Cognitive Biases in Bitcoin Investing

Short answer: Cognitive biases are thinking errors that everyone makes, including smart and experienced investors. With bitcoin they hit harder than with most investments, because the price swings a lot and is visible around the clock. You won't get rid of them, but you can recognise them and defuse them with fixed rules. This catalogue shows twelve of them, each with an example from the bitcoin market and a countermeasure.

This article is a reference. How to bear the swings emotionally is explained in HODL psychology. The typical cycle of greed and fear is described in FOMO, panic and capitulation. Here we look at the individual thinking errors behind them.

Where our knowledge of thinking errors comes from

In the 1970s, the psychologists Daniel Kahneman and Amos Tversky showed that people do not judge like calculating machines when deciding under uncertainty. We use rules of thumb, so-called heuristics. They are fast and usually good enough, but they lead to predictable errors. Their 1974 paper "Judgment under Uncertainty: Heuristics and Biases" describes three of them: availability, representativeness and anchoring. In 1979 came prospect theory, which explains why losses hurt more than gains please. Kahneman received the Nobel Memorial Prize in Economics for this work in 2002; Tversky had died in 1996.

Other researchers described further biases, such as Baruch Fischhoff hindsight bias (1975) and Hal Arkes with Catherine Blumer the sunk cost effect (1985). Not every term in this catalogue comes from Kahneman and Tversky. For each one, we say where it comes from.

The twelve thinking errors at a glance

1. Confirmation bias

What it is: You mainly look for and believe information that supports your opinion. What contradicts it, you overlook or dismiss. The psychologist Peter Wason showed this as early as 1960 with simple number puzzles.

With bitcoin: You only follow accounts that love bitcoin, or only ones that hate it. Algorithms reinforce this: whoever clicks on price targets of a million gets more of them. The result is an echo chamber in which every piece of news sounds like confirmation.

Countermeasure: Deliberately read the best criticism of your position. For bitcoin holders, that means, for example, knowing the weaknesses of your favourite model. Before every purchase, ask yourself: what would have to happen for me to be wrong?

2. Recency bias

What it is: You give too much weight to what has just happened and project it into the future.

With bitcoin: After a steep rise it feels as if it will go on like this forever. After a crash it feels as if bitcoin is finished. In June 2026 bitcoin closed at $58’628, after standing at $124’673 in October 2025. Anyone who only looked at the last few months considered a further crash certain. Anyone in 2021 who only looked at the last year considered $100’000 a done deal.

Countermeasure: Look at long periods. The chart further down overlays all bear markets. It shows that deep declines have happened several times and that recovery took years each time.

3. Anchoring

What it is: A number you have seen once influences your estimate, even if it is random. In an experiment by Tversky and Kahneman, participants spun a wheel of fortune that stopped at 10 or 65. Afterwards they were asked to estimate what percentage of UN member states are African countries. The group that got 10 estimated 25% on median, the group that got 65 estimated 45%.

With bitcoin: Your anchor is often your purchase price or the last all-time high. "I'll only sell once it's back at $124’000" or "I won't buy more below $60’000 because I once bought cheaper." Neither number says anything about today's value.

Countermeasure: Make decisions without looking at your entry price. Ask: would I buy at this price today if I had nothing yet? If you need a reference point, use one that can be calculated transparently rather than a number from your memory.

4. Loss aversion

What it is: A loss hurts more than an equal gain pleases. Kahneman and Tversky described this in 1979 in prospect theory. In a later measurement (1992) the factor was around 2.25.

With bitcoin: A drop of 30% feels like a disaster, a gain of 30% only like "quite nice". The consequence: you sell after a crash to end the pain, or you hold a bad investment too long so you don't have to realise the loss.

Countermeasure: Only hold so much that a fall of 70 to 80% does not change your life. Look at the price less often. More on this in HODL psychology.

5. Overconfidence

What it is: You consider your knowledge and your timing better than they are. In 2001, Brad Barber and Terrance Odean analysed the accounts of around 35’000 US households. Men traded 45% more than women, and trading cost them 2.65 percentage points of return per year, women 1.72 percentage points.

With bitcoin: After a few successful trades you believe you can spot the top and the bottom. You use leverage, trade daily or sell "just briefly" to buy back cheaper.

Countermeasure: Write down every buy or sell decision with date and reasoning. After a year, compare your result with a simple savings plan that would have bought stubbornly over the same period. If you are not clearly ahead, the savings plan is the better strategy.

6. Herd behaviour

What it is: You do what everyone does because you assume the others know something. Economists speak of information cascades: everyone follows the person before them until their own information no longer matters.

