The Road to Million Dollars: From USD 80K to USD 2M — Brad’s Event-Driven Trades

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.

In the market, million-dollar outcomes are often associated with bold bets.

But behind those bets, there is usually a long process of filtering information, managing emotions, and defining risk with precision.

This episode of The Road to Million Dollars features Brad, a Singapore-based investor whose portfolio crossed the million-dollar mark through high-risk, event-driven options trading—supported by strict position sizing, relentless information intake, and disciplined profit-taking.

1. From a Decade in Markets to a Mental Turning Point

Brad is 36 years old and based in Singapore. He began investing more than ten years ago, around the time he started his first job, and has remained active in the markets ever since.

Three months ago, he retired.

That motivation shaped both his risk tolerance and his long-term commitment to trading.

But the real turning point didn’t come from a single trade. It came from a realization:
Retail investors are no longer playing on an uneven field.

“With platforms like Tiger and social media, retail investors now have access to data that once belonged only to institutions with Bloomberg terminals,” Brad said.

From that point on, he stopped competing on stock-picking depth alone—and began focusing on speed, synthesis, and macro-level thinking.

2. The Trades That Changed Everything: $UnitedHealth(UNH)$ and $Boeing(BA)$

Brad’s breakout year was driven not by luck, but by preparation.

$UnitedHealth(UNH)$  was his defining trade. When the stock sold off sharply and sentiment turned cautious, Brad’s portfolio stood at around USD 400,000. After deep research, he concluded that fundamentals remained intact and the decline was driven by fear—not structural damage.

Acting on that conviction, he bought options ahead of earnings.
Soon after, UnitedHealth disclosed that $Berkshire Hathaway(BRK.B)$  had taken a position. The stock opened up roughly 16%, and Brad’s options surged 500–600%, lifting his portfolio to around USD 2.4 million.

This was not an isolated win.

Brad cited $Boeing(BA)$ as another example of his event-driven process. When President Trump met Turkish President Erdoğan after an eight-year gap, Brad flagged the meeting as market-relevant. Based on historical research, he identified a recurring pattern: Trump’s overseas engagements often translate into large aircraft orders.

He positioned early with short-dated options. Days later, a major Boeing order was announced. The stock rose about 4%, delivering roughly a 250% return.

For Brad, these trades reflect a core trait of his investing style: a relentless hunger for knowledge.
By studying events, history, and second-order effects in advance, he is ready to act decisively when a catalyst appears.

3. Why It Worked: Event-Driven, Macro First

Brad describes his style as high-risk, event-driven macro trading.

He does not see himself as a traditional fundamental or technical trader. In his view, AI has significantly eroded the edge of purely chart- or balance-sheet-based analysis—machines can process those faster and more consistently than humans.

Instead, Brad focuses on areas where AI is still weaker:

• Macro events

• Geopolitics

• Human behavior

He uses AI tools to assist with fundamentals and technicals, but relies on his judgment to connect the dots.

This approach also shapes how he consumes information.
Brad spends up to eight hours a day reading news across the U.S., Asia, and Europe—not to chase headlines, but to identify patterns and second-order effects.

“In the market, about 80% of information is noise,” he said.

“The real skill is filtering until only the 20% that matters remains.”

4. High Risk, But With Rules

Despite his aggressive style, Brad does not trade recklessly.

He follows two non-negotiable rules:

• No single position should exceed 50% of the portfolio—and ideally stay closer to 20%, no matter how strong the conviction.

• Profits must be taken. Positions are never held indefinitely out of greed.

However, Brad is significantly more conservative when it comes to other asset classes, such as crypto.
Given its volatility, he caps crypto exposure at around 5% of his portfolio, with much tighter position sizing and earlier profit-taking.

His account has blown up before. This year, he restarted with USD 80,000, scaling step by step:

 USD 100k → 200k → 400k → 500k → 1 million.

“Don’t be afraid to fail,” Brad said.

“Every failure teaches you something—about IV, Greeks, earnings, and risk.”

Today, around 80% of his net worth is allocated to safer investments, with 20% reserved for high-risk active trading.

5. Tiger, the Million-Dollar Moment, and What Comes Next

Brad’s enpricing, but execution speed and operational stability—from deposits and order placement to stop losses and withdrawals. For an event-driven trader, reliability matters as much try into U.S. equities was closely tied to Tiger.

He values not just as strategy.

When his portfolio first crossed USD 1 million, Brad felt immediate relief.

“I didn’t feel trapped by a job anymore.”

To him, the milestone represents freedom of choice—not a finish line.
What matters more is whether the process remains repeatable.

6. Final Thought

Brad’s journey isn’t about guessing stocks or chasing headlines.

It is built on information filtering, event-driven logic, disciplined risk control, and emotional regulation—amplified by AI tools.

For most investors, the lesson is not to copy his trades, but to understand how preparation, conviction, and discipline intersect when opportunity appears.

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