Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.
In investing, you place a bet and then wait. It often takes months or years before you find out whether the decision was sensible or not.
That delay creates a problem. Outcomes are uncertain because information is incomplete and the world does not unfold in straight lines. If you judge decisions purely by how they turn out, you will learn the wrong lessons.
The correct lens is probability, not prediction.
Poker and Motorways
Consider a hand of poker.
You push all your chips into the middle with seven-deuce offsuit, the worst starting hand in the game. Your opponent calls with a stronger holding. The cards run out in your favour. You win the pot.
The result is undeniable. The chips are now yours.
But at the moment you made the decision, you were behind. You required the deck to save you. You needed favourable variance to rescue an inferior position.
Over one hand, that can look like courage rewarded. Over many hands, it is a losing strategy.
The same pattern appears outside of cards.
Imagine someone crossing a busy motorway on foot to save a few minutes rather than using the pedestrian bridge. They run, traffic misses them, and they reach the other side unharmed.
For that one attempt, the choice appears justified. But the upside was trivial and the downside irreversible. Survival depended on timing and luck.
In both cases, the outcome does not tell you whether the decision was intelligent. It tells you only what happened.
If you allow outcomes alone to train you, you will gradually teach yourself to take risks that feel good when they work and feel unlucky when they do not.
Expected Value and Survival
Expected value is simply the weighted average of possible outcomes. If you repeatedly take positions where the upside meaningfully exceeds the downside, the arithmetic works in your favour over time.
But that arithmetic assumes repetition. It assumes you remain in the game long enough for the edge to express itself.
Never forget the six-foot-tall man who drowned crossing the stream that was five feet deep on average.
Averages conceal extremes. A strategy that succeeds frequently but carries a small chance of ruin is far more fragile than it appears.
Many intelligent investors misjudge this. They identify a real edge, sometimes even quantify it carefully, and then size it as though bad outcomes arrive gently and evenly spaced. They do not.
Liquidity and the Illusion of Skill
Markets introduce another layer of complexity.
Think back to the last crypto bull market. Capital was plentiful, credit was easy, and risk appetite expanded steadily. Prices rose across a wide range of assets, regardless of quality.
When liquidity dominates, selection matters less than participation. Owning almost anything can produce gains because the primary force lifting prices is money flowing in rather than fundamentals improving.
That environment delivers reinforcement.
When a speculative position doubles quickly, the emotional sequence is subtle but powerful. Confidence grows. Position sizes increase. Standards relax slightly. The internal story shifts from “this might work” to “I understand something others don’t.”
Nothing about the underlying asset may have changed. What has changed is the environment. Rising prices validate behaviour before they test it.
If you're a duck floating on a pond and it's been raining and you're going up in the world, after a while you think it's you and not the rain. That you're some duck.
The danger lies in what happens next. Gains earned in a forgiving environment expand risk-taking just as the environment itself becomes less forgiving. When liquidity tightens and optimism fades, the same behaviour that once produced easy profits begins to reveal its cost.
What looked like insight was often just exposure to a rising tide.
Guardrails and Circuit Breakers
Because outcomes are unreliable teachers, investors need structure.
A defined process forces assumptions into the open before money is committed. It limits position size relative to uncertainty. It requires clarity about what would invalidate the thesis.
Guy Spier has described these as circuit breakers . They are mechanisms designed to interrupt impulsive behaviour before it becomes expensive.
Importantly, a good checklist does not only tell you when to buy. It also tells you when not to. Some of the most useful questions are framed in reverse: what would make this a mistake? What must be true for this to fail? What am I assuming without noticing?
Looking for reasons to disqualify an investment often reveals more than looking for reasons to justify it.
These guardrails do not guarantee success. They reduce the likelihood of self-inflicted damage.
Asymmetry and Staying Solvent
One of the clearest descriptions of intelligent risk-taking is:
Heads I win, tails I don't lose much.
The objective is not to be right frequently. It is to structure decisions so that losses are contained and gains, when they arrive, are meaningful.
A modest edge applied with restraint can compound for decades. The same edge applied aggressively can undo itself in a single cycle.
In a probabilistic world, outcome alone does not reveal decision quality. What you control is where you commit capital, how much you commit, and how exposed you are to a result that prevents you from acting again tomorrow.
The discipline is straightforward but demanding: avoid positions that require rescue, size positions so that a bad draw does not end the game, and allow repetition to do its work.
Investing is less about being brilliant and more about avoiding the kind of mistake you can’t come back from.
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