Interview with Cai Jiamin: How to Achieve an Annual Income of Hundreds of Millions Using Algorithms? (Part 2)

Continuing our discussion from the previous article, we'll explore more insightful dialogues. For a recap of the previous article, please click here: "Dialogue with Cai Jiamin: How to Achieve an Annual Income of Hundreds of Millions Using Algorithms? (Part 1)"

IV. Quantitative Trading | A Method for Consistently Making Money

01 Abandon manual trading: The sample data is different, and quantitative trading has already been validated.

Mia : Since this is our first interview with a quantitative trader, from what I've heard about your experience, you transitioned from manual trading to quantitative trading. Most people around you still primarily use manual trading. What efforts did you make to switch from manual to quantitative trading? Did you find it easy?

Calvin Tsai : I think the biggest turning point came after I suffered two consecutive margin calls while trading with manual positions. I realized that this wasn't a stable way to quickly achieve financial freedom. That's when I started researching quantitative trading. I saw that almost all of the world's top ten hedge funds used quantitative trading. There was also a very famous hedge fund—Renaissance Technologies, managed by Jim Simons—that had achieved an annual return of about 67% over forty years, which is an incredible achievement. I studied this company and found that they had been doing quantitative trading forty years ago, and the entire company revolved around quantitative operations. I understood then—quantitative trading had been proven to be a consistently profitable method. So why was I still doing manual trading? Why wasn't I studying quantitative trading? So I abandoned manual trading and officially embarked on the path of quantitative trading.

Mia : Actually, in this process, there are also value investing methods like Livermore's and Buffett's. You chose quantitative trading from among so many types of trading; how did you find it?

Calvin Tsai : If you compare the traders I just mentioned who are very good at short-term trading, or those who make a lot of money through long-term investing—but from a statistical perspective, some people who make a lot of money through long-term trading and investing may simply have bought a stock and held it for thirty years to make money—statistically, this is likely a result of "good luck," rather than having a large sample of data to support the idea that they can consistently make money. Quantitative trading is different. We have hundreds or thousands of trades every day. I wouldn't say that quantitative trading relies on luck. With short-term trading, it's true that some people bought Bitcoin ten years ago and made millions, tens of millions, or even hundreds of millions in their accounts ten years later—but that might really just be because they "happened to buy Bitcoin." If you had bought other altcoins ten years ago, the result ten years later might have been completely different. So a big difference between short-term trading and quantitative trading lies in statistics and mathematics—the sample data is different. Short-term trading may only have one sample, while quantitative trading may have thousands, tens of thousands, or even millions or hundreds of millions of sample data. I am more inclined to believe that quantitative trading can consistently make money.

02 Self-learning methods: Spending time in the library, manual testing, and data verification

Mia : We're quite curious, how did you learn quantitative trading?

Calvin Tsai : It's simple, I know it can make money.

Mia : So how did you learn it? Did you just write your own scripts?

Calvin Tsai : Yes, we started by going to the library.

Mia : Or should I read a book?

Calvin Tsai : Yes, it was all about reading books. Back then in the university library, whenever there was a book on quantitative or systematic trading, I would read it from the first page to the last, taking notes on every single one. That was the first step. The second step was searching online to see if anyone was sharing their knowledge on this topic. It mainly consisted of reading books and learning online.

Mia : So when did you start to find your rhythm in quantitative trading? You mean that feeling of having a very high win rate?

Calvin Tsai : I think it's a gradual, cumulative process. I started by testing with Hong Kong stock data, which was very simple. Since I didn't know programming at first, I used Excel, pulling in 100 days of Hong Kong stock price data, and then gradually expanding—100 days, a year, four years, constantly increasing the data volume. Then I considered different strategies. I would test with data I used to focus on when trading manually. Gradually, you'll find your rhythm, find a set of techniques—how to process different data, how to clean it, how to filter out useless data, and how to uncover useful strategies. I think it really is a step-by-step, gradual process. It's truly hands-on; you have to do it yourself to get that feel for it. Many students say they want to learn, but they only listen to others talk about it; they don't actually open Excel, stock, or cryptocurrency data to try it out. You only experience the learning curve when you actually try it yourself.

