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. 060You backtested a strategy and it performed brilliantly, but in live trading you keep losing money. What would you do?Time seriesHardsuperdayJump TradingQuantitative Research · Chicago · 2018

   Say this

   First I would cut the size, because the priority is to stop bleeding while I diagnose. Then I would work through the causes in order of likelihood: costs and slippage, look-ahead or survivorship bias in the backtest, overfitting from too many trials, and only last the possibility that the edge was real and has decayed.

   Then walk it

   1. Costs first, because it is the most common and the easiest to check. Compare realised fill prices against the prices the backtest assumed. If the backtest filled at mid and you are paying the spread plus impact, a strategy with a one basis point edge and a two basis point cost is a losing strategy that looked like a winner. Reconstruct the P&L attribution trade by trade against the simulated trades.
   2. Then look-ahead bias. Did any feature use data timestamped after the decision, including restated fundamentals, index membership known only later, or a corporate action applied on the announcement date rather than the effective date? Survivorship bias in the universe is the same family of error.
   3. Then overfitting. How many variants did I try before this one? If the answer is hundreds, the in-sample Sharpe is a maximum over many draws, and the deflated Sharpe is the honest number. Test on a market or a period I never touched.
   4. Then regime and decay. Plot the backtest P&L by year and see whether the edge was concentrated in one period. Check whether the alpha has been crowded out, which usually shows up as the signal still predicting but the entry price already moved.
   5. And the meta-answer, which is the one they want: I would write the diagnosis as a hypothesis with a test, not a list of possibilities. For example, if costs are the cause, the loss should scale with turnover, so I would compare the live P&L of the highest and lowest turnover sleeves. Then I would say what would make me shut it off permanently, and I would set that threshold before I looked at any more data.

   Where candidates lose it

   Jumping straight to the market regime changed. That is the excuse every losing strategy gets and it is almost never the first cause. The ordered list of costs, bias, overfitting, then decay is what a research head wants to hear, along with the instinct to reduce size before you finish diagnosing.

   Expect next

   • How exactly would you test whether costs are the cause?
   • How many strategy variants did you try, and how should that change your prior?
   • At what point do you shut it off for good?

   Reported by candidates at Jump Trading (Quantitative Research, Chicago, 2018). Source: Wall Street Oasis.

2. 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.

3. 064You are long five hundred lots and the market keeps offering below you. What do you do with your quotes?Market makingIntermediatetechnicalProp trading firmsQuant trading

   Say this

   Skew. Lower both my bid and my offer so I am more likely to sell than to buy, because I want to reduce inventory, and widen if the flow suggests the market is informed. Skewing quotes is how a market maker manages inventory without crossing the spread.

   Then walk it

   1. The mechanism: a market maker's reservation price moves against their inventory. Long inventory means I value the next unit less, so my fair value shifts down and my quotes should shift with it. That is the core result of the Avellaneda-Stoikov style inventory models.
   2. Skewing is cheaper than hedging aggressively. If I dump 500 lots at market I pay the spread plus impact immediately. If I skew, I get paid the spread to unwind, just more slowly.
   3. But I need to distinguish two situations. If the offers are noise traders, I keep skewing and unwind profitably. If the offers are informed flow ahead of news, skewing just means I keep buying into a falling market, which is how market makers blow up.
   4. The tell is whether the market comes back. If I sell some and the price recovers, I was providing liquidity. If every trade is followed by the market moving further against me, I am being run over and I should widen, reduce size, or cross the spread and get flat.
   5. So the decision rule I would say out loud: skew first, size down second, and cross the spread third if my position is still growing against me. And I would have a hard limit set in advance, because the one thing you cannot do is decide your maximum loss while you are losing.

   Where candidates lose it

   Answering hold and wait for it to come back, which is the losing trader's answer. Also answering just hedge without noting that hedging costs the spread. The interviewer wants to see the skew mechanism named, and wants to hear you distinguish noise flow from informed flow.

