Continuing from the previous discussion, we continue to explore more exciting dialogues. For a recap of the previous article, please click on "Dialogue with Cai Jiamin: How to Achieve an Annual Income of Over 100 Million with Algorithms? (Part 1)"
IV. Quantitative Trading ｜ A Sustainable Way to Make Money
01 Give Up Manual Trading: Sample Data is Different, Quantitative Trading has been Verified
Mia: Since this is our first interview with a quantitative trader, I noticed that you transitioned from manual trading to quantitative trading. Most people around you still primarily engage in manual trading. During this process, what efforts did you make to shift from manual to quantitative trading? Did you find it easy?
Calvin Tsai: I think the biggest change actually stemmed from my two consecutive blow-ups while trading manually. I realized that this was not a stable method that could quickly lead me to financial freedom. At that time, I began to study quantitative trading. I saw that almost all of the top ten hedge funds globally use quantitative trading methods. There is a very famous hedge fund—Renaissance Technologies, managed by Jim Simons, which has achieved an annual return of about 67% over the past forty years, which is an extraordinary achievement. I researched this company and found that they started quantitative trading forty years ago, and the entire company operates around quantitative methods. I understood that quantitative trading has been validated and is a method that can continuously make money. So why was I still doing manual trading? Why not study quantitative trading? So I gave up manual trading and officially embarked on the path of quantitative trading.
Mia: In this process, there are also trading methods like Livermore's and Buffett's value investing. How did you find quantitative trading among so many trading types?
Calvin Tsai: If you compare those strong manual traders or long-term investors who make big money, from a statistical perspective, some people who trade long-term or invest long-term may just have bought a stock and held it for thirty years to make money. Statistically, this could very well be a result of "good luck," rather than being supported by a large sample of data that proves they can continuously make money. Quantitative trading is different. Every day we have hundreds or thousands of trades. I wouldn't say quantitative trading relies on luck. In manual trading, there are indeed people who bought Bitcoin ten years ago and now have made millions or even billions in their accounts—but that could just be a case of "happening to buy Bitcoin." If you had bought other altcoins ten years ago, the outcome could have been completely different. So a significant difference between manual trading and quantitative trading lies in statistics and mathematics—the sample data is different. Manual trading might only have one sample, while quantitative trading could have thousands, tens of thousands, or even millions or billions of sample data. I tend to believe that quantitative trading can continuously make money.
02 Self-Learning Method: Spending Time in Libraries, Manual Testing, and Validating Data
Mia: We are quite curious, how did you learn quantitative trading?
Calvin Tsai: It's simple; I knew it could make money.
Mia: So how did you learn? Did you write scripts yourself?
Calvin Tsai: Yes, I started by going to the library.
Mia: Just reading books?
Calvin Tsai: Yes, just reading books. At that time, in the university library, I would read every book that mentioned quantitative trading or systematic trading from the first page to the last, taking notes on each one. That was the first step. The second step was to search online to see if anyone shared knowledge in this area. Mainly, it was about reading books and learning online.
Mia: When did you start to feel that you had a grasp of quantitative trading? That feeling of having a very high win rate?
Calvin Tsai: I think it was a gradual accumulation process. At first, I used Hong Kong stock data for testing, which was very simple. I didn't know how to program, so I used Excel to pull in a hundred days of Hong Kong stock price data, and then gradually expanded it—one hundred days, one year, four years, continuously increasing the data volume. Then I would think about different strategies. I would take the data I focused on during manual trading to test. Slowly, you start to find a feeling, a set of techniques—how to handle different data, how to clean it, how to filter out useless data, and how to mine useful strategies. I really believe it’s a step-by-step, gradual process. It’s truly hands-on; you have to do it yourself to get that feeling. Many students say they want to learn, but they only listen to others and don’t actually open Excel or stock or cryptocurrency data to try. You really have to get your hands dirty to experience that learning curve.