03 Market Differences: Cryptocurrency is more volatile than traditional industries

Mia : When you were in traditional finance, how much money did you make through quantitative trading?

Calvin Tsai : In traditional finance, I haven't actually made a lot of money. My company's and my personal trading only amount to a few million Hong Kong dollars. Traditional trading really isn't very profitable. Firstly, the volatility of traditional markets is relatively low. Earning 20% annually is considered very strong among peers. But think about it—if your initial capital is only one million Hong Kong dollars, a 20% annual return is only two hundred thousand Hong Kong dollars. That's not a number that will make you rich overnight, nor will it allow you to quickly achieve financial freedom. But it's different in the cryptocurrency market because the volatility is much higher. Bitcoin's annualized volatility is about 100%, while the annualized volatility of stocks is only 20%, a five-fold difference. So theoretically, earning over 100% annually is not uncommon. This difference in volatility has led to completely different profit margins in traditional and cryptocurrency markets.

Mia : So starting in 2017, you saw the high volatility of Bitcoin and chose to enter the Crypto industry. After entering Crypto, you initially did both, right?

Calvin Tsai : Yes. Initially, I was still trading stocks and commodities. But I'm quite risk-averse—after all, I still remember my two previous margin calls. So, at first, I didn't dare put all my money into crypto; it was a gradual process. I really saw—OK, this strategy is making more money this month than the traditional market. Traditional markets might only make 2% this month, while crypto might make 20%. So, I slowly moved my money in month by month. So, the funds gradually shifted from the traditional market to the crypto market, step by step.

04 Turning Money into Numbers: Focus Your Concentration and Capital on Major Cryptocurrencies

Mia : So back then, in just a year and a half from 2017, you went from a few million to hundreds of millions. Did you ever feel like, "Wow, I'm a chosen one"?

Calvin Tsai : No, I wouldn't feel that way. Because I've had two margin calls before—that's the key point.

Mia : It left a deep impression on me.

Calvin Tsai : Why did you use high leverage in your two previous margin calls? As I just mentioned, I lost money at 16 and 19 because of leverage. Why did I use leverage back then? Because after making money for several months in a row, I thought—OK, I'm a god, I'm a stock market genius! Buffett only makes 20% a year, and I make 20% in a month. I thought, if I increase the leverage from 1x to 20x, or even 100x, the money I make won't be so small. So, I made that mistake twice. By 2021 and 2022, when I was making a lot of money, I no longer had that "I'm a chosen one" feeling. The mistakes I made before taught me lessons, so making money was just a number to me. I might make a million a day, but I wouldn't feel anything.

Mia : So, in 2017, were you doing quantitative trading in major cryptocurrencies or minor cryptocurrencies?

Calvin Tsai : A major cryptocurrency, also a major cryptocurrency.

Mia : So you've been trading major cryptocurrencies all this time?

Calvin Tsai : Yes, I did test smaller cryptocurrencies. Theoretically, smaller cryptocurrencies do offer more opportunities because many large institutions are focused on larger cryptocurrencies and wouldn't try to profit from smaller ones. Theoretically, you should be more profitable with smaller cryptocurrencies. However, as my capital grew, it became less convenient. Smaller cryptocurrencies lack market depth and trading volume; sometimes when you place an order, you have to wait a long time for it to be executed, which affects the return on investment. So, I eventually focused my attention and capital on larger cryptocurrencies.

V. Beyond Trading | Market Outlook, Rational Living, and the Essence of Passion

01 Market Outlook: Driven by Institutions, Cryptocurrencies May Develop Different Indices

Mia: So how do you assess the current landscape of the crypto market? How does it differ from previous cycles?

