To The Moon

🎉In 2025, a growing number of Tiger users achieved million-dollar investment returns. Tiger launched The Road to Million Dollars series to get closer to investors who have already reached annual million-dollar gains, as well as those who are actively pursuing the million-dollar goal and have achieved annual returns exceeding USD 100,000—listening to their stories of how they think, persevere, and grow.

For Tiger, investing is more than just profit and loss figures; it is a journey from aspiration to achievement. Through these stories, we hope to inspire more people to set their own investment goals and turn “a million dollars” from a distant dream into a visible, attainable milestone.

🎁Click here to redeem your Dream Edition Million-Dollar Milestone at the Tiger Coin Center🎁

🚀💰Introduction to the Million Dollar Road

This interview features Tiger Community user "Suzhou Jiucaihezi." @苏州韭菜盒子

He has been trading US stocks for nearly ten years, from stocks to options, from frequent trial and error to systematic trading. He experienced significant losses in the early stages and underwent multiple rounds of self-iteration in his understanding of markets and trading.

This is not a story about “getting rich quickly.”

Rather, it is a realistic path about how to survive in the market, how to solve complex problems, and how to coexist with uncertainty over the long term.

1. 📈From Full-Time US Stocks to Ten Years of Options Trading

On Tiger Community, his nickname is "Suzhou Jiucaihezi." @苏州韭菜盒子 resides in Suzhou and has been trading US stocks for nearly ten years. He started trading full-time in 2017. By 2022-2023, he had shifted almost all his focus to options, now primarily trading options and rarely trading stocks.

For him, this is not a change in style, but a natural iteration of trading understanding—

When you truly treat trading as a long-term career, you will eventually move towards a "system," otherwise it is difficult to survive long-term in uncertainty.

2. 🎯Why Focus Only on Big Tech and In-Depth Research on Only Two Companies?

His focus isn't scattered; it's primarily concentrated on the Mega Seven (US tech stocks), but he dedicates the most energy, conducts repeated research, and invests heavily in only two companies: Tesla and Nvidia.

@苏州韭菜盒子 doesn't do "opportunity-driven research," but rather selects targets that can be tracked long-term and continuously validated, treating research itself as a long-term project. Because in his view, whether trading stocks or options, you can't avoid judging the direction of the target: will it rise, fluctuate, or fall in the future? The foundation of this judgment comes from the depth of your understanding of the company.

3. 🔍How He Determines if a Company is Worth Long-Term Investment

Before committing to long-term research and trading, he breaks down a company across several layers:

1. 🛠️The essence of the product and technology: What problem does it solve? Through what product or technical architecture? Are there real, scalable application scenarios?

2. 🛡️Moats and competitive landscape. How high are the technical barriers? How deep is the moat? Who are the competitors, and how intense is the competition?

3. 📊Growth potential and constraints of the business and profits. Market size, user structure, growth ceiling, and potential risks.

4. 🚀Long-term upside. For example, Tesla is already a trillion-dollar company—does it still have a path to becoming an $8 trillion company?

Throughout this process, he closely monitors whether the company is executing along the roadmap outlined by its CEO or management. These key milestones are like "breadcrumbs on the ground," helping him infer where the company may ultimately go.

Beyond that, @苏州韭菜盒子 assesses whether the valuation is reasonable and takes the macro environment into account. Above all, he adheres to one core principle:

Fundamentals are fundamentals. Trading is trading.

Some companies may have mediocre fundamentals, yet their stock prices can still become extremely expensive. Whether a stock is worth going long is not the same as whether it is “worth that price.” Ultimately, he assesses entry points by combining product strength, valuation level, and timing.

4. 🚗Tesla is not a "robot story," but a productivity revolution driven by FSD

Mr. Cui's assessment of Tesla is notably restrained, even counterintuitive.

In his view, $Tesla Motors(TSLA)$ 's humanoid robot business is currently immature and far from being an industry leader; in the short term, it's more of conceptual hype. What truly deserves a place in the valuation system is FSD (Full Self-Driving).

@苏州韭菜盒子 repeatedly emphasizes that once FSD achieves truly "unsupervised autonomous driving," it will directly change the patterns of transportation, logistics, delivery, and travel, and can be replicated on a large scale at extremely low marginal costs. This is the core logic supporting Tesla's trillion-dollar, or even higher, market capitalization. Therefore, he is not "chasing trends," but rather continuously building his trading judgment based on FSD's technological progress, timelines, and market expectation gaps.

5. NVIDIA is not about "expensiveness," but "whether the shovel is worth it."

Faced with widespread market skepticism about Nvidia's "overvaluation," Mr. Cui provides a lucid counter-perspective:

"The market's true hesitation isn't over $NVIDIA(NVDA)$ ; it's whether the AI companies purchasing these massive amounts of GPUs can actually turn a profit in the future."

