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. 041What is the difference between alpha and beta, and how do you actually separate them?Performance and alphaIntermediatetechnicalMulti-manager platformsAsset management

   Say this

   Beta is the return you get for taking market risk, which anyone can buy for a few basis points. Alpha is what is left after you strip out every systematic exposure you were paid to take. You separate them by regressing the return stream on the factors and looking at the intercept.

   Then walk it

   1. The single-factor version: regress fund returns on market returns. The slope is beta, the intercept is alpha, the residual is unexplained. A fund with 0.6 beta in a market up 20 percent earned 12 points from beta before any skill.
   2. The problem is that a single factor flatters almost everyone. Add size, value, momentum, quality and low volatility and a lot of claimed alpha becomes a known factor tilt. That is the entire point of the Fama-French and Carhart extensions.
   3. For hedge funds you go further and add the exposures specific to the strategy: credit spreads, volatility, term premium, and for merger arb a factor that is essentially short the market's tail. Fung and Hsieh style models exist precisely because hedge fund returns are non-linear.
   4. The practical version inside a fund is attribution rather than regression. Decompose today's P&L into market, sector, style and residual, and only the residual counts as stock picking.
   5. The subtlety worth saying: alpha is model dependent. It is defined as what your factor model cannot explain, so a better model shrinks it. Alpha today is often just a factor nobody has named yet, which is roughly the history of quantitative finance.
   6. And beware short samples. With three years of monthly data the standard error on alpha is large enough that a 3 percent annual alpha is statistically indistinguishable from luck. Saying that is what separates a candidate who has run the regression from one who has read about it.

   Where candidates lose it

   Defining alpha as 'outperformance versus the index'. That is beta plus a benchmark choice. Alpha is residual to a factor model, which means it depends on which factors you include, and any honest answer says so. Also mention the sample-size problem: it is the fastest way to sound like you have handled real return data.

   Expect next

   • How many years of data do you need to prove an alpha is real?
   • Is a small-cap tilt alpha or beta?
   • How would you decompose a long-short fund's returns?
2. 042What is the Sharpe ratio, and what are its limitations?Performance and alphaCorephone / first roundAsset managementMulti-manager platforms

   Say this

   Excess return over the risk-free rate, divided by the volatility of that excess return. It is return per unit of risk, and the limitation is that it defines risk as volatility, which is the wrong definition for anything with a skewed or illiquid payoff.

   Then walk it

   1. Rough benchmarks to have in your head: a long-only equity index sits around 0.4 to 0.5 over the long run, a decent hedge fund 0.8 to 1.2, a platform at the fund level 2 or more because of diversification across pods, and anything claiming 4 over a long period needs explaining.
   2. Annualisation matters and gets fumbled. Multiply the monthly mean by 12 and the monthly standard deviation by the square root of 12. That scaling assumes independent returns, which is exactly what fails for illiquid books.
   3. Limitation one, symmetry. Volatility punishes upside surprise as much as downside. A fund whose good months are huge looks worse than a fund grinding out the same return, which is backwards for an investor.
   4. Limitation two, and this is the big one: a strategy that sells tail risk has a beautiful Sharpe until the tail arrives. Writing out-of-the-money options or running a levered convergence trade manufactures a high Sharpe by hiding the risk in the third and fourth moments.
   5. Limitation three, smoothing. Illiquid positions marked on stale prices have artificially low measured volatility, which inflates the ratio. The tell is high autocorrelation in monthly returns, and I would check that before believing any private-credit or distressed Sharpe.
   6. So I would look at Sharpe alongside skew, kurtosis, worst drawdown, time to recover and return autocorrelation. Sortino and Calmar cover part of the gap, and neither fixes the fundamental point that one number cannot describe a return distribution.

   Where candidates lose it

   Forgetting the risk-free rate in the numerator, or annualising by multiplying volatility by 12. Then, on limitations, giving only the symmetry point. The tail-selling and the stale-marks problems are what an allocator actually worries about, and naming autocorrelation as the diagnostic is the detail that lands.

   Expect next

   • How would you detect a fund that is selling tail risk?
   • What does high autocorrelation in monthly returns tell you?
   • What is the difference between Sharpe and Sortino?
3. 043What is the difference between the Sharpe ratio and the information ratio?Performance and alphaIntermediatetechnicalAsset managementQuantitative hedge funds

   Say this

   Sharpe measures excess return over cash divided by total volatility. Information ratio measures excess return over a benchmark divided by tracking error. Sharpe asks whether the whole portfolio was worth owning; information ratio asks whether the active decisions added value.

   Then walk it

   1. The numerator differs in what you subtract. Sharpe subtracts the risk-free rate. IR subtracts the benchmark, so all the market return is stripped out and only the active bet remains.
   2. The denominator differs too. Sharpe uses the volatility of total excess return; IR uses tracking error, the volatility of the difference from the benchmark.
   3. For a genuinely market-neutral hedge fund the two converge, because cash is effectively the benchmark. For a long-only manager they are very different: a fund can have a strong Sharpe from owning equities and a terrible IR from poor stock selection.
   4. The fundamental law of active management lives here: IR is roughly the information coefficient times the square root of breadth. It tells you a manager can raise IR either by being more skilful per decision or by making more independent decisions, which is the entire argument for systematic investing.
   5. Practical benchmark: a long-only manager with an IR of 0.5 sustained over ten years is genuinely good. Most active managers do not clear it after fees, which is why the fee compression happened.
   6. The shared weakness: both use volatility as risk and both need long samples to say anything. And IR is hostage to the benchmark choice, so a manager can improve their IR by picking a benchmark they are structurally tilted away from. Always ask what the benchmark is before reading the number.