03 Market Differences: Cryptocurrencies are More Volatile than Traditional Industries
Mia: How much did you earn from quantitative trading when you were in traditional finance?
Calvin Tsai: In traditional finance, I actually didn’t make much, maybe a few million Hong Kong dollars combined with my personal trading. Traditional trading really wasn’t very profitable. The first point is that the volatility in traditional markets is relatively low; earning 20% a year is already considered strong among peers. But 20%, think about it—if the principal is only one million Hong Kong dollars, earning 20% a year is only two hundred thousand Hong Kong dollars. That’s not a number that can make you rich quickly or achieve financial freedom. But in the crypto space, it’s different because the volatility is much higher. The annualized volatility of Bitcoin is about 100%, while the annualized volatility of stocks is only 20%, which is a five-fold difference. So theoretically, earning over 100% a year is not uncommon. The difference in volatility has already led to completely different profit margins in traditional markets and cryptocurrency markets.
Mia: So starting from 2017, you saw the high volatility of Bitcoin and chose to enter the crypto industry. When you entered crypto, you were doing both sides at first, right?
Calvin Tsai: Yes. At first, I was still trading stocks and commodities. But I was inherently risk-averse—after all, I had experienced two blow-ups before. So initially, I didn’t dare to put all my money into cryptocurrencies; it was a gradual process. I really saw—OK, this strategy made more money this month than the traditional market. The traditional market might only earn 2% this month, while cryptocurrencies might earn 20%. So I gradually moved my money over month by month. Thus, the funds slowly transitioned from the traditional market to the crypto market, step by step.
04 Turning Earnings into Numbers: Focusing Attention and Funds on Major Coins
Mia: So at that time, from 2017, after a year and a half, you turned a few million into over a hundred million. Did you ever feel like, "Wow, I’m the chosen one"?
Calvin Tsai: No, I didn’t have that feeling. Because I had blown up twice before—that’s also key.
Mia: That left a deep impression.
Calvin Tsai: In those two previous blow-ups, why did I encounter high leverage? As I mentioned, I blew up at 16 and 19 because of leverage. Why did I encounter leverage back then? It was because I had been making money for several months in a row, and I thought—OK, I’m a god, I’m a stock god! Buffett only earns 20% a year, and I earn 20% a month. At that time, I thought, if I increase my leverage from one times to twenty times, or even a hundred times, the money I earn wouldn’t be so little. So I had already made that mistake twice. By 2021 and 2022, when I was making a lot of money, I completely didn’t have that "I’m the chosen one" feeling. The mistakes I had made before taught me a lesson, so making money was just a number to me. I could earn a million in a day, and I felt nothing.
Mia: So at that time in 2017, were you doing quantitative trading with major coins or small coins?
Calvin Tsai: Major coins, yes, major coins.
Mia: So you have been focusing on major coins until now?
Calvin Tsai: Yes, I tested small coins in between. But theoretically, small coins do have greater opportunities because many large institutions are trading major coins; they won’t go after small coin profits. Theoretically, trading small coins is more profitable. However, as my capital scale grew, it became inconvenient. The market depth for small coins isn’t enough, and the trading volume isn’t sufficient. Sometimes when you place an order for small coins, you have to wait a long time for it to execute, which affects the return rate. So I later decided to focus my attention and funds on major coins.
V. Beyond Trading｜Market Outlook, Rational Living, and the Essence of Passion
01 Market Outlook: Institution-Driven, Cryptocurrencies May Give Rise to Different Indices
Mia: How do you evaluate the current landscape of the crypto market? How does it differ from previous cycles?
