On March 12, 2020, U.S. stocks triggered circuit breakers within minutes of opening. The Dow Jones Industrial Average closed down over 2,300 points, a decline of nearly 10%. In just ten days, circuit breakers were triggered four times—even the financial crisis twelve years earlier wasn’t this intense. The worst single day in 2008 saw the Dow drop 778 points. What fell in one day now was three times that amount.

It all began with the global spread of COVID-19.

But what was truly frightening wasn’t the magnitude of the decline itself. What was truly frightening was: no one knew what would happen next.

All Models Failed

As a long-term market observer, I tried to do all the “right things” during those days: read technical charts, study central bank statements, review historical comparisons. But every analytical framework I habitually used was telling me the same thing—“Your past experience doesn’t apply here.”

We’re accustomed to using the known to infer the unknown. When we see stock market crashes, our instinctive response is: “It fell in 2008 too, and eventually recovered.” But 2008 didn’t have global lockdowns. No cities of ten million people becoming ghost towns overnight. No cruise ships turning into floating virus incubators, no masks becoming national strategic resources.

Our tools—whether technical analysis or fundamental analysis—were all constructed in a “normal world.” When the world’s operating rules themselves change, these tools become like paper umbrellas trying to block a tsunami.

Popper’s Reminder

During that period, I revisited the work of philosopher of science Karl Popper.

Popper’s most famous assertion is: a theory can only be called scientific if it is falsifiable. This doesn’t mean “science is just stuff that gets overturned,” but rather—science’s value lies not in “proving what is right,” but in “acknowledging what might be wrong.” A good theory must specify in advance under what conditions it would be refuted. If a theory can never be wrong, it’s not science—it’s faith.

I found this line of thinking particularly powerful when applied to investment and decision-making.

Most investors—including myself—spend too much time seeking evidence for “why I’m right.” We look for data supporting our views, listen to analysts who agree with us, and seek comfort in echo chambers on social media. The essence of these behaviors is “verification” rather than “falsification.”

But Popper tells us that real knowledge progress comes from falsification—from actively asking: “Under what circumstances would my judgment be wrong?”

The Power of “I Don’t Know”

Honestly, during those days in March 2020, I did something few people in investment circles are willing to admit: I told myself—I really don’t understand this.

Not false modesty, but genuinely not knowing what would happen next.

I didn’t know how long it would take to develop vaccines (the most optimistic prediction then was 18 months, with most experts thinking it impossible). I didn’t know how long lockdowns would last. I didn’t know whether central banks’ massive quantitative easing would trigger inflation. I didn’t know whether global supply chains would break down.

Each “I don’t know” made me more lucid.

Because the trap of “I know” is—it makes you act prematurely. Before you truly understand the situation, you make potentially ruinous decisions based on incomplete information. The power of “I don’t know” is—it makes you wait. Wait for more signals, wait for clearer pictures to emerge.

In running companies, I’ve learned similar lessons. Every day of entrepreneurship is filled with uncertainty, and the most dangerous decisions I’ve witnessed often don’t come from “not knowing what to do,” but from “thinking you know.” Those decisions made with overconfidence, leaving no exit routes—those are truly fatal.

Reality Is Always More Brutal Than Models

What happened to that week’s market afterward?

On March 16, the Dow fell another nearly 3,000 points, setting the record for largest single-day point drop in history. Then, over the following months, while almost all analysts remained bearish, U.S. stocks began a mind-boggling V-shaped recovery. By summer, many people started saying “I knew all along it would bounce back.”

But let’s be honest: no one “knew” this in March. Those who later claimed they saw the bottom coming weren’t sharing insights—they were rewriting memory.

How would Popper view this? He’d probably say: “The fact that markets recovered doesn’t mean your judgment at the time was correct. It just means that this time, you happened not to be falsified.”

Reality is always more complex and more brutal than our models. What we can grasp is always just one facet of reality. This isn’t pessimism—it’s cognitive clarity. And in this era when even market analysis is disrupted by falsificationism, when information floods make us think we can analyze everything, predict everything, this clarity becomes even more precious.

This Day in History

March 13, 2020. If viewed from the future, this day will be remembered not for its decline, but for revealing a truth: all our cognitive frameworks are fragile when facing true “unknown unknowns.”

Since then, I’ve maintained greater skepticism toward the word “certainty.” Not avoiding judgment, but leaving a question mark after every judgment.

If Popper taught us one thing, it’s this: the best knowledge isn’t the knowledge of “I know,” but the knowledge of “I know what I don’t know.” And in this era when even AI hallucinates, acknowledging our ignorance may be the most lucid stance of all.