2.9 billion, Mr. Duan has made a bottom-fishing move.
Mr. Duan has made a bottom-fishing move.
On the morning of April 8, Duan Yongping posted 5 delivery slips on Xueqiu, selling put options for Nvidia, Apple, TSMC, Google, and Tencent. Before making his move, Duan Yongping posted, "The mountain is still that mountain, and the beam is still that beam"… "The understanding king will at least have to stir things up for a while; selling some puts and stirring things up together might be a fun game."
Calculating (after excluding suspected duplicate trades in the delivery slips), this time Duan Yongping's "bottom-fishing" involved approximately $394.55 million (about 2.9 billion RMB), with about $90 million in Apple, about $150 million in Nvidia, about $80 million in Google, and about $80 million in TSMC. The contract durations in the delivery slips range from just a few days to as far out as 2026, with varying strike prices, but given Duan Yongping's character and his previous statements about being "in cash," he must have prepared his positions.
Tencent was more of an experimental operation, with Mr. Duan selling different term Tencent puts at 440 HKD per share, but he felt it was generally average, hence he said, "The premiums for longer-term puts are not good, and the short-term ones are average; it's hard to collect the premiums."
Additionally, Duan Yongping directly "purchased" 10,000 shares of Nvidia at $94 per share, a "small amount" of less than $1 million. Buffett said, "Be fearful when others are greedy," whether Duan Yongping has successfully copied the homework this time remains to be seen, especially since the market is waiting for Buffett's speech in May, and the old man still has a large amount of cash untouched.
Last month, when U.S. stocks began to plummet, Duan Yongping boldly declared that he had "already been in cash, enjoying the pleasure of being in cash," stating, "The core of investment management is managing risk, not pursuing returns." He escaped the peak in cash and then turned around to prepare to bottom-fish with 2.9 billion.
2.9 billion is a fun game; it’s no wonder it’s Mr. Duan.
In cash, bottom-fishing.
Let’s take a look at the four companies he bottom-fished this time. Apple and Google are Mr. Duan's favorites. As of the end of Q4 2024, Duan holds Apple shares worth $10.233 billion, accounting for 70.50% of his portfolio. Similarly, he also holds 3.77 million shares of Google, with a market value of $717 million.
At the end of last month, Duan publicly stated, "I will consider increasing my position in Google. Google has a deep foundation and should not be underestimated." Even though Trump's tariffs pose a threat to the cornerstone of the business model, Mr. Duan still remains optimistic about Apple.
Nvidia and TSMC, the water sellers of the AI era, have become Mr. Duan's new favorites.
According to public information, Duan first bought Nvidia on March 19 this year, announcing an order to buy 100,000 shares of Nvidia stock at a limit price of $92.52 just an hour before CEO Jensen Huang's speech, while simultaneously selling call options for that batch of stocks at a strike price of $120, with a contract effective until March 20, 2026.
A year ago, he was still an investor who "didn't understand" Nvidia, writing, "Understanding a company is indeed very difficult. I didn't understand it before, and I still don't understand it now. I can't figure out whether this company will be better or worse in ten years."
However, starting this year, Duan Yongping has mentioned Nvidia on Xueqiu more than a dozen times, clearly indicating a change in attitude. In early March, when he still felt he didn't understand Nvidia, Duan chose to sell 1,000 Nvidia puts for a total price of $370,000. Even after buying Nvidia stock, he admitted that he couldn't say he fully understood it, but he did feel that NVDA's moat was quite impressive. "Looking at it, this is definitely a good company; buying some is likely to be profitable."
Additionally, he mentioned that many years ago he had dinner with Jensen Huang, "I had a very positive impression of him, but unfortunately, we didn't chat much because my English wasn't good. If I had been able to see this back then, my attention might have increased a lot; it's not too late to start paying serious attention now."
Now, with the U.S. stock market plummeting, Mr. Duan finds that "the more Nvidia drops, the more interested I become," stating, "Think different does not mean you have to be different from others. You can be the same with NVDA." In terms of acceptance of technology, Mr. Duan is clearly more aggressive than Buffett.