Calvin Tsai: Well, there is a significant difference in this cycle. For example, the bull market in 2021 was driven by retail investors; a lot of retail money flowed in, buying contracts and chasing prices. But this time, starting around 2020, especially after the introduction of spot ETFs, it’s more institutions buying in. The data I’ve seen, whether on-chain data or market data, shows that institutional funds are driving this bull market. For instance, Bitcoin rose from $60,000 to $120,000, and most of that was due to institutional buying. Moreover, in the past six months to a year, many institutions plan to use company funds to buy Bitcoin, with proportions possibly being 1% or 3%, so the main driving force behind the market is institutional funds. Conversely, this time there isn’t the same atmosphere as in 2021, where retail investors were using 20x or 50x leverage to chase prices. So this bull market has lower volatility compared to previous ones, with less drawdown, and the market depth and trading volume are healthier. This is a very significant difference compared to 2021.
Mia: Do you think that, as you just mentioned, traditional finance, including ETFs and other funds, gradually entering the crypto market is a good or bad thing for quantitative traders?
Calvin Tsai: There are pros and cons.
The good part is that trading volume has increased, and market depth has deepened. Theoretically, we can operate with larger capital scales and accommodate more funds for trading, which is a benefit.
Mia: And the downsides?
Calvin Tsai: The downside is that traditional institutions are also starting to show interest. They find that, for example, ETFs are very convenient, allowing them to buy Bitcoin directly without needing to operate through different channels. I’ve heard that many institutions that hadn’t touched Bitcoin before are now researching Bitcoin strategies and different coin strategies this year.
Mia: The competition has intensified?
Calvin Tsai: Yes, with different institutions entering, competition has indeed intensified. However, I would say there are both benefits and drawbacks. Previously, some large funds and institutions would resist Bitcoin. They thought, since traditional investors don’t touch it, we won’t either; the risk is too high. But now, with more ETFs, more institutions are starting to hold Bitcoin and are gradually becoming interested. They will proactively ask, "Can I invest in you? How do I buy Bitcoin?" This is also a great opportunity for us.
Mia: Do you think that the market efficiency is gradually improving, making it difficult for some small to medium-sized quantitative teams to survive? What advice would you give them? How can they survive in such a competitive market?
Calvin Tsai: It is indeed a bit difficult because I am also part of a small team, so I have a deep understanding of this. For example, in the past, there were many high-frequency institutions in the US, Hong Kong, or A-shares, with dozens of them. But now, if you look at the Hong Kong, US, or A-share markets, there may only be a little over ten high-frequency institutions left, and they are basically the top, wealthiest, and fastest institutions that have taken most of the money. Many of the profits that small and medium teams could have earned have been taken by large institutions. So I think, what is the advantage of small and medium teams? I believe it lies in lower communication costs. Fewer people mean fewer meetings and less management, which is the advantage of small teams. I suggest that small and medium teams learn as much as possible from large institutions. I am also striving to survive, and I refer to large institutions: large institutions in the Hong Kong market, large institutions in the US market, etc., to see how they operate and learn from their structures and methods. I think small and medium teams should try to reference the survival methods of large institutions that are very profitable.
Mia: Looking ahead to the next two to three years, what trends or potential breakout points do you think are most promising?
Calvin Tsai: I think a key point is that institutions are gradually joining the cryptocurrency market. You see, there is still a lot of room for development compared to traditional stock markets. For example, there are many indices in traditional markets, but there is currently no large index to track cryptocurrencies. Additionally, many pension funds can buy stocks, bonds, and foreign exchange, but many pension funds or retirement funds still cannot buy Bitcoin. I think there is significant room for development here—how traditional institutions will accept and embrace Bitcoin as a new asset. So I believe this area will be a focus in the next two to three years, and there should be many different funds that allow clients to buy Bitcoin, and different indices will also develop.
Mia: I understand. I have another interesting question: how do you view public discussions about quantitative strategies? What are some things you would share, and what are some things you would absolutely not disclose?
