Quant interview preparation

Prop market making and quantitative research, weighted the way the interviews actually are: probability and expected value, statistics and machine learning, market making logic, programming and options. Every question is either traced to a named firm from a public candidate report, or tagged at desk level when we could not trace it, and every probability answer shows the reasoning path rather than just the number.

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100 questions, mapped to the firms that asked them

Questions
100
Traced to a firm
53
Firms
15
Updated
September 2026
Asked at
All firmsOld Mission Capital12Tower Research Capital10Jump Trading7Akuna Capital5Citadel4D.E. Shaw3Jane Street3AQR Capital Management2DRW2Millennium Management2Schonfeld2Squarepoint Capital2Susquehanna International Group2Belvedere Trading1Optiver1
Topic
All topicsProbability10Coins, cards and games6Expected value8Statistics11Market making15Estimation and mental maths4Stochastic processes4Regression5Machine learning6Time series6Programming10Options and derivatives8Fit and motivation7
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  1. 026You start with fifty dollars and bet a dollar on a fair coin each time. What is the probability you reach a hundred before going broke, and how does it change if the coin is slightly against you?Stochastic processesIntermediatetechnicalQuant tradingQuant research

    Say this

    In a fair game it is exactly one half, because your wealth is a martingale and the stopping value must average back to fifty. Tilt the odds slightly against you and the probability collapses, not linearly but exponentially in the number of steps.

    Then walk it

    1. Fair case: wealth is a martingale, so by optional stopping, 50 equals 100 times p plus 0 times (1 minus p), giving p equal to 0.5. In general starting at a with an upper barrier b, the probability is a over b.
    2. Biased case: with win probability q the hitting probability is (1 minus r to the a) over (1 minus r to the b) where r is (1-q)/q.
    3. Put a number on it. At q equal to 0.49, r is about 1.0408. With a equal to 50 and b equal to 100, the probability of reaching 100 drops to roughly 12 percent. A one percent edge against you turns a coin flip into a 1-in-8 shot.
    4. That sensitivity is the entire lesson. Expected value per bet is minus two cents, which sounds trivial, but over the hundreds of bets you need to walk the barrier it compounds into near certainty of ruin.
    5. And the practical version on a desk: expected time to absorption in the fair case is a times (b minus a), so 50 times 50 equals 2,500 bets. Casinos and market makers both live on this asymmetry. Small edge, high repetition, deep pockets.

    Where candidates lose it

    Giving a over b and stopping. The interesting content is how brutally the biased case differs, and candidates who cannot state the r to the power formula usually also guess that a one percent edge changes the answer by about one percent. It changes it from 50 percent to 12 percent. Put a number on it.

    Expect next

    • What is the expected number of bets until you stop?
    • What happens if you bet your whole stack each time instead?
    • How does this relate to a trader's drawdown limit?

Firm tags come from public, anonymous candidate reports on Wall Street Oasis: strong signal, not sworn testimony. Firms are named as the places a question was reported, not as partners of Fin Maverick. Answers are written for this page to show how to think out loud; they are not scripts to recite.