Calvin Tsai : Yes, this cycle is very different. In the past, like the bull market of 2021, it was driven by retail investors; a lot of retail money rushed in, buying contracts and chasing the rise. But this time, starting around 2020, especially after the launch of spot ETFs, it's been more institutional buying. The data I've seen, whether on-chain or market data, shows that institutional funds are driving this bull market. For example, Bitcoin rose from $60,000-$70,000 to $120,000, mostly due to institutional buying. And in the last six months to a year, many institutions have planned to use company funds to buy Bitcoin, perhaps 1% or 3%, so institutional funds are the main driver of the market. Conversely, this time there isn't the atmosphere of retail investors using 20x or 50x leverage to chase the rise, as was the case in 2021. Therefore, compared to the previous bull market, this one has lower volatility, smaller drawdowns, and healthier market depth and trading volume. This is a very significant difference compared to 2021.

Mia : So, do you think that, as you just mentioned, the gradual entry of traditional financial institutions, including ETFs, into the crypto market is a good thing or a bad thing for quantitative traders?

Calvin Tsai : It has its pros and cons.

The good thing is that trading volume has increased, and market depth has increased. Theoretically, we can manage a larger amount of capital and accommodate more funds for trading, which is an advantage.

Mia : What about the downsides?

Calvin Tsai : The downside is that traditional institutions are also starting to get interested. They've found that ETFs are convenient, allowing them to buy Bitcoin directly without having to go through different channels. I've heard that many institutions that hadn't touched Bitcoin before have started researching Bitcoin strategies this year, as well as strategies for different cryptocurrencies.

Mia : Has the competition intensified?

Calvin Tsai : Yes, the entry of different institutions has indeed intensified competition. However, I would say this has both advantages and disadvantages. Previously, many large funds and institutions would resist Bitcoin at the mere mention of it. They felt that if traditional investors weren't touching it, they shouldn't either—the risk was too high. But now, with the increasing number of ETFs and more institutions holding Bitcoin, they are gradually developing an interest. They will proactively ask, "Can I invest in you? How do I buy Bitcoin?" This is also a great opportunity for us.

Mia : So you think that with market efficiency gradually increasing, some small and medium-sized quantitative trading teams may find it difficult to survive. What advice would you give them? How can they survive in such a competitive market?

Calvin Tsai : It is indeed quite difficult, because I myself run a small team, so I understand this deeply. For example, in the past, there were dozens of high-frequency trading institutions (HFDIs) in the US, Hong Kong, and A-share markets. But now, if you look at Hong Kong, US, and A-share markets, there are probably only a dozen or so HFDIs left, and they are basically the top, wealthiest, and fastest institutions, taking the lion's share of the profits. Small and medium-sized teams have had much of the money they could have earned taken by these large institutions. So, I think the advantage of small and medium-sized teams lies in their lower communication costs. Fewer people, fewer meetings, less management—that's the advantage of small teams. I suggest that small and medium-sized teams try to learn from large institutions. I myself am also struggling to survive, and I refer to large institutions—large institutions in Hong Kong and US stock markets, etc.—to see how they operate and learn from their structures and methods. I think small and medium-sized teams should try to learn from the survival strategies of some highly profitable large institutions.

Mia : Looking ahead to the next two to three years, what do you think will be the most promising trend or potential breakout point?

Calvin Tsai : I think a key point is the gradual entry of institutions into the cryptocurrency market. You see, compared to the traditional stock market, there's still a lot of room for growth. For example, traditional markets have many indices, but there isn't a large index tracking cryptocurrencies yet. Also, many pension funds can buy stocks, bonds, and foreign exchange, but many retirement funds can't buy Bitcoin. I think a huge opportunity lies here—how traditional institutions can accept and embrace Bitcoin as a new asset. So I think this will be a key focus for the next two to three years; there should be many different funds allowing clients to buy Bitcoin, and different indices will also be developed.

Mia : I understand. I have another interesting question. How do you view publicly discussing quantitative strategies like this? What strategies would you disclose publicly, and what strategies would you absolutely never share?

