Hedge Funds interview preparation

Questions

100

Traced to a firm

39

Firms

16

Updated

September 2026

Asked at

All firmsMan Group10Balyasny Asset Management7Bridgewater Associates3DED.E. Shaw3Apollo Global Management2KKR2Oaktree Capital Management2Point722SCSquarepoint Capital2ACAQR Capital Management1BGBaupost Group1Coatue Management1HPS Investment Partners1Northern Trust1Viking Global Investors1Wolverine Trading1

Topic

All topicsStrategy taxonomy8Stock pitch10Short selling6Portfolio construction8Risk and drawdown8Performance and alpha7Event-driven and merger arb8Distressed and credit5Fund structure and economics7Financing, NAV and operations6Compliance and research process5Quant and systematic6India and Category III AIFs5Career and fit11

Level

AnyCoreIntermediateHard

Type

AnyTechnicalMarket viewBrainteaserCaseFit

1. 011Are you sure your thesis can be backed up? What if their costs do not fall?Stock pitchHardsuperdayApollo Global ManagementInvestments · Remote · 2021

   Say this

   Answer the substance, do not defend the position. Give the evidence behind the cost assumption, quantify what the stock is worth if you are wrong, and say where you would cut. Under pressure, the willingness to concede the weak leg is worth more than conviction.

   Then walk it

   1. Evidence first, and be specific. 'Management guided to it' is weak. 'The input contract repriced in Q2, gross margin already moved 180 basis points, and two quarters of run-rate are visible in the reported numbers' is strong.
   2. Then price the downside. 'If costs stay flat, EBITDA is 12 percent below my number, the multiple compresses to peers, and the stock is worth 48 rather than 85. From 62 that is about 22 percent down.'
   3. Then the asymmetry, which is the real defence. 35 up against 22 down still works at even probability, and I would size it accordingly rather than at a full weight.
   4. Then the monitoring plan. Which disclosure tells you early, and by when. If the cost curve is visible in a monthly input price or a quarterly gross margin line, the thesis is testable in real time and that is what makes it a hedge fund position.
   5. Then concede properly where you should. 'You are right that the cost assumption is the weakest leg, so I would start at half size and add on the first print that confirms it' is a better answer than digging in.
   6. And name the structural hedge. If the cost concern is industry-wide rather than company-specific, you can pair the long against a competitor with the same input exposure and isolate the part you actually have a view on.

   Where candidates lose it

   Defending emotionally, or answering a different question than the one asked. This is a test of whether you update on evidence. Candidates who repeat the bull case with more adjectives fail; candidates who quantify the bear case and name a stop pass even if the interviewer keeps pushing.

   Expect next

   • At what price would you stop out?
   • How would you size it given that uncertainty?
   • What would you have to believe for the bear case to be right?

   Reported by candidates at Apollo Global Management (Investments, Remote, 2021). Source: Wall Street Oasis.

2. 012Take me through a structured investment idea the way you would present it to a portfolio manager.Stock pitchHardcase studyPoint72Investment Banking · London · 2026

   Say this

   A PM has five minutes and wants four things: what the trade is, what you know that they do not, what it is worth if you are right and wrong, and what kills it. Structure it in that order and answer the question asked before you show your work.

   Then walk it

   1. Page one is the trade and the sizing. Long, short or paired, entry, target, downside, horizon, and the risk you want to take in the book. Everything else supports this page.
   2. Page two is the variant view with consensus next to your number. A PM reads this page and nothing else if they are busy.
   3. Page three is the mechanism: the two or three drivers that get you from today's numbers to yours, each with the evidence behind it. Volume, price, mix, cost, capital allocation. No page of company history.
   4. Page four is the risk map: the bear case with a price, the two things that break it, the dated falsifiers, and the hedge if the idea has an unwanted factor or sector exposure.
   5. Then the questions you could not answer. Naming them yourself is a credibility move at a platform, because the PM will find them anyway and would rather find them in your appendix than in the P&L.
   6. Business judgement is what is actually being graded in a case like this. That means industry structure, who has pricing power, where the profit pool sits, and whether the company's advantage is durable. A model with no industry view is a spreadsheet, not an idea.