In his view, Nvidia is essentially a company that "sells shovels," and AI application companies like Tesla are key examples for verifying whether "shovels" are valuable. As long as AI can: clearly improve productivity, translate into real, sustainable revenue, and be implemented on a large scale in the real world, then Nvidia's current valuation is not unreasonable, and may even have room for further growth.

6. Whether AI is a bubble depends on your timeline🕰️

Regarding whether AI is a bubble, he emphasizes that it must be discussed within a time dimension. Looking back at history, whether it's the steam engine or electricity, truly large-scale improvements in productivity were only achieved decades after their invention.

AI will undoubtedly improve human productivity; the key is how long it will take. If viewed over a five-year or longer period, AI is not a bubble, but if viewed only for one or two years, a temporary bubble is entirely possible. Therefore, judging whether AI is a bubble essentially means judging when it can cover more people's lives at a lower cost and truly improve efficiency.

7. ⏳Waiting for the Right Moment, Not Chasing Market Trends: Options Trading

In trading, he primarily focuses on options, but emphasizes that "the nature of options dictates that you must wait for the right moment." When a company experiences a significant drop due to macroeconomic or fundamental events, and he judges it to be a mispricing, he uses options as a long-term buyer. In environments with no significant events and high volatility, he typically focuses on selling.

His current trading system is built around selling options. In high-volatility, high-valuation environments, relying purely on buying options is extremely difficult for most people to sustain profitability.

8. 📈Options 3.0: Using "Selling" to Make Time Work for You

Compared to stock trading, Mr. Cui's true systemic advantage lies in options trading.

@苏州韭菜盒子 clearly divides his evolutionary path into three stages:

• 1.0: Buying Only (Correct direction, but large drawdowns)

• 2.0: Buying + Hedging (Complex strategy, but still easily consumed by volatility)

• 3.0: Systematic Trading Centered on Selling

The current core logic is: earn premiums through selling, making "time" your friend. Sell Put/Call when the market makes a mistake, and volatility is overestimated. Switch to buying only when extreme prices or trend signals appear.

He points out that in markets marked by high volatility and lofty valuations, making money on the long side is exceptionally hard, as time decay quietly eats away at returns. A strategy built around selling, however, creates a smoother, more repeatable, and more sustainable path to profits.

9. 📖Forget the K-lines. It’s the narrative that matters.

His edge doesn't come from technical indicators; he barely looks at them beyond overbought or oversold signals. Instead, he hunts for three things: Macro narratives, product milestones, and market mispricing.

A prime example: When the market wrongly dialed back rate-cut expectations, he saw the error based on his deep read of the Fed and the economy. He didn't just watch—he moved in as a buyer and was proven right.

The Takeaway: Profits aren't built on trading frequency. They are built on the conviction to strike hard when the market gets the price wrong.

10. 📊The hardest return profile to achieve? A smooth one.

He maintains a strict safety rule: once the account hits $100k, he withdraws the profit. Since opening his Hong Kong account in August, he’s already tripled his returns.

His secret isn't "home run" trades. As an option seller, the gains per trade are modest, but they are consistent. "Individual profits might be small, but a smooth curve is where the real compounding happens."

11. Beyond Options: What Trading Truly Brings

He has taken a deeply self-driven path in options trading—completely self-taught, having read nearly all major domestic and international books on the subject. He is now organizing his advanced strategies and may publish a book in the future.

He often uses a metaphor:

• Options are the leaves

• Macro is the trunk

• Investment targets are the branches

• Understanding human nature is the wind and rain

Without these, options have nothing to attach to.

For him, the greatest gain from trading is not money, but the development of methodology and self-awareness—learning that not every opportunity needs to be seized, not every fluctuation needs participation, and sometimes the ability not to trade is itself a skill. Ultimately, trading has taught him how to remain rational amid uncertainty.

12. The Path Was Difficult, But He's Grateful He Persisted🙏

Looking back on this path, he admits it wasn't easy.

@苏州韭菜盒子 worked in auditing after graduation, then in investment relations, but his full-time commitment to trading was "pushed" onto this path after leaving a job. He lost millions early on, paid hefty tuition fees, and endured his family's lack of understanding.

Yet he always knew this was not gambling, but a process of solving complex problems. The path is difficult, and he does not recommend it lightly. But he is grateful that he persevered. For him, trading is a continuous process of correction and iteration—no need for labels or comparisons, just focus on doing the right things and managing risk. The rest is left to the market.

Looking back at Suzhou chive pocket's journey, it's difficult to summarize in a single sentence. There is no clear starting point, no “one winning trick,” only constant refinement—from stocks to options, from buying to selling, from emotion-driven to system-driven trading.

Ultimately, trading is not about capturing every market fluctuation, but about building a capability: staying rational amid uncertainty, acting when the market is wrong, and waiting when there is no opportunity. Money is a byproduct, not the goal. What truly matters is whether you gradually learn to deconstruct complex problems and find a solution that suits you.

Perhaps this is precisely the meaning behind "The Road to Million Dollars"—not to replicate a particular trading method, but to see how different people gradually forge their own paths.

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