   Expect next

   • How do you tell whether the flow is informed?
   • At what point do you cross the spread and get flat?
   • How would you set your position limit in advance?
4. 069You quote a tight market and get lifted on your offer immediately. Are you happy?Market makingIntermediatetechnicalProp trading firmsQuant trading

   Say this

   No, not immediately. An instant fill is usually bad news: it means my offer was the cheapest thing available, which suggests my fair value was too low. I would shift my market up, not celebrate the spread I just earned.

   Then walk it

   1. The right frame is that a fill is information. If the market wanted my offer that fast, my offer was probably below consensus fair value.
   2. The fill I actually want is slow and two-sided: I buy on the bid, sell on the offer, and end the day roughly flat having collected the spread many times. Getting filled on one side only is a warning.
   3. So the immediate action is to move both quotes in the direction of the flow and reconsider the width. The mid moves up, and I may widen because I am now less sure where fair value is.
   4. How to measure whether it was actually bad: markout. Look at the mid a minute later. If the market is above where I sold, I was adversely selected regardless of the spread I booked. Booking the spread and losing on the markout is the classic way a market maker loses money while showing positive spread capture.
   5. The one case where I am genuinely happy is if I know the flow is uninformed, for instance a retail-sized order or a predictable end-of-day hedger. Then an instant fill is exactly the business. So the honest answer is: it depends who traded with me, and I would want to know that before I formed a view.

   Where candidates lose it

   Saying yes, I made the spread. That is the answer of somebody who thinks the spread is profit rather than gross revenue. Instant one-sided fills are the signature of adverse selection, and the interviewer is checking whether your instinct is to update or to congratulate yourself.

   Expect next

   • How would you check whether you were picked off?
   • What do you do with your quotes now?
   • When would an instant fill be good news?
5. 070Something goes badly wrong on your book during the session. How do you react?Market makingIntermediatetechnicalOld Mission CapitalProp Trading · Chicago · 2025

   Say this

   Reduce risk first, diagnose second, and tell someone immediately. In that order. The instinct to understand the problem before acting on it is the wrong instinct when the position is still live and the loss is still growing.

   Then walk it

   1. Step one, stop the bleeding. Pull quotes, flatten or hedge the exposure I did not intend to have, and cap any automated system that might still be adding to it. Getting smaller is almost never the wrong move under uncertainty.
   2. Step two, escalate. Tell the senior trader on the desk and the risk desk straight away, before I know the cause. Every trading floor's disaster stories are about someone who tried to fix it quietly first.
   3. Step three, establish the facts. What is my actual position, what is the realised and unrealised loss, is the pricing wrong or is the position wrong, and is anything still running that I have not stopped.
   4. Step four, only then diagnose and fix. A bad parameter, a stale feed, a hedge that did not go through, a fat finger, a genuine adverse move.
   5. And afterwards, write it up. A one-page post-mortem with a concrete control change is what stops the same failure twice. What a desk actually wants to hear from a junior candidate is that you act to reduce risk without needing permission, and escalate without needing to look competent first. Composure plus disclosure, in that order.

   Where candidates lose it

   Answering that you would investigate the cause first. On a live book that is exactly backwards, and a prop trading interviewer is listening for the reduce-then-escalate-then-diagnose sequence. Also do not claim you would stay completely calm. Say you would act on a checklist precisely because you would not be calm.

   Expect next

   • Who do you tell, and how quickly?
   • Tell me about a time you made a real mistake and what you did.
   • What would you put in the post-mortem?

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

6. 071Here is a scenario. Walk me through how you would analyse the trade.Market makingHardcase studySchonfeldQuantitative Research · New York · 2021

   Say this

   I would structure it as five questions: what is the thesis and what would make it wrong, what is the expected value, how do I size it, how do I hedge what I am not trying to be exposed to, and what is my exit. Then say the number, because a trade analysis without a number is an opinion.