Calvin Tsai : For example, the fund size, strategy direction, strategy type, and our way of thinking that we just mentioned are things we can share. But if we're talking about my most profitable strategy, or the strategy parameters, indicators, programming methods, machine learning models, etc., those are more sensitive. In terms of frequency, high-frequency strategies are usually not shared. High-frequency methods may be similar to others, but they gain an advantage through speed, so you won't see high-frequency traders sharing their insights. Low-frequency views can be shared, such as my target price for Bitcoin next year, or the development of Bitcoin in the next few years—these are things that can be made public. So we have things we can share, and we also have money-making methods that need to be kept secret. We can't talk about how we make a living. I also enjoy education and have been teaching and sharing locally since 2017. We mainly share methodologies and directions. For example, understanding Bitcoin, quantitative trading, and data acquisition—these broad directions are worth learning. The real details of the strategies still require you to innovate and learn on your own. Even if you're given a strategy directly, if you don't know how to adjust it next month or how to improve it if it fails, you still won't make money. The core is to truly understand and master the entire method.

02 In daily life: I don't have strong material desires, and I usually enjoy playing Texas Hold'em.

Mia : Yes, now that we've finished discussing trading, I'd like to talk about Kaiwen, who's also a very interesting person. Let's talk about your personal life and values outside of trading. What's your life like outside of trading? I heard that you try to solve all kinds of problems in your life using data?

Calvin Tsai : Yes, it's quite rational. I think this job has made me more rational in my life as well. Because we have to look at a lot of data at work, and then use the data to make judgments and draw conclusions, my daily life has also become more quantitative. Yes, I'm more sensitive to data.

Mia : Do you have any specific examples you can share with us?

Calvin Tsai : For example, let me give you a rather exaggerated example. When I go to a convenience store with a friend to buy water, I can immediately tell which bottle is the cheapest. Each bottle has a different capacity—500ml, 700ml, 300ml—and the price varies accordingly. As a trader, I'm quite sensitive to numbers, so I can tell at a glance which bottle offers the best value. Or, when I go to a coffee shop, I can quickly calculate which is the most cost-effective by looking at the large, medium, and small cups and their prices.

Mia : Have you been very good with numbers since you were a child?

Calvin Tsai : No, I only developed that feeling later through education and training.

Mia : Oh, I thought you discovered your talent for numbers when you were 12 years old, that kind of innate feeling.

Calvin Tsai : No, not really. My math in elementary and middle school wasn't top-notch either. I participated in the Mathematical Olympiad before, but I didn't win any prizes.

Mia : So, if you started learning trading after the age of 12 and began practical trading at the age of 14, would that have improved your math skills?

Calvin Tsai : No, not at all. Because the mathematics used in trading is quite different from the mathematics learned in school. In addition to mathematics, it also requires statistical logic and an understanding of the market. It's the result of a combination of multiple abilities, not just mathematics itself.

Mia : What's your personal life like outside of trading? Do you have any hobbies?

Calvin Tsai : Yeah, besides trading, my favorite thing is definitely trading. Besides trading, I also like playing Texas Hold'em.

Mia : Oh, actually it's another kind of thing...

Calvin Tsai : Yes, Texas Hold'em is actually quite similar to trading. It involves risk management and bankroll management. You need to observe the personalities and playing styles of different people at the table, and calculate the odds of winning on different hands. You need to know when to decisively abandon a strategy, and which hand you shouldn't invest in when you don't have an advantage. It's very similar to market trading.

Mia : I understand. So, when you went through a period of extreme poverty and then eventually became a billionaire, did it affect your life? Did it change anything?

Calvin Tsai : Not much has changed. Because most of my money is still in trading, yes, in Bitcoin and trading. I don't have a strong materialistic streak, so my lifestyle hasn't changed much.

03 Driving force: Liking the trading itself more than liking the money

Mia : We've noticed a phenomenon among other traders we've encountered: after making a lot of money, they might lose interest in making money or even trading itself. I saw in a previous interview that you mentioned that you felt there wasn't much difference in happiness between 30 million HKD and over 100 million. So how do you maintain your interest in trading and keep pushing yourself forward?

Calvin Tsai : I think some traders lose interest after making money because they didn't originally enjoy trading; they traded for the money. I initially traded for money too, but I gradually realized that I enjoy trading itself more than the money. Money is just a "score" in trading, like a level in a game; it proves your methods and ideas are correct. What truly makes me happy is the trading process itself. I enjoy seeing my progress. For example, before, I might not have been able to think of a good method for a strategy, but now, seeing a set of data, I can quickly come up with a strategy. Facing different risks, I can continuously optimize my methods. This sense of satisfaction from progress is my source of happiness, not the amount of money I have or how many sports cars I can buy. For me, opening my account is like looking at a game score. Before, my level was 10; now it's 100—it's just a number. The greatest significance is the satisfaction I feel from my own progress.