Calvin Tsai: For example, the scale of funds, the direction of strategies, the types of strategies, and our thought processes are things that can be shared. But if we talk about my most profitable strategies, or the parameters of the strategies I am currently using, what indicators I use, what programming methods, machine learning models, etc., those are more sensitive. In terms of frequency, high-frequency strategies are usually not shared. The methods for high-frequency trading may be similar to others, but they rely on speed for their advantage, so you won’t see high-frequency traders coming out to share. Low-frequency insights can be shared, such as my target price for Bitcoin next year or the development of Bitcoin in the coming years; these can be made public. So we have points we can share, as well as profitable methods that need to be kept confidential. The methods for making money cannot be disclosed. I also enjoy education; since 2017, I have been teaching and sharing locally, mainly sharing methodologies and directions. For example, understanding Bitcoin, quantitative trading, and data acquisition—these broad directions are worth learning. The real detailed strategies still need to be innovated and learned on one’s own. Even if I directly give you a strategy, if you don’t know how to adjust it next month or how to improve it when the strategy fails, you still won’t make money. The core is to truly understand and master the entire method.
02 In Life: No Strong Material Desires, Enjoys Playing Poker
Mia: Right, now that we’ve talked about trading, I want to discuss you as a person, which is also very interesting. Let’s talk about your personal life and values outside of trading. What is your life like outside of trading? I heard that you tend to think of using data to solve all problems in life?
Calvin Tsai: Yes, I am quite rational. I think this job has made me more rational in life. Because we have to look at a lot of data at work and use data to make judgments and draw conclusions, my everyday life has also become more quantitative; yes, I am sensitive to data.
Mia: Do you have any specific examples you can share with us?
Calvin Tsai: For example, I’ll give a rather exaggerated example. When I go to a convenience store with friends to buy water, I can immediately tell which bottle of water is the cheapest. Each bottle has different capacities—500ml, 700ml, 300ml—and the prices vary. As a trader, I am sensitive to numbers, so I can quickly identify which bottle has the best cost-performance ratio. Or when I go to a café, I can quickly calculate which size cup—small, medium, or large—offers the best value based on capacity and price.
Mia: Have you always been sensitive to numbers since you were young?
Calvin Tsai: No, I developed this sensitivity later through education and training.
Mia: Oh, I thought you discovered your talent for numbers at the age of 12, that it was an innate feeling.
Calvin Tsai: Not really. My math in elementary and middle school wasn’t exceptional. I participated in the Math Olympiad before, but I didn’t win any awards.
Mia: So after you started learning trading at 12 and began actual trading at 14, did that improve your math skills?
Calvin Tsai: No, it didn’t. Because the math used in trading is quite different from what is learned in school. Besides math, it also involves statistical logic and an understanding of the market. It can be said that it is a combination of various abilities, not just math itself.
Mia: What is your personal life like outside of trading? Do you have any hobbies?
Calvin Tsai: Well, besides trading, my favorite thing is still trading. Apart from trading, I also enjoy playing poker.
Mia: Oh, that’s actually another form of…
Calvin Tsai: Yes, poker is very similar to trading. Because it also involves risk management and capital management. You have to observe the personalities and playing styles of different people at the table, and you also need to calculate the winning probabilities of different hands. You need to know when to decisively abandon a strategy and when not to invest in a hand when you have no advantage. This is very similar to market trading.
Mia: I understand. When you have gone through a very poor phase and then later reached billionaire status, has that affected your life? Has it changed?
Calvin Tsai: Not much has changed. Because most of my money is still invested in trading, yes, in Bitcoin and trading. I personally do not have strong material desires, so my lifestyle hasn’t changed much.
03 Driving Force: Enjoying Trading Itself More Than Money
Mia: We have encountered a phenomenon with other traders, which is that when they make a lot of money, they may lose interest in making money or even trading. I saw in your previous interview that you mentioned the difference in happiness between 30 million Hong Kong dollars and over 100 million is not significant for you. So how do you maintain your interest in trading and continue to drive yourself forward?