   Then walk it

   1. Thesis first, stated as a falsifiable claim with a horizon. Not this looks cheap, but I think this spread compresses from 80 to 50 basis points over three months because of a specific mechanism, and if it is still at 80 in three months I am wrong.
   2. Expected value: probability times payoff on each branch. If there is a 60 percent chance of making 3 and a 40 percent chance of losing 2, that is 1.8 minus 0.8, so plus 1 with a 5-point range of outcomes. The range matters as much as the mean.
   3. Sizing: from the loss branch, not the win branch. I size so that the bad case is a loss I can carry, which in practice means a fraction of my risk budget, and I say what that fraction is.
   4. Hedging: separate the exposure I want from the ones that come attached. If the view is idiosyncratic, hedge out the market beta, the sector, and the rate duration, then check what basis risk remains after hedging, because that is the risk I did not choose.
   5. Exit and monitoring: the level or the date at which I am out, plus the two or three observables that would tell me the thesis is breaking before the P&L does. And I would name the thing I cannot hedge, because every trade has one and being explicit about it is what makes the analysis credible rather than promotional.

   Where candidates lose it

   Describing the thesis at length and never getting to sizing, hedging or the exit. Anyone can have a view. What a multi-manager platform is hiring for is the risk framework around it, so spend at least half your answer on size, hedge and exit, and name the unhedgeable residual yourself.

   Expect next

   • What is your stop, and why there?
   • What would make you double the position?
   • What risk are you left with after hedging?

   Reported by candidates at Schonfeld (Quantitative Research, New York, 2021). Source: Wall Street Oasis.

7. 073Why do alphas decay, and how would you detect that yours is dying?Time seriesHardsuperdayQuant researchQuant trading

   Say this

   Because a profitable pattern attracts capital until the price moves to where the profit was. Detect it by tracking realised versus expected performance, the signal's own predictive power separately from the P&L, and crowding measures, and set the decision rule before performance deteriorates.

   Then walk it

   1. Mechanisms in order of frequency. Crowding, where other people trade the same signal and the entry price moves. Structural change, where the market feature the signal exploited is regulated or engineered away. Arbitrage by faster participants. And plain overfitting, where the alpha was never there.
   2. Separate the two things that can break. Is the signal still predicting, measured by information coefficient, the correlation between forecast and subsequent return? Or is it predicting but no longer profitable after costs? The first is decay, the second is crowding or impact, and the fixes differ.
   3. Concrete measures: rolling information coefficient, rolling Sharpe, realised transaction cost versus modelled, and the fraction of your expected edge captured on a typical fill. If the signal is intact and the capture rate is falling, other people are in front of you.
   4. Crowding proxies: short interest and borrow costs for the short leg, correlation of your P&L with published factor returns, and how your strategy behaves on days when leveraged players deleverage. A crowded trade has fat negative tails on those days.
   5. The discipline is the answer though. Set the decay threshold in advance, for example halve the allocation if the rolling one-year information coefficient falls below half its backtest level for two consecutive quarters. Deciding in the middle of a drawdown is how people turn a decayed alpha into a large loss, and having the rule written down before you need it is the part an interviewer is actually testing.

   Where candidates lose it

   Answering only markets get more efficient. Be specific about mechanisms and about measurement, and above all separate whether the signal stopped predicting from whether the trade stopped being profitable. A pre-committed decision rule is the piece most candidates never mention.

   Expect next

   • What is an information coefficient and what is a good value?
   • How would you measure crowding in a trade?
   • Would you turn it off, or reduce it, and who decides?
8. 082Something in your C++ program is overwriting memory it should not. How do you find it?ProgrammingHardtechnicalTower Research CapitalForeign Exchange · London · 2019

   Say this

   Reach for the sanitisers first. AddressSanitizer catches out-of-bounds writes and use-after-free with roughly a two times slowdown and tells you both the write site and the allocation site. If the corruption is timing-dependent, add ThreadSanitizer for data races.

