future, the deciding factor will be who can use these tools in a more detailed and more efficient way.

From a poor student to a quantitative trading champion with annual earnings of over 1 hundred million, Cai Jiamin has walked the most difficult path. He says there are no naturally gifted trading geniuses—only learning and relentless hard work. Staying rational, correcting cognitive biases in time, and always maintaining a humble mindset—these are the core keys to getting through bull and bear cycles. Today, he not only makes money himself, but also shares and educates others, encouraging more people to do what they truly love rather than doing things they don’t want to do just for money. This is Cai Jiamin’s trading philosophy.