In contrast, his overall operations have left investors amused. At the end of February, he decisively reduced his position by 70%, holding a large amount of cash. A few days later, due to FOMO, he bought back Nvidia and a series of U.S. stocks, even adding leverage. Unfortunately, after that, Nvidia's stock price fell more than 25% from its peak, leading to a significant decline in the net value of the fund managed by him.
In addition to Nvidia, Duan has recently also focused on TSMC, combining Mr. Duan's recent statements, "TSMC's business model and corporate culture are very strong. TSMC and Microsoft are both powerful B2B companies; I was slow to realize this." Perhaps Mr. Duan is also susceptible to FOMO.
Bottom-fishing is just a routine operation for him.
In fact, bottom-fishing is a common operation for Mr. Duan.
Mr. Duan's well-known bottom-fishing operation with NetEase is well-documented. In 2022, Mr. Duan also bottom-fished Tencent's U.S. ADR five times in February, March, April, August, and October, continuously bottom-fishing and replenishing his position, with the cheapest price reaching $32. At that time, Duan Yongping believed that, in the long run, buying Tencent stock might be safer than keeping money in the bank, as one could enjoy the dividends of corporate growth.
During the 2008 financial crisis, Duan Yongping also executed a perfect bottom-fishing strategy. He recalled that in September 2008, as the impact of the financial crisis grew larger following Lehman Brothers' collapse, the entire market was in a state of panic.
"By November, the panic in the entire market was intensifying, and negative sentiment was almost at its peak. I thought to myself, this is probably what Buffett meant by people's 'fear' coming, and it was time for me to be 'greedy.' At first, I didn't have a particularly clear goal; I just felt that there were bargains everywhere in the market, but I didn't know which ones were safe. It seemed like every company had significant problems, and any of them could fail. What I thought most about was how to mobilize all my resources to seize this once-in-a-lifetime opportunity."
In February 2009, GE's stock fell below $10. At that time, many companies related to subprime mortgages, such as Lehman, AIG, and Citigroup, had already gone bankrupt or were on the brink of bankruptcy, and negative news about GE was increasing. Many people on Wall Street were saying GE would be the next Lehman.
However, Mr. Duan believed that the financial crisis would not destroy GE's strong corporate culture, and past strategic errors could be corrected over time. Therefore, when GE's stock price fell from around $9 to $6, he began to buy in large quantities. The returns were quite substantial; he sold at over $20, yielding about 200%.
Magical U.S. Stocks
Last night, the U.S. stock market experienced quite a magical moment, with the Nasdaq plummeting nearly 5% shortly after opening, only to rebound with news that "tariff policies will be paused for 90 days," with the index turning from a 5% drop to over a 4% gain within half an hour, and the S&P index rising over 3%.
However, about seven minutes later, the three major U.S. indices sharply reversed direction, bouncing around like a speculative stock. Friends following the U.S. stock market jokingly remarked that "little essays" have also become popular for trading stocks.
It is worth mentioning that the S&P 500 index has only seen a cumulative drop of over 10% in two trading days three times before: during the 1987 stock market crash, during the 2008 global financial crisis, and at the beginning of the pandemic in early 2020. The darkest moments of the stock market have also led to a loss of over $500 billion in wealth for 500 of the world's richest people.
In contrast, the domestic capital market has orderly released a series of positive signals.
According to statistics from China Securities Journal, on the evening of April 7, multiple large central state-owned enterprises, private listed companies, and shareholders issued announcements related to buybacks. Central Huijin, China Chengtong, and China Guoxin made significant purchases of A-shares.
Central Huijin stated that it firmly believes in the development prospects of China's capital market and fully recognizes the current value of A-share allocation. It has again increased its holdings in exchange-traded funds (ETFs) and will continue to increase its holdings in the future to resolutely maintain the stable operation of the capital market. China Chengtong's subsidiaries, Chengtong Financial Holdings and Chengtong Investment, have increased their holdings in ETFs and central enterprise stocks, continuously making large purchases of central state-owned enterprise stocks and technology innovation stocks, acting as long-term investors in listed companies. China Guoxin Holdings announced that its subsidiary, Guoxin Investment Co., Ltd., has increased its holdings in central enterprise stocks, technology innovation stocks, and ETFs, actively supporting technological innovation in key areas and contributing to maintaining market stability.
