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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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Question bank

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 Capital5Citadel4DED.E. Shaw3Jane Street3ACAQR Capital Management2DRW2Millennium Management2Schonfeld2SCSquarepoint Capital2Susquehanna International Group2Belvedere Trading1Optiver1
Topic
All topicsProbability10Coins, cards and games6Expected value8Statistics11Market making15Estimation and mental maths4Stochastic processes4Regression5Machine learning6Time series6Programming10Options and derivatives8Fit and motivation7
Level
AnyCoreIntermediateHard
Type
AnyBrainteaserTechnicalCaseMarket viewFit
Showing 1–2 of 2 · filtered from 100Clear filters
  1. 062You have made me a market. If the true answer falls inside your market, how much would you risk to win a hundred dollars?Market makingHardtechnicalAkuna CapitalTrading · Chicago · 2025

    Say this

    That depends entirely on how wide I quoted and how confident I am, and those two are linked. If I quoted a tight market I should not be very confident the answer is inside it, so I would risk little. If I quoted wide, I should be confident, and I would risk more. The honest answer is to price my own probability and then bet a fraction of Kelly.

    Then walk it

    1. The question is a consistency check. A tight market is a strong claim, and the interviewer is testing whether my stated width matches my stated confidence. If I said 300 at 310 on the number of Starbucks in New York and then say I am 90 percent sure the truth is inside, one of those is a lie.
    2. So I quantify. Suppose I think there is a 60 percent chance the answer is inside my market. Then risking x to win 100 has expected value 0.6 times 100 minus 0.4 times x, which is positive for x below 150. So fair value is 150 and I would bet meaningfully below that.
    3. Kelly gives the size: bet a fraction of capital equal to edge over odds. At 60 percent on an even-money-ish bet the full Kelly fraction is around 20 percent of capital, and I would take a quarter to a half of that, because my 60 percent is itself an estimate and overbetting Kelly is far more punishing than underbetting.
    4. I would also name the asymmetry in the setup. The interviewer chooses whether to take the bet, so they only take it when they think my price is wrong. That is adverse selection, and it means I should shade my number down from the naive fair value.
    5. So a concrete answer: with a 60 percent belief and an adversary who selects, I would risk around 50 to 70 dollars to win 100, and I would say out loud that I am shading below the 150 fair value because you get to choose whether to trade.

    Where candidates lose it

    Giving a bravado number like I'd risk a thousand, or refusing to name a figure. Both fail. Also failing to notice that your quoted width already implied a confidence level, so an answer inconsistent with your own market gets picked apart immediately. Name your probability, compute fair value, then shade for adverse selection.

    Expect next

    • So tighten your market and answer again.
    • What if I let you choose which side of the bet to take?
    • Explain why you shaded below fair value.

    Reported by candidates at Akuna Capital (Trading, Chicago, 2025). Source: Wall Street Oasis.

  2. 097Describe a technical challenge you solved, so that a non-expert understands it but an expert still learns something.Fit and motivationHardsuperdayAkuna CapitalTrading · Chicago · 2026

    Say this

    Structure it in three layers. One sentence on the problem in plain language that anyone would care about, then the mechanism in an analogy with no jargon, then one specific technical detail that a specialist would find non-obvious. The last layer is what the question is really asking for.

    Then walk it

    1. Layer one, the stakes in plain words: our pipeline took six hours and we needed it in twenty minutes, or the model was accurate in testing and wrong in production and nobody knew why.
    2. Layer two, the mechanism by analogy. Pick an analogy that is load-bearing rather than decorative. For a cache: it is like keeping the twenty files you use on your desk instead of walking to the archive each time, and the hard part is deciding what to throw off the desk.
    3. Layer three, the detail for the expert. One precise, surprising thing. The bottleneck was not compute, it was that we were re-parsing timestamps sixty million times, and interning them cut the runtime by eighty percent. Or: the bug was that the validation split was random rather than chronological, so the model was reading the future.
    4. Say what you rejected and why. That is where an expert learns something, because it shows the decision space and not just the destination.
    5. And control the length. Ninety seconds, then stop and let them ask. The hardest part of this question is not the content, it is the discipline to stop talking, and a candidate who tests understanding by pausing rather than narrating for five minutes has already demonstrated the skill being measured.

    Where candidates lose it

    Picking either the audience-friendly version or the expert version and doing only one. The question explicitly demands both layers. Also do not choose your most complicated project, choose the one where you can name one genuinely surprising detail, because the surprise is what makes an expert lean in.

    Expect next

    • What was the alternative you rejected, and why?
    • How did you know your fix actually worked?
    • Explain it again, but in thirty seconds.

    Reported by candidates at Akuna Capital (Trading, Chicago, 2026). Source: Wall Street Oasis.

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.

Puzzles

100 Quant puzzles, solved step by step

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100 Quant case studies, worked step by step

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