Author: darkzodchi , Crypto KOL
Compiled by: Felix, PANews
The financial market is full of highly educated and intelligent people, but only a minority make money, and a significant portion of them have lower levels of education. They've learned a lot of theory, yet they still can't make money. What causes this "anomaly"? Crypto KOL darkzodchi, based on his own experience and research, analyzes this phenomenon and identifies five common cognitive errors made by intelligent people. Details are below.
I know someone who can mentally solve differential equations. He graduated with honors and works at a top-tier tech company you've definitely heard of, earning $180,000 a year. But his net worth is practically zero. If you include his car loan payments, it's probably even negative.
In stark contrast, most of my friends dropped out of school before the age of 20 to dedicate themselves to entrepreneurship or trading, and now earn more than those with finance degrees. Half of them don't even know basic economic terminology; they only know when to act.
What's going on?
I've seen this countless times: strategists almost never act. Have you ever wondered why university professors don't drive Ferraris? Because they know how to act in theory, but not how to do it in practice.
Let's talk about five math mistakes that particularly confuse smart people, and the "foolproof" solutions for each one.
Myth 1: Pursuing precision while neglecting the importance of action.
Intelligent people like to pursue absolutely correct answers. This pursuit is rewarded in school: in math exams, a 97% accuracy rate is far inferior to 100%.
But in the world of money? A 97% accuracy rate next month is far less valuable than the current 70% accuracy rate.
I witnessed a friend spend two years building a "perfect" liquidity provision project, even raising funds for it. He used custom metrics and conducted backtesting for 15 years, covering three different volatility environments. Frankly, that's remarkable work.
But by the time he launched his model, the market environment had changed. His model was targeting a market that no longer existed. Meanwhile, an unknown person on the CT forum made $80,000 with just three simple lines of heuristic code—"buy when funding rate is negative, sell when it's positive"—while my friend was still struggling to figure it out.
There is actually a formula for this, called information value, which tells you when it's worthwhile to conduct more research:
VoI = EV (Decision Based on More Information) - EV (Immediate Decision) - Delay Cost
If VoI < 0, stop the research and take immediate action.
The cost of delay is something smart people often underestimate. They think the cost is zero because doing research makes them "feel productive." That's not the case. Markets change, opportunities disappear, and funds sit idle.
I often make this mistake myself. In August 2025, I spent a month thinking about how to build a Polymarket project, trying to come up with an extremely complex solution, until I completely forgot about it.
By October, I had changed my mindset and started writing code every day. In November, the project went live.
More time is wasted on "thinking about ideas" than on actually creating them. This is a classic example of self-destruction.
Solution: Set a deadline before you begin your research. "No matter how much information I have, I will make a decision by Friday." This single habit is more valuable than any formula.
Myth 2: Looking for patterns in noise (and betting based on them)
This is a big problem, and a problem unique to intelligent people.
If you're intelligent, your brain is like a pattern recognition machine. It's this ability that allows you to achieve excellent grades and get your dream job. You can always see structure where others see chaos.
The problem is: financial markets are mostly chaotic. Your brilliant pattern-matching brain will find patterns that don't even exist. Then it will convince you these patterns are real, then you'll place bets, and eventually you'll lose everything.
This condition is called "overfitting." Here's an example to illustrate how it works.
Take any dataset: stock prices, temperature readings, anything will do. Run enough combinations of indicators, and you'll surely find a formula that can "predict" the past with 95% accuracy. In backtesting, it looks fantastic. But it's garbage; it finds patterns in the noise.
Overfitting test:
- If your model has N parameters, and you tested K combinations:
- Expected number of false discoveries = K × significance level
- Testing 100 metrics at a p < 0.05 level yielded 5 “significant” results that were purely noise.
I was once deeply involved myself. In 2022, I discovered a "pattern" on Ethereum that worked for three months. It was probably related to the trading volume ratio on Binance and Coinbase. The backtesting looked flawless, and I excitedly invested $2,000 immediately.
As a result, I lost $400 in the first week. This pattern was actually noise. I wasn't smart enough at the time to realize that the problem was the very act of "discovering it."
Data from Polymarket strongly confirms this. When I analyzed 112,000 wallets, those running the most complex strategies (more than 10 signals, sophisticated machine learning models) actually underperformed those using only 2-3 simple rules. Higher complexity = more overfitting = more losses.
Solution: Before trusting any pattern, ask yourself, "If I test 100 random strategies, how many of them would appear to be purely lucky?" If the answer is more than one or two, then your "finding" is likely just noise. The Bonferroni correction method can help: divide the significance threshold by the number of strategies you tested.
Myth 3: Diversifying investments when concentrated investment is needed (and vice versa).
I feel this very strongly because a few years ago I was running five different projects at the same time, and they all failed.
Every smart person knows the adage "Don't put all your eggs in one basket." This is like the first law of finance: diversification. Modern portfolio theory, Markowitz, Nobel laureate.
However... actual mathematical calculations reveal some more subtle truths that most people overlook.
Diversification protects you when you lack an advantage. If you're randomly picking stocks, then diversification is certainly fine. You don't actually know what the future holds.
However, when you truly have an advantage (you've genuinely discovered an undervalued investment opportunity), diversification can actually harm your returns. This is because you're diluting your best ideas with mediocre ones.
- Kelly Criterion: f* = Advantage / Odds
- If your advantage is 15% and the odds are 1:1: f* = 0.15 / 1.0 = 15% of your capital.
- If your advantage is 3%: f* = 0.03 / 1.0 = 3% of the funds
The formula literally means: the greater the advantage, the more you bet; the smaller the advantage, the less you bet. It doesn't say "split all your money equally across 47 positions".