On the morning of April 8, the People's Bank of China and Central Huijin made significant statements. Central Huijin clarified that it is the "national team" in the capital market, playing a role similar to that of a "stabilization fund." The central bank also stated that it would provide sufficient relending support to Central Huijin when necessary. Meanwhile, the National Financial Regulatory Administration also announced that it would increase the proportion of insurance funds invested in the stock market.
Perhaps Mr. Duan could also consider another "old friend," Moutai?
How to Understand Duan Yongping's Stock Market Operations This Week | MacTalk - Thoughts from Chi Jianqiang A few days ago, I saw Duan say on Xueqiu:
A few days ago, I saw Duan say on Xueqiu:
He sold some Apple and other puts. The understanding king is mighty; it feels like he will have to stir things up for a while, and selling some puts and stirring things up together might be a fun game. As always, never use margin. If the price of the puts looks cheap from ten years later, then this investment is worth making, suitable for both short and long term.
What does Duan Yongping mean by this statement? I'm not very clear, but we can ask Gimini 2.5 Pro, and the response is as follows:
Gimini 2.5 Pro: This statement is Duan Yongping sharing his investment strategy and philosophy during periods of market volatility, mainly revolving around selling put options. We can break it down:
1. "Sold some Apple and other puts":
Core Operation: He sold (Sell) some put options for Apple Inc. (AAPL) and other companies he considers good.
2. What selling put options means: Selling put options allows the investor (in this case, Duan Yongping) to receive a premium. In exchange, he takes on an obligation: if the buyer of the option chooses to exercise it on or before the expiration date, the seller (Duan Yongping) must buy the corresponding number of shares from the buyer at the agreed strike price.
3. Seller's Expectation: Typically, those who sell put options expect the stock price to be at or above the strike price at expiration, so the option won't be exercised (or will be worth very little), allowing them to earn the entire premium.
4. "The understanding king is mighty; it feels like he will have to stir things up for a while":
Background/Motivation: "Understanding king" usually refers to former U.S. President Donald Trump. This statement implies that he believes (at that time) due to political or other macro factors (possibly related to Trump), the market will experience a period of volatility or uncertainty ("stirring things up").
Strategy Connection: During periods of increased market volatility, the implied volatility of options typically rises, making the premiums higher. Therefore, selling options when expecting the market to "stir" can yield richer premiums.
5. "Selling some puts and stirring things up together might be a fun game":
Strategy Description: This indicates that he may not just sell once, but during market volatility, he might repeatedly sell put options based on the situation ("stirring things up together") to continuously earn premiums.
Mindset: "Fun game" reflects his relatively relaxed attitude towards this strategy, but it also suggests that it requires skill and an understanding of risk.
6. "As always, never use margin":
Risk Warning: This is a point he consistently emphasizes. Margin (financing, margin trading) refers to borrowing money from a broker to invest. Selling put options (especially naked puts) carries inherent risks; if the stock price drops significantly, the seller may need to use a large amount of capital to buy the stock. If margin is used, a sharp market downturn leading to losses may trigger a margin call, or even forced liquidation, resulting in irreparable losses.
Principle: He emphasizes using only his own and idle funds for such operations, ensuring that even in the worst-case scenario (needing to buy the stock at the strike price), he can fully afford it without jeopardizing financial safety.
7. "If the price of the puts looks cheap from ten years later, then this investment is worth making":
Core Philosophy: This reveals his deeper logic behind selling puts, consistent with his value investment philosophy. The companies he sells puts on (like Apple) are ones he is willing to hold long-term. The strike price he sets is one he believes is reasonable, even if forced to buy the stock (i.e., "the price of the puts… is cheap").
