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

AnyCoreIntermediateHard

Type

AnyBrainteaserTechnicalCaseMarket viewFit

1. 093You are long a delta-hedged call. Where does your profit and loss actually come from?Options and derivativesHardsuperdayProp trading firmsDerivatives

   Say this

   From the difference between realised and implied volatility. You earn gamma by rehedging, buying the underlying when it falls and selling when it rises, and you pay theta for the privilege. If realised vol beats the implied vol you paid, the gamma earnings exceed the theta bill.

   Then walk it

   1. The mechanics of gamma scalping: long a call means delta rises as spot rises. To stay hedged you sell into rallies and buy into dips, which is systematically buying low and selling high. Each round trip banks money proportional to the square of the move.
   2. The algebra: daily P&L is approximately half gamma times (change in S) squared minus theta times the time step. Substituting the Black-Scholes relationship between gamma and theta gives P&L proportional to half gamma S squared times (realised variance minus implied variance) times dt.
   3. So the position is a bet on variance, not on direction, and it settles continuously rather than at expiry. Put a number on it: a one percent daily move against a 20 percent annual implied vol, which implies about 1.26 percent daily, means you lose on that day because the move was smaller than what you paid for.
   4. Real-world frictions that eat the theory: you hedge discretely, so you capture only part of the gamma and the hedging error has variance proportional to the hedge interval. You pay the spread on every rehedge, so hedging too often costs more than the gamma it captures. There is an optimal hedge frequency that trades hedging error against transaction cost, and it scales with gamma and the spread.
   5. And the residual you cannot get rid of: vega. If implied vol falls while realised vol is fine, you lose on the mark even if your gamma P&L is positive. A long-dated option is mostly a vega position where the gamma story barely matters, which is why the expiry you choose determines which of these two effects dominates.

   Where candidates lose it

   Saying you profit if the stock goes up. You are delta hedged, so direction is neutralised by construction. The answer must be realised versus implied volatility, with gamma earned against theta paid. Then volunteer the discrete hedging cost, because in practice it is what determines whether a theoretically profitable long gamma position makes money.

   Expect next

   • How often would you rehedge, and what determines the optimal frequency?
   • What if implied vol collapses but realised vol is high?
   • How does this change for a one-week option versus a one-year option?
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.