   Where candidates lose it

   Building up to the recommendation. Analysts trained on client decks lead with company overview and market sizing and lose the room. Put the trade in the first sentence, and make sure something in the case shows judgement rather than arithmetic, because that is the explicit test.

   Expect next

   • What is the single best argument against this idea?
   • How would you express it if you could not short the obvious hedge?
   • What would you need to see to double the size?

   Reported by candidates at Point72 (Investment Banking, London, 2026). Source: Wall Street Oasis.

3. 017How did you get the assumptions and calculations in your case study?Stock pitchHardcase studyDED.E. ShawGeneralist · New York · 2025

   Say this

   Go line by line and separate the three kinds of input: facts from disclosure, estimates built bottom-up from a driver, and judgement calls. Say which is which for every important number, and cite the source for the facts.

   Then walk it

   1. Facts first: pull them from primary disclosure and say where. 'Installed base of 1.4 million units is from the 2025 annual report, segment note 4.' Never from a secondary summary if the filing exists.
   2. Then the built estimates. Show the decomposition rather than the result. Revenue is units times price, units are installed base times replacement rate, and the replacement rate comes from the reported life of the asset. Now the number is auditable.
   3. Then the judgement calls, flagged as such. 'I assumed a 60 percent attach rate on the new product. There is no disclosure, so I triangulated from the competitor who does report it and haircut it for their head start.'
   4. Then sensitivity. Say which assumption the answer is actually sensitive to. Most models have one or two inputs that move the value and ten that do not, and knowing which is which is the sign of someone who has built models rather than filled them in.
   5. Then the cross-check. Does the implied market share exceed the whole addressable market in year five? Does the implied margin exceed the best operator in the industry? A bottom-up model with no top-down reality check is where the embarrassing errors live.
   6. Honest close: name the number you are least confident in, and what you would go find if you had another week. Interviewers at quantitative shops are probing whether you know the difference between a number you derived and a number you liked.

   Where candidates lose it

   Saying 'industry reports' or 'I assumed it grows in line with GDP' for a number that drives the whole answer. That reads as reverse-engineering the model to a conclusion. Label facts, estimates and judgement separately, and volunteer the one assumption the valuation is most sensitive to before you are asked.

   Expect next

   • Which assumption is the answer most sensitive to?
   • What is the implied market share in year five?
   • What would you check if you had another week?

   Reported by candidates at D.E. Shaw (Generalist, New York, 2025). Source: Wall Street Oasis.

4. 025How do you size a position?Portfolio constructionHardsuperdayMulti-manager platformsLong-short equity

   Say this

   From the downside and the correlation, not from the upside. The question is how much the book loses if I am wrong, how likely that is, and how much of that same risk I already own elsewhere. Upside sets whether the trade is worth doing; downside sets how big it can be.

   Then walk it

   1. Start with the loss budget. If my bear case is minus 40 percent and I am unwilling to lose more than 1.5 percent of the fund on a single idea, the position caps out around 4 percent regardless of how much I like it.
   2. Then risk rather than notional. A 4 percent position in a 60 percent volatility name is a bigger risk position than 8 percent in a 20 percent volatility name. Sizing in contribution-to-risk terms is what a platform risk system will force you to do anyway.
   3. Then correlation, at the book level. Three longs expressing the same rate view are one position with three tickers. If I cannot name the common factor, I have not finished the work.
   4. Then liquidity. Days of average daily volume to exit is a hard constraint. If a position takes ten days to unwind in a normal tape, it takes thirty in a bad one, and the size should reflect the exit, not the entry.
   5. Then conviction, which is really the falsifiability of the thesis and the closeness of the test. A thesis with a print in six weeks supports more size than a five-year structural view, because I will learn sooner and can cut cheaply.
   6. Kelly is the theoretical anchor and I would say why nobody runs it full: you cannot estimate the probabilities finely enough, and the penalty for overestimating your edge is geometric. Most people run a quarter to a half of Kelly. In a pod seat much of this is imposed by the risk system, and the analyst's job is to argue for size inside those limits.