   Then walk it

   1. Order of tools: compile with -fsanitize=address,undefined and run the failing case. That resolves most buffer overruns and use-after-free immediately. Valgrind memcheck is slower but needs no recompile and catches uninitialised reads that ASan misses.
   2. If the corrupted location is known but the writer is not, set a hardware watchpoint in gdb on that address with watch, and let it break when something writes. Four watchpoints on x86, which is usually enough.
   3. If the corruption is not reproducible, make it reproducible before anything else. Record the inputs, pin the threads, disable randomisation, and consider record-and-replay with rr. A bug you cannot reproduce cannot be fixed, only guessed at.
   4. Common causes to check by inspection while the tools run: writing past the end of a fixed buffer, a dangling reference into a vector that reallocated, a stale pointer into an object that moved, a struct written with memcpy at the wrong size, and two threads writing the same cache line without synchronisation.
   5. And the systems answer for a production trading process where you cannot run ASan in the hot path: build with sanitisers in a test environment and in a canary, add canary values or guard pages around suspect buffers, and turn on the allocator's own debug checks. I would also say plainly that the fastest fix for a class of these bugs is to stop using raw buffers, because bounds-checked containers and spans eliminate the whole category.

   Where candidates lose it

   Answering add print statements. That is the answer of someone who has never used a sanitiser, and at a firm running C++ in production it is disqualifying. Name ASan specifically, name the gdb watchpoint technique for a known address, and say how you would make an intermittent bug reproducible before you try to find it.

   Expect next

   • What does AddressSanitizer not catch?
   • How would you debug this in production where you cannot run sanitisers?
   • What is a data race and why is it undefined behaviour?

   Reported by candidates at Tower Research Capital (Foreign Exchange, London, 2019). Source: Wall Street Oasis.

9. 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.

10. 087You think the market is overestimating volatility. What options strategy would you use?Options and derivativesIntermediatetechnicalOld Mission CapitalProp Trading · Chicago · 2025

    Say this

    Sell volatility and hedge the direction out. The cleanest expression is a short straddle or strangle, delta-hedged so the position is a bet on volatility rather than on the underlying. If implied vol is above what I think realised vol will be, I collect the difference through the gamma-hedging P&L.

    Then walk it

    1. The mechanism: a delta-hedged short option position makes money when realised volatility comes in below the implied vol you sold. Your P&L is approximately half of gamma times the difference between implied variance and realised variance, integrated over the life of the trade.
    2. The instrument choice. A short straddle at the money has the most vega and gamma per unit of premium, so it is the purest vol expression. A short strangle has less gamma but a wider profitable range and less immediate pin risk. If I wanted a cleaner exposure with no path dependence I would sell a variance swap, where the payoff is literally implied minus realised variance.
    3. Risk management is the whole trade. Short gamma means every hedge is at a worse price than the last, so a gap move is where the loss lives. I would cap it with a long wing, turning the strangle into an iron condor, which sacrifices some premium to remove the unbounded tail.
    4. Sizing from the tail: I would set the position so the worst plausible gap, say a five percent overnight move, is a loss I can carry, not from the expected daily P&L. Short vol positions have positive expected value most days and lose several months of it in one session.
    5. And the honest caveat: implied vol trading above realised vol is the normal state of the world, not a mispricing. The variance risk premium exists because sellers are being paid to warehouse gap risk. So I need to believe implied is rich relative to that premium, not merely rich relative to realised, otherwise I am just collecting a risk premium and calling it alpha.

    Where candidates lose it

    Answering short straddle and stopping. Two things must follow: that you delta hedge to isolate the vol view, and that short gamma means a fat left tail so you cap or size for it. Also the variance risk premium point, because saying implied is above realised therefore sell it is the reasoning that ends careers.

    Expect next

    • How do you make it a pure volatility trade?
    • What happens if the stock gaps ten percent overnight?
    • Why is implied usually above realised in the first place?

    Reported by candidates at Old Mission Capital (Prop Trading, Chicago, 2025). 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.