Game theory sounds abstract until you sit in a trading interview and realise the interviewer is using it to watch how you think. It is the study of decisions made when several people are deciding at once and everyone’s outcome depends on everyone’s choice, which happens to be a fair description of a market.
This post keeps things short and practical. We explain what game theory is, work through one example, and then look at why trading firms lean on it when they interview for Quant Trading for Quant Researcher roles.
If you want the full treatment, with more examples and the solution techniques worked out by hand, our Probability course has a dedicated Game Theory lesson that goes much deeper than this overview.
Table of Contents
What Is Game Theory?
Most of the probability you learn treats the world as a fixed source of randomness. You draw from a distribution, compute an expectation, and make a decision. Game theory adds one twist: part of what you are reasoning about is another rational person who is reacting to you. Your best move now depends on their best move, and theirs depends on yours.
Every game has three ingredients:
- Players
The decision makers. In a trading question these might be two market makers, a buyer and a seller, or you against the rest of the market. - Strategies
The actions available to each player, and the plan for which one to take. - Payoffs
The number each player receives for every combination of choices. By convention each player wants to maximise their own payoff, and larger is better.
Once a situation is written down this way, you can solve it. The goal is usually to find a stable outcome: a set of choices where no player can do better by changing their own decision while everyone else holds theirs fixed.
A Worked Example: Two Market Makers
Take two market makers who each have to decide whether to quote a Wide spread (keep spreads fat and share the profit) or a Tight spread (undercut the rival to win the order flow). Their monthly profits, in arbitrary units, look like this. Each cell shows (your payoff, rival’s payoff):
| Rival: Wide | Rival: Tight | |
|---|---|---|
| You: Wide | (10, 10) | (4, 12) |
| You: Tight | (12, 4) | (6, 6) |
Read the bottom-left cell as: if you quote Tight and the rival quotes Wide, you earn 12 and the rival earns 4. Now work out your best move by fixing the rival’s choice and comparing your two options.
- If the rival quotes Wide
You compare the first column: Wide earns you 10, Tight earns you 12. You prefer Tight. - If the rival quotes Tight
You compare the second column: Wide earns you 4, Tight earns you 6. You prefer Tight.
Tight is better for you no matter what the rival does, so Tight is your dominant strategy. The payoffs are symmetric, so the same is true for the rival. Both of you quote Tight, and you each earn 6.
Here is the catch. If you had both quoted Wide, you would each have earned 10. The stable outcome leaves both of you worse off, because each side is individually tempted to undercut. This is the classic Prisoner’s Dilemma, and it is the cleanest illustration of why individually rational behaviour can be collectively poor. On a real desk it is part of why spreads get competed down toward the cost of providing liquidity: an agreement to keep spreads wide is not stable when every participant has a private incentive to undercut it.
Why Game Theory Comes Up in Trading Interviews
Game theory is a favourite interview topic because it separates candidates who can compute an expected value from candidates who can compute an expected value while the other side is trying to take their money. A few specific reasons it shows up:
- It tests reasoning about other people’s incentives
A market maker who quotes a price has to ask who would trade against that quote, and why. That is a game-theoretic question, not just a probability one. - It rewards clear, structured thinking under pressure
Most of these questions have a short, exact answer that you reach by a clean argument, which is precisely what an interviewer wants to watch you produce on a whiteboard. - It connects directly to trading concepts
Adverse selection, the winner’s curse, signalling, and the value of being unpredictable all come straight out of game theory.
It is worth being honest about the scope. Game theory is one tool among several, not the whole interview, and you do not need a graduate course to handle the questions that come up. You need the vocabulary, a handful of solution techniques, and the discipline to apply them carefully.
Where to Go Deeper
This post covered the core idea and one example. The full Game Theory lesson in our Probability course takes a deeper dive and works through the techniques you are most likely to be asked about, including:
- Dominant strategies and iterated elimination, including the “guess two-thirds of the average” game
- Nash equilibrium and how to find one by hand with best-response analysis
- Mixed strategies and why randomising your behaviour can be the optimal response to an adversary
- Zero-sum games and the minimax theorem
- Sequential games, backward induction, and credible threats
- The winner’s curse and how adverse selection shapes the way market makers quote
If you are preparing for quant interviews, that lesson is the natural next step after this overview.