   Where candidates lose it

   Sizing by upside. Every analyst's favourite idea has the most upside, and sizing on that is precisely how books blow up. Also, giving notional percentages with no mention of volatility, correlation or liquidity. A hedge fund answer talks in risk contribution, not in weights.

   Expect next

   • What is your maximum single position, long and short?
   • How would you handle two positions with 0.8 correlation?
   • Would you add to a loser?
5. 029How would you hedge a name that does not have a similar public comp?Portfolio constructionHardtechnicalBalyasny Asset ManagementEquity Research · New York · 2026

   Say this

   Decompose the position into the risks you do not want and hedge each one with whatever trades, rather than hunting for a twin. Usually that means a basket: some index or sector for market beta, a factor or style proxy, and then something specific for the commodity, currency or customer exposure.

   Then walk it

   1. First, write down what you are actually exposed to. Market beta, sector, style factors like growth and momentum, one or two macro sensitivities, maybe a single large customer or an input cost. The comp problem disappears once you stop thinking in comps.
   2. Then hedge the biggest exposures with liquid instruments. Index futures for beta, a sector ETF for industry, and a factor ETF or a long-short style basket if the name is a strong growth or momentum expression.
   3. Then go up or down the value chain. If there is no comp, there is usually a supplier, a customer or an input. A specialty chemical company with no peer can often be partly hedged with the feedstock or with the auto OEMs it sells into.
   4. Then a statistical basket as the fallback. Regress the stock on a set of liquid candidates over a sensible window and build a weighted short basket from the loadings. It is crude but it is honest, and platforms do exactly this.
   5. If nothing works, the right answer is to size it smaller. An unhedgeable idiosyncratic risk is a legitimate risk to take, just not at full weight, and saying that is better than inventing a hedge.
   6. Then name the two failure modes: a regression-fitted basket can be a spurious relationship that breaks in the stress you were hedging against, and it needs rebalancing or the loadings drift. I would re-estimate monthly and cap how much of the risk I claim is hedged.

   Where candidates lose it

   Answering 'short the index' and stopping, or inventing a comp that is not really one. At a multi-manager platform this question is about whether you think in risk factors rather than in tickers. And do not miss the escape hatch: sometimes the correct answer is that the risk cannot be hedged and the position should be halved.

   Expect next

   • How would you build that regression basket and over what window?
   • What could go wrong with a statistically fitted hedge?
   • When is the right answer to just size it smaller?

   Reported by candidates at Balyasny Asset Management (Equity Research, New York, 2026). Source: Wall Street Oasis.

6. 030What does factor neutral mean, and why do platforms insist on it?Portfolio constructionHardsuperdayMulti-manager platformsQuantitative hedge funds

   Say this

   Factor neutral means the book has close to zero net exposure to the common systematic drivers of return: market, size, value, growth, momentum, quality, volatility, and the industry groups. Platforms insist on it because they are paying for idiosyncratic stock picking and can buy factor exposure themselves for a few basis points.

   Then walk it

   1. Mechanically, a risk model like Barra or Axioma decomposes every stock into factor loadings plus a residual. Neutrality means the weighted factor loadings across the book net to roughly zero, within stated limits.
   2. The business logic is straightforward: if a PM's returns come from a persistent growth tilt, the fund is paying a performance fee for something an ETF delivers. Stripping the factors leaves what the PM is actually paid for.
   3. It also makes pods additive. If every pod is factor neutral, their P&Ls are close to independent, and the centre can lever the combination. Factor tilts are the main thing that makes supposedly uncorrelated pods lose money on the same day.
   4. In practice it is enforced as limits, not perfection. Something like plus or minus 0.1 on any style factor and a cap on industry net exposure, monitored daily, with the risk team reducing you if you breach.
   5. The cost is real and worth naming. Neutralising factors removes return you might have wanted, forces trades that have nothing to do with your thesis, and creates rebalancing cost. A PM who genuinely has skill at calling the cycle is being asked to stop doing it.
   6. The deeper limitation: neutrality is only as good as the risk model. A crowding factor is not in most commercial models, so a book can be textbook factor neutral and still be one position, which is roughly what happened to quant equity in 2007 and to crowded pod longs in early 2021.