Calvin Tsai: I think some traders lose interest after making money because they were never really passionate about trading; they were trading for the money. I initially traded for money too, but later I gradually realized that I enjoy trading itself more than I enjoy money. Money is just a "score" in trading, like a level in a game; it proves that your method is correct and your ideas are right. What truly makes me happy is the process of trading itself. I enjoy seeing my progress. For example, when I used to develop a strategy, I might not have thought of a good method, but now when I see a set of data, I can quickly come up with a strategy. When facing different risks, I can continuously optimize my methods. The satisfaction that comes from this progress is the source of my happiness, not how much money I have or how many sports cars I can buy. For me, opening my account is like looking at a game score. My level used to be 10, and now it’s 100; it’s just a number. The greatest significance is the satisfaction I feel from my own progress.
Mia: Your sports car is very cool. After making money, what is the most extravagant or rational purchase you’ve made?
Calvin Tsai: Theoretically, I don’t think I’ve made any extravagant purchases. I haven’t spent a lot 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 can be quite expensive; if you buy some high-frequency data, it might cost hundreds of thousands of Hong Kong dollars a year. I think that money is well spent because the satisfaction lasts a long time. Buying a sports car, a watch, or luxury goods may only provide satisfaction for a few weeks; after a month, it’s gone, and you 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 is the long-term source of happiness.
04 Engaging in Education: Encouraging More People to Do What They Truly Want to Do
Mia: I understand. Now, many people who have just entered this industry and made some money, some through manual trading and some through on-chain trading, if they want to transition to a more stable trading method, what would you suggest they do?
Calvin Tsai: Learn quantitative trading.
Mia: What kind of person is suitable for learning quantitative trading?
Calvin Tsai: I think those who are not resistant to numbers are suitable for learning quantitative trading. I have taught many students; some have succeeded, and some have failed. I found a significant point: some people who have been learning for six months or a year without success actually dread math from a young age and are resistant to numbers. Quantitative trading requires facing a lot of numbers, finding patterns, and adjusting parameters, which involves a lot of numbers. So the two most important points are: having logical ability and not being resistant to numbers.
Mia: Besides that, what do you think is more important for a quantitative trader to do well?
Calvin Tsai: Stay rational. Many people who do quantitative trading halfway through see others making ten times their money through manual trading or hundreds of times by buying coins, and they will switch back to manual trading; this shows a lack of rationality. They are misled by short-term profits, which affects the execution of long-term strategies. So the most important thing is to stay rational, believe in your methods, and trust the strategies you have in hand.
Mia: So you focus on what you choose to focus on, rather than shifting to wherever there is money. Since you are also involved in quantitative teaching, do you worry that more quantitative traders entering this industry and learning this system will make the industry more competitive?
Calvin Tsai: Theoretically, the answer is yes, it will. I think this question is very good; very few other interviews ask it, but it is very important. Why do I still want to teach others? To be honest, I gain a lot of satisfaction and a sense of achievement from the teaching process. In the past few years, I have taught some people who have grown their capital from hundreds of thousands to tens of millions, or even over a hundred million, 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, rather than doing things you don’t want to do just for money. Seeing these students make money and realize their lives gives me a sense of satisfaction greater than making an extra billion or two. Therefore, I think spending time and energy on teaching is something that makes me very happy. In the past, if I blew up and went back to hundreds of thousands, I might have focused on going home to develop strategies rather than sharing and educating. But now, I find that education is a very joyful thing for me.
Mia: I understand. Among the many people you have trained, as you mentioned, many have quickly made a lot of money. How many are there approximately? Do they have any common traits?
Calvin Tsai: More than a dozen of my middle school and university classmates have achieved financial freedom. In fact, being close to you gives you the opportunity to achieve financial freedom. The key is that they have an understanding of quantitative trading and are interested in learning about it. But I must say, this is really not easy. I have talked to many people about Bitcoin and quantitative trading, but out of ten people, about eight have no interest, and only two really want to delve deeper; and of those two, one might give up halfway. The dozen or so people you just heard about are actually just a small part of many, so there is no stage that is very easy.
Mia: I understand. In this process, if some people do not learn, could it be because you did not explain it well enough or did not teach them effectively?