Warren Buffett (who is indeed very good at this) has said many times that diversification is a form of protection against ignorance. If you know what you are doing, diversification is meaningless.
I used to hold 5-10 different tokens during the SOL and BSC craze. The best-performing token rose by 120%, but it only made 4% of my portfolio, earning me only about $80 in total. Meanwhile, my largest holding fell by 40%.
The top Polymarket wallets I've researched only hold 3-5 positions at any given time, and that's all, but the size of each position is determined by its strengths.
Solution: Honestly ask yourself: Do I have an advantage in this trade? If so, increase your position (within the Kelly criterion range). If not, either abandon it entirely or go for an index-based allocation. The compromise of "putting a little in everything" is the graveyard of returns.
Myth 4: Anchoring to irrelevant numbers
Intelligent people are particularly susceptible to the anchoring effect because they can remember numbers, and those numbers become subconscious reference points for all future decisions.
"I bought ETH at $4,800."
So what? The market doesn't care. This number is completely, utterly, 100% irrelevant to whether ETH is worth buying today. But your brain has already welded $4,800 to your pride. Now, every price below that feels like a "loss," and every price above that feels like "breaking even."
This is more than just a feeling. It changes your behavior in measurable ways:
- You held a losing position for too long (waiting for it to "break even").
- You sold your profitable positions too early (fearing a return of profits).
- You evaluate new opportunities based on past prices rather than future value.
There's a very simple test to verify this. Daniel Kahneman calls it, "Would I still buy it today?"
- You own an asset with a current price of P.
- You buy at a price of P_0.
- P_0 can be completely ignored, as it is already a sunk cost.
Question: If you had cash right now, would you buy this asset at a price of P?
- If you will → hold
- If not → Sell
- If you are unsure → your position is too large.
I had to write this on a sticky note and stick it on my monitor: "Will I buy today?" Because even knowing this bias, I still unconsciously think, "But I'm only down 20% right now, let's wait and see if there's a rebound." The anchoring effect is that powerful.
This doesn't just apply to transactions. Salary negotiation? If your current annual salary is $90,000, you use that as an anchor to ask for $100,000. But the market salary for your position might be $130,000. You're actually negotiating with yourself using an irrelevant anchor. Changing jobs? "I've worked here for four years." So what? The question is, should you stay here or go somewhere else for the next four years? The past four years are in the past anyway.
Solution: Before making any financial decisions, write down the numbers that affect you. Then ask yourself, "Does this number really relate to future outcomes, or am I just being held back by past experiences?" If it is a past experience, cross it out (literally, cross it out with a pen).
Myth 5: Mistaking understanding for action
This is the cruelest misconception. To be honest, it's also my biggest weakness.
Intelligent people who have read about compound interest will nod in agreement. They understand the Kelly Criterion, they can explain loss aversion at a dinner party, and they have read *Thinking, Fast and Slow* (or at least a summary).
Then they assume that understanding equals action. That's not the case at all; it's far from it.
Understanding compound interest doesn't mean you're investing; understanding the Kelly Criterion doesn't mean you're properly allocating your positions; and understanding loss aversion doesn't mean you're immune to its effects.
This area has been studied. It's known as the "knowledge-behavior gap," and the gap is significant. One study found almost no correlation between financial literacy scores and actual financial outcomes. People who scored 95 on a financial literacy test were just as likely to accumulate credit card debt as those who scored 50.
Financial Results = Knowledge × Action × Persistence
No matter how extensive your knowledge, if you take no action, the result will be zero.
The formula is obvious, but smart people always get stuck on the first step. They keep accumulating knowledge: reading another book, taking another course, listening to another podcast. Because learning feels both secure and safe. Action, on the other hand, feels both risky and uncomfortable.
I know, because I've experienced it firsthand. Before my first trade, I read three books on investing. I could explain the efficient market hypothesis, factor investing, option pricing—all of it. And my first real trade? I panicked and lost 12% in three days. All that knowledge ultimately came down to emotions.
Do you know what helped me in the end? I was on the basketball court, pulled out my phone, and placed a $50 bet on Polymarket, just to try it out. Not $5,000, just $50. It was a small stake, real money, with almost no chance of winning—but I just wanted to feel what betting was like.
Suddenly, those probability formulas stopped being abstract. They became directly relevant to my money. That $50 bet made me understand my biases better than 11 books combined.
Solution: After reading this article, do only one thing—not five things, just one. Make a small bet, calculate the expected value, and verify a hypothesis. The gap between knowledge and action is bridged through countless small actions.
Why is this more important than we think?
What bothers me most about all this is that these five mistakes aren't due to "stupidity," but rather to "being too clever in the wrong direction." Schools train us to be meticulous, precise, and knowledgeable. But the market rewards speed, general accuracy, and proactive action.
The rules of the game have changed, but no one told us.
The good news is that once you see these pitfalls, you can no longer ignore them. Every time you find yourself spending 3 hours researching a $200 decision—that's pitfall one. Every time you spot an exciting "pattern" in a crypto chart—that's pitfall two. Every time you spread your money across 20 positions in the name of "diversification"—that's pitfall three.
The smartest thing a smart person can do is to become a little "dumber." Simpler strategies, smaller positions, faster decision-making. Less research, more action.
Mathematics supports this, my study of 112,000 wallets proves it, books prove it, and personal, costly mistakes prove it.
Stop looking and start putting it into practice!
Related Reading:A Must-Read for Beginners: Five Trading Secrets Shared by Experienced Traders
