About the author
Kyo Won Jeong
Researcher, Quantitative Trader

He holds a Ph.D. in Electrical and Computer Engineering from UC San Diego (advisor: Pavel Pevzner) and a B.S. in Electrical Engineering from Seoul National University. He is a bioinformatics (proteomics) researcher in Germany. He works in algorithms, machine learning and statistical modeling, and applies the same methodology to systematic trading.

Thinking in Probabilities 1

A broken TV and probabilistic thinking

2026-09-21

Imagine a company making TVs with a 0.01% failure rate.

If they plan to sell 500 TVs, they may not need to worry much about defective units.

But what if they plan to make 100,000?

The failure rate is still exactly the same: 0.01%.

The difference is that now the company has to prepare for failures to happen: warranty costs, replacement units, customer support, and so on.

The probability hasn't changed.

The number of repetitions has.

That is where I think probabilistic thinking begins to shine:

Not seeing an event as an isolated occurrence, but as one possible outcome within a much larger process.

And this perspective becomes especially important in trading.

A single SL or TP doesn't tell you much about probability.

But once you assume the same trade will be repeated hundreds of times, things start to emerge:

win rate,

risk-reward,

streaks of losses,

expected value,

the distribution of outcomes,

and, most importantly, the need for rules and discipline.

Seeing one trade is fundamentally different from seeing it as one of many repeated trades.


This is educational writing about trading. It is not investment advice or a recommendation to make any particular trade.

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