Calvin Tsai: I think it’s more about the individual. The methods and content I teach are the same, but whether they learn or not really depends on themselves. The key is whether they seriously try to understand this matter or treat it as a cash cow. If you do not understand Bitcoin and only think about doubling your money tomorrow or next month, you usually cannot hold on. Why can some people hold for five or ten years while others sell after a few months? Essentially, it comes down to whether they understand what Bitcoin is and why they should buy Bitcoin. In trading, I have summarized that the biggest difference between unprofitable traders and profitable traders is motivation. Unprofitable people usually trade for money, to buy sports cars, while those who truly make money love trading itself. They are happy to see the prices on each exchange tending to balance, validating that their strategies can make money; they trade not to satisfy material desires but to truly excel at trading. Therefore, making money is actually just a byproduct of doing what you love. When you chase money as a goal, it can easily affect your mindset and lead to poor results.
05 Advice for Beginners: Effort is More Important, Stay Rational, Keep an Open Mind, and Maintain a Learning Attitude
Mia: Do you think trading requires talent? Do you think someone can replicate you?
Calvin Tsai: I think effort is far more important than talent. No one is born knowing how to trade, and no one is born knowing how to do manual trading or quantitative trading; it is all learned step by step. I also lost a lot in manual trading at first, and after losing two big trades, I truly learned. So I believe it is 100% about effort.
Mia: What about some beginners? Some beginners in quantitative trading might think it is a guaranteed way to make money. What advice would you give them?
Calvin Tsai: The world is very fair; there is no such thing as guaranteed profits. You definitely need to invest time and energy. Even the simplest act of putting money in a bank does not guarantee profits; many banks have gone bust in history. So, there is no free lunch in this world; you must do what others have not done to earn money that others cannot 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 enter the crypto space?
Calvin Tsai: I think there are a few key points. First, stay rational. Many people lose their rationality when they incur significant losses; they become irritable, and their emotions are affected by losses, making it difficult to analyze clearly. The first step is to manage your emotions well; maintaining stability and rationality is essential for clearly analyzing numbers, logic, and methodology. Second, reduce cognitive biases. What are cognitive biases? For example, you might think, "If I don’t sell this coin, I haven’t lost," or "I’ve held it for a few months; if I keep holding, it will rise tenfold next year." You need to understand the pitfalls in your thinking and work hard to correct them. Third, keep an open mind. You need to realize that there are many things beyond your understanding. I have been learning quantitative trading for a long time, but I always maintain a learning attitude, knowing that there are still many things I do not know and many things I have overlooked. I actively seek them out and learn. Many people think, "I already know a lot," but in reality, they do not see what they have not seen—what we call "unknown unknowns." Therefore, I always maintain a learning mindset. Even when I see other educators, I may perform better than them, but I still believe there are things I can learn from them.
Mia: I understand. So first, stay rational, avoid biases, and maintain an open learning attitude. Kelvin has emphasized rationality throughout this process. Do you think that when you become an absolutely rational person, it might make those around you feel that you have less emotional fluctuation and are somewhat unapproachable?
Calvin Tsai: Yes, some people may feel that way, thinking I lack humanity. But I believe that trading and life can be separated; at a certain point, you can distinguish between them, as long as it is under the premise of rationality.
Mia: How do you balance that?
Calvin Tsai: Balance it rationally. With people, when you don’t need to be rational, you can be more emotional, show more care, and understand others' feelings.
Mia: But when your rationality has become a habit, how do you bring out your emotional side? For example, when interacting with family, friends, or in close relationships, how do you balance rationality and emotion?
Calvin Tsai: I am still learning.
Mia: Well, we are very grateful to Calvin for this interview today, which has filled in many gaps regarding quantitative trading and the series of dialogues with traders. Everyone is welcome to follow Calvin on Twitter, Telegram, and his quantitative fund. Currently, Calvin is also working on some investment projects, so if anyone wants to learn, they can contact him at any time to understand the "secrets" that cannot be publicly discussed in those strategies. Alright, this interview ends here. Bye!
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