Value Judgment: He is not merely selling puts to earn premiums; he views selling puts as a potential way to buy good company stocks at an ideal price. If the stock price does not drop below the strike price, he earns the premium; if it does, he is forced to buy, which is equivalent to purchasing the desired stock at a price he has previously deemed "cheap." This price must withstand the test of time ("looking back ten years").
Strategy Flexibility: This strategy has both short-term gains (earning premiums) and long-term goals (buying good company stocks at a good price). Therefore, from both short-term operations and long-term investment perspectives, he believes this is appropriate.
In summary:
Duan Yongping's statement describes a strategy that combines options trading with value investing:
Anticipating market volatility, he earns premiums by selling put options.
The target companies are those he believes in long-term and is willing to hold.
The strike price he sets is one he considers worthwhile even if he has to buy.
Strictly prohibits using leverage (Margin), covering potential buying obligations with his own cash to control risk.
Under this strategy, if the stock price does not drop, he earns premiums; if it does and he is exercised, he buys the desired company stock at a predetermined ideal price. This makes the strategy reasonable for both short-term (collecting rent) and long-term (building positions).
This is a relatively conservative options strategy based on fundamental value judgments, with the core being a deep understanding of company value and strict risk control.
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This response is far better than other AIs.
You see, from such a brief statement by the big guy, we can learn so much knowledge through AI. It must be said that AI is a must-have, whether you want to learn or work. After all, Mr. Duan is not going to explain these basic terms and logic to you.
Sharing an Efficient Reading Method by Li Xiaolai#
Since the first day of 2023, I have almost spent an hour every day reading, accumulating about 100 books. As my reading volume has increased, I increasingly agree with the view of Silicon Valley investor Dr. Wu Jun: reading should be layered to balance breadth and depth, thus more effectively acquiring knowledge.
It sounds simple, but how to do it specifically?
Recently, I saw Teacher Li Xiaolai share his reading method on Weibo, which inspired me greatly. Combining my personal experience, I have broken down and optimized this method, transforming it into a more grounded and suitable reading process for ordinary people. If it inspires you, feel free to follow.
01
Li Xiaolai's Efficient Reading Method
Teacher Li Xiaolai's reading method combines efficient filtering and deep reading, with the specific process as follows:
Ask AI (ChatGPT) for recommendations on 5 to 10 books in a certain field to quickly identify quality books.
Find these books, buy them all, download and convert them into text format for easier processing later.
Use AI tools like NotebookLM (not directly available in China) to quickly browse these 5 to 10 books in one day, filtering out the most worthwhile content for in-depth reading.
Spend 3 to 5 days deeply reading the most worthwhile book.
Then spend 1 day deeply reading the most valuable parts of the remaining books.
When I first saw this efficient reading method, I was filled with excitement and eager to try it. However, upon calm reflection, I realized that I shouldn't blindly copy it, as it might backfire.
Teacher Li Xiaolai's deep reading requires a certain reading foundation and patience, but everyone's learning habits and reading abilities are different. Directly imitating such advanced reading methods may lead to frustration due to inability to persist, causing a loss of interest in reading.
Therefore, the method needs to be improved.
02
A More Suitable Efficient Reading Method for Ordinary People
I really like a saying: "Learn its form, comprehend its essence, learn and then think." This means we should not only learn the external form but also grasp its internal essence, and reflect and summarize in practice. Only in this way can we continue to progress.
Returning to Teacher Li Xiaolai's efficient reading method, we can capture three core points:
First, cast a wide net to avoid missing quality books in a certain field.
Next, quickly filter to ensure time is spent on quality content.
Finally, deeply read and delve into the 20% most valuable content, spending 80% of the time on it.
Based on these points and my personal experience, I believe a more suitable efficient reading method for ordinary people is as follows:
- First determine the theme, rather than aimlessly searching for books.
In Teacher Li Xiaolai's process, he first uses AI (like ChatGPT) to obtain 5 to 10 quality books on a certain theme. For ordinary people, the most important thing is to clarify what problem you want to solve or what knowledge you urgently need to supplement. You can:
First ask yourself: What skills do I want to improve recently? What challenges am I facing?