Mia : Your car is really cool. After you made money, what was your most extravagant or most rational purchase?

Calvin Tsai : Theoretically, I don't think I've ever made any extravagant purchases. I haven't spent large sums of money on entertainment or other things. My most rational spending is actually on the essence of trading, such as buying data to backtest strategies. Data is actually quite expensive; if you buy some high-frequency data, it can cost hundreds of thousands of Hong Kong dollars a year. I think this money is well spent because the satisfaction is long-lasting. Buying sports cars, watches, or luxury goods might only bring satisfaction for a few weeks, a month, and then you'd want to buy a better sports car or a more expensive watch to stimulate yourself, but I'm not that kind of person. I prefer self-actualization and self-achievement; that's the long-term source of happiness.

04. Engage in education: Encourage more people to do what they truly want to do.

Mia : I understand. So, many people who are new to this industry have made some money, some through manual trading, and some through on-chain trading. If they want to switch to a more stable trading method, what advice would you give them?

Calvin Tsai : Learning quantitative trading.

Mia : So what kind of person is suitable to learn quantitative trading?

Calvin Tsai : I think people who don't resist numbers are suited to learn quantitative trading. I've taught many students, some successful, some unsuccessful. I've found a major point is that some people who haven't succeeded after studying for six months or a year actually had a headache from math since childhood and a resistance to numbers. Quantitative trading requires dealing with a large amount of data, finding patterns, and adjusting parameters, which involves a lot of numbers. So the two most important things are: logical ability and an inability to resist numbers.

Mia : Besides that, what else do you think is more important for a quantitative trader to do well?

Calvin Tsai : Stay rational. Many people who do quantitative trading, seeing others make ten times their initial investment through manual trading or hundreds of times their initial investment through cryptocurrency, will switch back to manual trading. This shows a lack of rationality. They are misled by short-term profits, affecting the execution of their long-term strategy. Therefore, the most important thing is to stay rational, believe in your method, and believe in the strategy you have.

Mia : So, you're saying you should focus on what you choose to focus on, instead of going wherever the money is. Since you also teach quantitative trading, are you worried that if more quantitative traders enter the industry and learn this method, it will make the industry even more competitive?

Calvin Tsai : Theoretically, the answer is yes, it is. I think this is an excellent question; few people ask it in other interviews, but it's very important. Why do I still teach others? Honestly, I derive great satisfaction and a sense of accomplishment from teaching. Over the past few years, I've taught people who have grown their fortunes from hundreds of thousands to tens of millions, even hundreds of millions, achieving financial freedom. In a capitalist society, the faster you make money, the faster you can enjoy freedom and do what you truly want to do, instead of doing things you don't want to do for money. Seeing these students make money and achieve their life goals gives me more satisfaction than making a hundred or two hundred million more. So, I find that spending time and energy on teaching is something that makes me very happy. In the past, if I had suffered a financial blowout and lost all my capital, I might have focused on going home and developing strategies instead of sharing and educating. But now, I find that education is something that brings me immense joy.

Mia : I understand. So, how many of the people you brought out have made a lot of money so quickly, as you said? Do they have anything in common?

Calvin Tsai : More than a dozen of my high school and college classmates have achieved financial freedom. Actually, you're within reach of them, and you have the opportunity to achieve financial freedom. The key is that they understand quantitative trading and are interested in learning about it. But I must say, it's really not easy. I've talked to many people about Bitcoin and quantitative trading, but about eight out of ten aren't interested, only two are genuinely interested in studying it in depth, and of those two, one might give up halfway through. The dozen or twenty people you just heard about are actually only a small fraction of the many, so no stage is easy.

Mia : I understand. So, in this process, some people didn't learn it. Could it be because you didn't explain it well enough and didn't teach them?