   Where candidates lose it

   Defining factor neutral and not explaining the commercial reason. The interviewer wants to hear that the fund can buy factor beta cheaply, so what they are paying you for is the residual. And if you claim factor neutrality is sufficient risk control, say the crowding caveat yourself, because that is the live criticism of the model.

   Expect next

   • Which factors would you neutralise and which would you keep?
   • How would you detect crowding if the risk model does not have it?
   • What is the cost of factor neutralisation to a PM?
7. 033You are down 4 percent on the month and your risk manager is on the phone. What happens next?Risk and drawdownHardsuperdayMulti-manager platforms

   Say this

   First I would know the answer to their question before they ask it: what lost the money, whether it was the thesis or a factor, and what I am doing about it. Then I would cut risk to the level they need, without arguing, and keep the positions I still believe in at a smaller size.

   Then walk it

   1. Attribution first, and fast. Split the loss into market, sector, style factor and idiosyncratic. A 4 percent loss that is mostly a momentum unwind is a very different conversation from a 4 percent loss on two broken theses.
   2. If it is factor, the fix is mechanical: neutralise the offending exposure and the drawdown stops compounding. That is a risk process failure, and I would own it as such.
   3. If it is idiosyncratic and the theses are intact, I still have to reduce, because a drawdown limit is not an opinion. The question is which positions to keep. I would cut the ones where the falsifier has been triggered or where liquidity is worst, and keep the highest conviction, most liquid, nearest-catalyst names at reduced size.
   4. Say the number out loud, because it is how these seats work. Most platforms run a soft limit around 3 to 5 percent where gross is cut hard, and a hard stop near 7 to 10 percent where the book is closed. Knowing that is what shows you understand the seat.
   5. Then the behavioural discipline: do not double down to get it back, do not switch style, and do not stop communicating. PMs who go quiet in a drawdown get taken down faster than PMs who over-communicate.
   6. And the honest part: I would reserve the right to say that a position is being cut for risk reasons, not because I think it is wrong. That distinction is worth recording, because it is how you learn whether your process or your judgement failed.

   Where candidates lose it

   Saying you would defend the book and ask for more room. On a multi-manager platform the drawdown limit is the contract, not a negotiation, and that answer gets you marked as someone who will not survive the risk framework. Lead with attribution, accept the reduction, and show judgement in what you keep.

   Expect next

   • Which positions would you cut first, and why?
   • At what level does the platform close your book?
   • How would you tell the difference between bad luck and a broken process?
8. 035Write a function that returns the n largest drawdowns in a return series.Risk and drawdownHardtechnicalBalyasny Asset ManagementQuantitative Trading · London · 2025

   Say this

   Build the cumulative NAV, walk it once tracking the running peak, and record a drawdown episode whenever the series falls below a peak and then makes a new high. Each episode gets a depth, a start, a trough and a recovery date. Then sort the episodes by depth and return the top n. It is a single linear pass.

   Then walk it

   1. Step one: turn returns into a wealth index, cumulative product of one plus r. Do this before anything else, because drawdowns are multiplicative and summing returns gives the wrong depth.
   2. Step two: running maximum of the wealth index. The drawdown series is wealth divided by running max, minus one, which is zero or negative at every point.
   3. Step three, the part interviewers actually test: segment into episodes. An episode opens when the drawdown series goes below zero and closes when it returns to zero, meaning a new high water mark. Within each episode the trough is the minimum.
   4. Step four: sort episodes by depth, take the first n. Say the complexity: O(T) for the pass plus O(k log k) for the sort, where k is the number of episodes, so linear in practice.
   5. State the edge cases before being asked, because this is where candidates get cut: the series ends while still in a drawdown, so the last episode is unrecovered and you should report it with no recovery date. Also decide whether overlapping nested dips count as one episode or several, and say which convention you are using.
   6. The naive alternative is to take the n most negative points of the drawdown series, and it is wrong: they will all sit inside the same crash. Volunteering why that fails is what shows you understood the question rather than pattern-matched it.

   Where candidates lose it

   Returning the n most negative values of the drawdown series. They cluster in one episode, so you report the same crash n times. The question is really about episode segmentation. Also, sum returns instead of compounding them and every number is wrong. State your episode convention out loud.