Then let AI (like DeepSeek, Kimi) or experienced friends recommend books; 5 to 10 is enough.
Using questions to guide direction will be more targeted, thus avoiding wasting time and energy.
For example, when I started cultivating my reading habit at the beginning of 2023, I had many confusions that needed answers, such as: How to read a book effectively? Why do some people gain so much from reading the same book while I do not? What is the difference? Can time really be managed? Everyone has 24 hours a day; why are some people so efficient while I am not? What is the problem, and how to solve it?
There are many similar confusions. My approach was to first determine the theme, such as reading methods, time management, habit formation, systematic thinking, etc. At that time, ChatGPT had just become popular, but I didn't ask ChatGPT for book recommendations; instead, I manually searched for books on platforms like Douban Reading, WeChat Reading, and Zhihu, compiling a book list.
▲ Book list on "Reading Methods"
▲ Book list on "Habit Formation"
▲ Book list on "Time Management"
Follow the public account and reply "High-Scoring Book List" to receive the book list I compiled.
Of course, compared to two years ago, AI has evolved tremendously. As I use AI more frequently, I now also directly ask AI for recommendations.
- Use accessible tools to quickly obtain information.
Li Xiaolai converts e-books into text format and uses AI tools like NotebookLM for quick scanning. This may be a bit challenging for ordinary people. At this point, you can:
Download reading apps on your phone, find the book, and quickly preview it using the "table of contents + keyword search" function to understand the book's framework and key chapters.
If you bought a physical book, you can take photos with your phone + use OCR software (like ScanMaster) to convert important chapter content into text, then analyze it using AI tools like DeepSeek or Kimi.
- First skim, then read deeply.
Li Xiaolai's idea is to quickly go through 5 to 10 books and then select the most worthwhile one for deep reading. Ordinary people can directly borrow this:
Spend 3 days to skim through the table of contents, preface, conclusion, or important chapters of all books, tagging each book with a "worth reading deeply" label.
Select the 1 to 2 most worthwhile ones for deep reading: highlight key points, take notes, and think about how to apply them to your life and work.
The other books can serve as a "resource library," only picking chapters most relevant to your questions.
- When reading deeply, don't rush to finish; focus on understanding.
Deep reading is not about racing to the last page but thinking as you read:
What are the most important points of this book?
Are there methods that can be directly applied to work, study, or life?
When you come across a concept, pause and think about whether you can explain it to someone else or write it in your own words.
- Combine notes with application.
For example:
Create a note document on your phone or computer (using Evernote, memos, Feishu, WPS, etc.), and write a 3 to 5 line summary after finishing each chapter.
When you come across good ideas, think about "How can I use this?"
As your notes accumulate, you'll have your own exclusive "knowledge base," allowing you to quickly find corresponding knowledge points and ideas when encountering similar problems next time.
03
Two Small Suggestions
- Learn the approach, then take action.
Li Xiaolai was once a renowned English teacher at New Oriental and had programming skills, so using foreign AI tools is second nature to him. Ordinary people might say, "I don't have these skills; I can't be as efficient as he is."
In fact, tools are just auxiliary means; the core is still the approach of "first broadly collecting information, then quickly filtering, and finally deeply researching and practicing." Even if we only have physical books and a mobile reading app, we can still use similar steps to filter and read deeply.
- Set time limits for reading.
Without time limits, it's easy to accumulate books and materials without ever reading or finishing them. Why not try:
Spend 3 days for quick browsing.
Spend 5 to 7 days deeply reading the most valuable book.
Then spend 3 days browsing the remaining few books, focusing on key chapters.
We may not be able to achieve the same efficiency as Teacher Li Xiaolai, but we can borrow this "time chunking" method to rhythmically arrange time according to personal circumstances, allowing ourselves to maintain focus during a certain period.
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In conclusion:
As Dr. Wu Jun said, reading should be layered to balance breadth and depth, enabling more effective knowledge acquisition. If you find value in this article, consider taking one interesting little tip and putting it into action.
That's all, let's encourage each other.