Calvin Tsai : I think it depends more on the individual. The methods and content I teach are the same, but whether they learn it or not really depends on themselves. The key is whether they seriously try to understand it or treat it as a cash cow. If you don't understand Bitcoin and only think about doubling your money tomorrow or next month, you usually won't be able to hold on. Why can some people hold for five or ten years, while others sell after a few months? Essentially, it's about whether they understand what Bitcoin is and why they should buy it. In trading, I've concluded that the biggest difference between traders who don't make money and those who do is their motivation. People who don't make money are usually doing it to make money, to buy a sports car, while those who truly make money are passionate about trading itself. They're happy when they see prices on each exchange tending to balance, validating that their strategy is profitable. They don't trade to satisfy material desires, but to truly do trading well. So making money is actually just a byproduct of doing what you love. When you chase after making money as a goal, it's easy to affect your mindset and won't yield good results.

05 Advice for beginners: Hard work is more important; stay rational, keep a broad perspective, and maintain a learning mindset.

Mia : Do you think trading requires talent? Do you think anyone can replicate you?

Calvin Tsai : I think hard work is more important than talent. No one is born knowing how to trade, whether it's manual or quantitative trading; everyone learns step by step. I also lost a lot of money trading manually at first, including two huge losses, before I truly learned. So I think it's 100% about hard work.

Mia : What about beginners? Some quantitative trading beginners may think that quantitative trading is a sure-fire way to make money. What advice would you give them?

Calvin Tsai : The world is fair; there's no such thing as a guaranteed profit. It always requires time and effort. Even the simplest thing—putting money in a bank—isn't guaranteed to make a profit; many banks have collapsed throughout history. Therefore, there's no such thing as a free lunch. You have to do what others haven't done to earn money that others can't earn.

Mia : What advice do you have for this new generation of young people who want to learn quantitative trading or manual trading, or who want to get into Crypto?

Calvin Tsai : I think there are a few key points. First, stay rational. Many people lose their rationality when they lose a lot of money; they become irritable, and their emotions are affected by the losses, making it impossible to analyze clearly. The first step is to manage your emotions, remain stable and rational, so that you can clearly analyze numbers, logic, and methodology. Second, reduce human biases. What are human biases? For example, you might think, "I haven't lost money as long as I haven't sold this coin," or "I've held it for several months; if I keep holding, it will increase tenfold next year." You need to understand the pitfalls in your thinking and strive to correct them. Third, keep a broad perspective. You need to realize that there are many things beyond your current understanding. I've been studying quantitative finance for a long time, but I've always maintained a learning mindset. I know there's still much I don't know, and much I've overlooked. I will find it and learn it. Many people think, "I already know a lot," but they haven't seen what they haven't seen—the "unknown unknown." Therefore, I always maintain a learning mindset. Even if I see other educators and I might perform better than them, I still feel that they have something I can learn from them.

Mia : I understand. So, first, stay rational; second, avoid prejudice; and third, maintain an open and learning mindset. Actually, Kelvin emphasized rationality throughout the whole process. Do you think that when you become an absolutely rational person, won't the people around you feel that you have few emotional fluctuations and are somewhat cold-hearted?

Calvin Tsai : Yes, some people might feel that way, thinking I lack humanity. But I believe trading and life can be separated. At a certain point, you can separate them, as long as it's done rationally.

Mia : So how do you balance it?

Calvin Tsai : Balance things rationally. When dealing with people, when you don't need to be rational, you can be more emotional, more caring, and try to understand their feelings.

Mia : But once you've become accustomed to rationality, how do you bring out your emotions? For example, how do you balance rationality and emotion when interacting with family, friends, or in close relationships?

Calvin Tsai : Still learning.

Mia : Okay, thank you so much for this interview with Calvin today. It filled many gaps in our series on quantitative trading and conversations with traders. We'll be compiling this video into a program, and you're welcome to follow Calvin on Twitter and Telegram, as well as his quantitative fund. Calvin is currently working on some investment projects, and if you'd like to learn more, feel free to contact him anytime to learn about the "secrets" of his strategies that can't be publicly discussed. Okay, that concludes this interview. Bye!

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