   Expect next

   • How would you handle a series that ends mid-drawdown?
   • How would you report time to recovery?
   • How would you do this for a portfolio of a thousand instruments efficiently?

   Reported by candidates at Balyasny Asset Management (Quantitative Trading, London, 2025). Source: Wall Street Oasis.

9. 040Your best long and your best short are in the same sector and both going against you. What do you do?Risk and drawdownHardsuperdayLong-short equityMulti-manager platforms

   Say this

   If both legs are losing at once, the pair is not hedged on the dimension that is moving, so first I would find out what that dimension is. It is usually a style factor rather than the sector, and the answer depends entirely on whether I have a factor problem or two independent thesis problems.

   Then walk it

   1. Diagnose before acting. Run the attribution: if the long is a value name and the short is a growth name, a growth rally hurts both and the sector hedge was never doing the work I thought it was.
   2. If it is a factor, the fix is to neutralise the factor, not to abandon the theses. Overlay a style hedge or adjust the pair weights so the loadings offset, and keep the idiosyncratic view.
   3. If both theses are genuinely deteriorating on their own facts, that is a different message: my process has a common flaw, probably a shared assumption about the end market. Then I cut both and go back to the work rather than pick one to defend.
   4. Check the correlation assumption I entered with. If I sized the pair as a hedged position and it is behaving as two directional positions, my risk is roughly double what I thought and the size has to come down immediately, regardless of the diagnosis.
   5. Then the liquidity ordering. Reduce where reducing is cheap, which often means cutting the more liquid leg first, and accept that this temporarily unbalances the pair.
   6. And I would say the part people skip: an adverse move in both legs of a pair is one of the most useful signals a book gives you, because it means your model of what the trade was exposed to was wrong. That is worth more than the P&L.

   Where candidates lose it

   Picking one leg to cut on instinct, usually the loser you like less. Without attribution you do not know whether you have one problem or two. Say what you would measure first. And if the pair was sized as a hedge but behaves directionally, the size is wrong now, so address that before discussing the theses.

   Expect next

   • How would you separate factor loss from idiosyncratic loss?
   • If it is a factor, do you hedge it or reduce?
   • What would you have done differently when you put the pair on?
10. 044A fund shows a 2.5 Sharpe over three years. What questions do you ask?Performance and alphaHardsuperdayFund of fundsMulti-manager platforms

    Say this

    I would assume it is either a short sample, a hidden tail risk, or stale marks until proven otherwise. Three years of monthly data is 36 points, which is far too few to distinguish a 2.5 Sharpe from luck, so the questions are all about where the risk went rather than where the return came from.

    Then walk it

    1. Start with the statistics. The standard error on a Sharpe estimate is roughly the square root of one over the number of years, so three years gives an error bar wide enough that a true Sharpe of 1 produces a measured 2.5 reasonably often.
    2. Then look at the shape. Negative skew and high kurtosis are the signature of selling insurance. What are the worst three months, and were they in the sample? If the sample has no stress event in it, the number describes a regime, not a strategy.
    3. Then autocorrelation of monthly returns. If it is materially positive, marks are stale or the book is illiquid and the volatility is understated, which mechanically inflates the ratio.
    4. Then attribution. How much of the return is a factor exposure that happened to pay, how much is carry, and how much is idiosyncratic? A fund that was long momentum and credit spreads in a good period for both has beta, not skill.
    5. Then capacity and concentration. What was the AUM during the period, what is it now, and did the return come from a handful of positions? A 2.5 Sharpe on 200 million does not survive a move to 2 billion.
    6. And the operational questions, which allocators lose money on far more often than they do on strategy: who marks the book, who is the administrator and auditor, how independent is the valuation of the illiquid sleeve, and what are the terms if I want out.

    Where candidates lose it

    Being impressed. The whole question is whether you are sceptical in a structured way. Also, do not just say 'I would ask about risk'. Name the specific diagnostics: sample-size error bars, skew, return autocorrelation, factor attribution and who marks the book. That list is the answer.

    Expect next

    • How many years would you need to be confident?
    • What does positive autocorrelation in monthly returns imply?
    • What operational questions would you ask?

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.