Quant interview preparation

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

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Type

AnyBrainteaserTechnicalCaseMarket viewFit

1. 001There are two bags of stones and you do not know how many black or white are in each. You draw two stones and both are black. What is the probability the next one is black, and will you bet on it?ProbabilityHardtechnicalCitadelQuantitative Trading · New York · 2025

   Say this

   Higher than a half, and yes I would bet on black. Because I do not know the composition, the two black draws are evidence about the composition itself, so I update towards bags that are black-heavy. The draws are not independent trials, they are a sample that teaches me about the urn.

   Then walk it

   1. Set it up properly: put a prior over the unknown mixture, say the proportion of black p is uniform on zero to one, and the draws are conditionally independent given p.
   2. Then this is Laplace's rule of succession. With k blacks out of n draws the posterior predictive probability of another black is (k+1)/(n+2). Two blacks out of two gives 3/4.
   3. The intuition without algebra: seeing black twice shifts the posterior mass towards high p, and the predictive probability is the posterior mean of p, which is now above a half.
   4. Compare it with the alternative model. If I were told the bag was exactly 50/50 and I was drawing with replacement, the answer would be exactly a half and the history would be irrelevant. The whole question is which model you are in.
   5. On the betting half: I would take anything better than even money on black, and I would size it small because 3/4 is a function of my prior, not of data. Two draws is almost no information. If the prior were concentrated near a half the answer moves back towards a half.

   Where candidates lose it

   Saying one half because the draws are independent. They are only independent conditional on the unknown composition, and the composition is exactly what you are learning. The second failure is giving 3/4 with no mention of the prior, as if it were a fact rather than the output of a uniform prior you chose.

   Expect next

   • What if the prior were Beta(2,2) instead of uniform?
   • Now make me a market on the probability and I will trade it.
   • Same question but sampling without replacement from a bag of 10 stones. Does the answer move?

   Reported by candidates at Citadel (Quantitative Trading, New York, 2025). Source: Wall Street Oasis.

2. 084How would you design a system to troubleshoot latency in a trading stack?ProgrammingHardsuperdayCitadelProp Trading · New York · 2026

   Say this

   Timestamp at every hop with one clock, measure distributions not averages, and make the whole path attributable so you can say which segment consumed the microseconds. The design principle is that you cannot fix what you cannot decompose.

   Then walk it

   1. Instrumentation: hardware timestamps at the network card for packet in and packet out, plus software timestamps at each stage, market data decode, book update, strategy decision, order encode, and kernel bypass send. Carry a correlation id through the whole chain so a single event can be reconstructed end to end.
   2. Clocks are the hard part. Use PTP with hardware timestamping across hosts, not NTP, and record clock offset and drift as first-class data. Two hosts disagreeing by fifty microseconds will invent latency that does not exist and hide latency that does.
   3. Statistics: report the median, the 99th, the 99.9th and the maximum. Averages are useless here because the distribution is heavily right-tailed and the tail is exactly what costs money. Track per-segment histograms, ideally with HDR histograms so the tail resolution survives.
   4. Storage and analysis: stream the records off the critical path into a time-series store, then build the two views that actually get used, a per-segment breakdown over time and a drill-down into the slowest individual events. Alert on percentile regressions against a rolling baseline rather than on fixed thresholds.
   5. Then the causes to design for, because the system exists to distinguish them: garbage collection or allocation pauses, page faults, context switches and CPU migration, interrupt coalescing settings, cache misses and false sharing, queueing at the exchange gateway, and simple network congestion. And I would say the measurement must not itself be on the hot path, so lock-free ring buffers with a separate reader thread, because an observability system that adds ten microseconds has destroyed what it measures.

   Where candidates lose it

   Describing logging and monitoring generically. This is a specific systems question and the differentiators are clock synchronisation, percentile rather than mean reporting, and keeping instrumentation off the critical path. Talk in microseconds, and be able to name concrete causes of a tail latency spike.

   Expect next

   • How do you synchronise clocks across hosts, and to what accuracy?
   • Why report the 99.9th percentile rather than the average?
   • Walk me through diagnosing a spike that happens once a day.

   Reported by candidates at Citadel (Prop Trading, New York, 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.