With bitcoin: When colleagues, taxi drivers and relatives talk about bitcoin, many people get in, usually after a strong rise. In a crash it runs the other way: when everyone sells, holding feels like a mistake.

Countermeasure: A savings plan with a fixed amount and a fixed date. It buys regardless of what the herd is thinking. The whole cycle of greed and fear is shown in FOMO, panic and capitulation.

7. Hindsight bias

What it is: In hindsight, everything seems predictable. Baruch Fischhoff showed in 1975: whoever knows the outcome of an event considers it more likely than they would have beforehand, and misremembers their own earlier assessment.

With bitcoin: "It was obvious that November 2021 was the top." At the time it was obvious to nobody. Whoever believes they knew it trusts themselves with too much timing next time. This error therefore leads straight to overconfidence.

Countermeasure: The journal from point 5. It shows you in black and white what you really thought back then.

8. Sunk cost effect

What it is: You hold on to something because you have already put a lot into it, not because it is still worthwhile. In 1985, Hal Arkes and Catherine Blumer sold theatre season tickets at different prices. Those who had paid full price attended more often in the first half of the season than those who had received a discount, even though the price had long been paid.

With bitcoin: An altcoin that has lost 90% is kept "because I've already lost so much". Or a strategy that doesn't work is continued because you have already invested time and fees.

Countermeasure: What you paid is gone, whatever you decide. The only question is what you want to do with the money from today. Ask it as if you had just received the amount in cash in your account.

9. Availability bias

What it is: What comes to mind easily, you consider frequent or important. Tversky and Kahneman also describe this rule of thumb in 1974.

With bitcoin: Headlines about an exchange collapse, a ban or a hack stick. Afterwards bitcoin seems riskier than it is for someone who holds their coins themselves. Conversely, stories of million-dollar gains stick and make big gains seem normal.

Countermeasure: Separate the news from its impact. With every headline, ask: does this change anything about my reasons for holding bitcoin? The answer is usually no. Many of the recurring scare stories are checked in The 15 most common bitcoin myths.

10. Gambler's fallacy

What it is: You believe that after a streak the opposite must come, as if chance had a memory. Tversky and Kahneman explain the error in 1974 with the representativeness heuristic: we expect even short sequences to look "balanced".

With bitcoin: "Bitcoin has fallen three months in a row, now it has to rise." Or: "The cycle says the bottom comes exactly in this month." A price owes you no countermove. It can keep falling longer than you think possible.

Countermeasure: Don't bet on streaks. Plan so that your approach works whether next month is red or green. Whether there is a fixed pattern at all is discussed in The bitcoin four-year cycle.

11. Unit bias

What it is: We want to own whole units and feel fractions are worth less. Andrew Geier, Paul Rozin and Gheorghe Doros showed in 2006 that people usually take one unit of food, regardless of its size.

With bitcoin: "A bitcoin is too expensive" or "I'd rather buy a coin for $0.10, I get thousands of those." The price per unit says nothing about whether something is cheap. €1’000 buys the same share of bitcoin whether you count it in BTC or sats.

Countermeasure: Think in sats and shares instead of whole coins. How that works is shown in Sats explained.

12. Survivorship bias

What it is: You only see those who survived and conclude that their path is safe.

With bitcoin: On social media, people tell how they bought early and held. Those who were liquidated with leverage in 2018 or 2022, lost everything in altcoins or could no longer find their seed tell nothing. With coins and exchanges, too, you only see the ones that still exist.

Countermeasure: With every success story, ask: how many tried the same thing and failed? Don't adopt a strategy just because a winner recommends it.

Bear markets show all thinking errors at once

In a crash almost all biases come together: the anchor is the last high, loss aversion screams, the headlines are grim, the herd sells. The figures from the site's daily data show how deep and long these phases were:

Why selling in particular is so prone to such traps is explained in The psychological trap when selling.

What helps against almost all thinking errors

You don't have to keep twelve countermeasures in your head. Four habits cover most of them:

1. Write down rules before it gets serious. How much you buy monthly, when you sell, what you do at −50%. In the moment of decision you only ask: what does my plan say?
2. Automate. A savings plan takes away the decision of whether now is a good time. That defuses herd behaviour, recency bias and the gambler's fallacy.
3. Keep a journal. Date, amount, reasoning. It helps against hindsight bias and overconfidence.
4. Mix your sources of information. Read criticism, not just agreement, and with headlines and success stories ask about the whole population.

All twelve thinking errors at a glance