   Where candidates lose it

   Saying they are basically the same thing, or getting tracking error and volatility confused. The distinction is what you subtract and what you divide by, and the good answer adds the benchmark-gaming point. For a market-neutral fund saying they converge shows you understand the definitions rather than memorising two formulas.

   Expect next

   • For a market-neutral fund, which would you quote and why?
   • What is a good information ratio over ten years?
   • How can a manager game their information ratio?
4. 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?
5. 045How do you attribute a fund's P&L?Performance and alphaIntermediatetechnicalMulti-manager platformsRisk management

   Say this

   Split it into the pieces that correspond to decisions someone made. Market, sector, style factor, then idiosyncratic stock selection, then financing and trading costs. The residual after the systematic pieces is the only part that is evidence of skill.

   Then walk it

   1. Start with market: beta-adjusted net exposure times the index return. That is the part you would have earned with no stock selection at all.
   2. Then sector or industry: the net weight in each industry times that industry's return relative to the index. This catches the PM who is really making a sector call and calling it stock picking.
   3. Then style factors from the risk model: growth, value, momentum, size, quality, volatility. Each has a net loading and a factor return, so each has a P&L line.
   4. Then the residual, which is stock selection. Split it long and short, because a book that makes all its money on the long side in a rising market has not demonstrated a short-selling capability and that matters for how much gross it should run.
   5. Then the costs that are frequently ignored: borrow fees, dividends paid on shorts, financing spread on the leverage, and realised trading cost. On a 300 percent gross book these can be well over a hundred basis points a year.
   6. The caveat to state: attribution is model dependent and the pieces do not add up cleanly. There is always an interaction and residual term, factor returns are estimated, and a PM can dispute the classification of a name. So I would use it to ask questions rather than to settle them.

   Where candidates lose it

   Attributing to positions rather than to risks. Listing the top five winners and losers is a P&L report, not an attribution. The point is to isolate whether the money came from decisions the PM is paid for. Remember to include financing and borrow costs; candidates almost always leave them out and they are large on a levered book.

   Expect next

   • What if all the alpha is on the long side?
   • How would you attribute a macro book instead?
   • What are the biggest cost lines on a levered long-short book?
6. 046What is a good hit rate, and why is that not the right question?Performance and alphaIntermediatetechnicalLong-short equityGlobal macro

   Say this

   Around 55 percent is genuinely good for a fundamental book, and many excellent macro managers run below 50. It is the wrong question on its own because P&L is hit rate times average win against miss rate times average loss. Expectancy, not accuracy, is what pays.

   Then walk it

   1. Write the identity out: expectancy equals p times average win minus one minus p times average loss. You can be right 40 percent of the time with a three to one win-loss ratio and run a very good book.
   2. That is exactly the trend-following and macro profile. Lots of small losses cut quickly, a few large winners held. The discipline is entirely in the size of the losses, not in the frequency of the wins.
   3. Fundamental long-short is the other shape: higher hit rate, smaller average win, because positions are researched and sized before entry rather than added to as they work.
   4. So the diagnostic questions are better than the hit rate. What is my average winner versus average loser, do I cut losers faster than winners, and am I adding to winners? A high hit rate with a losing book means you take profits early and let losses run, which is the most common retail-shaped mistake in a professional seat.
   5. Sample size again. Twenty positions tells you nothing about hit rate. You need hundreds of independent decisions before the number means anything, which is another reason systematic books can measure themselves and discretionary books mostly cannot.
   6. The honest limitation: hit rate is easy to game by how you define a decision. Was a position you added to three times one call or four? Without a consistent definition, the number is a story rather than a statistic.

   Where candidates lose it

   Quoting a high hit rate as though it were the goal. Interviewers use this to see whether you think in expectancy. Also watch the trap in the other direction: saying hit rate does not matter at all. It matters, it just has to be read with the win-loss ratio alongside it.

   Expect next

   • What is your win-loss ratio on your own investing?
   • Why do macro managers tolerate a sub-50 percent hit rate?
   • How would you know if you were cutting winners too early?
7. 047How would you evaluate a track record you were thinking of allocating to?Performance and alphaHardsuperdayFund of fundsMulti-manager platforms

   Say this

   Work out what generated the return, whether it is repeatable at the size they want to run, and whether the business around it can survive a bad year. Return level is the least interesting thing on the page; the interesting things are attribution, capacity and operations.

   Then walk it

   1. First, decompose. Factor regression on the monthly series plus position-level attribution if they will share it. A track record that is 70 percent explained by long momentum and short volatility is an expensive way to buy two factors.
   2. Second, ask what the sample contains. Which regimes did it live through? A book started in 2019 has seen a crash and a violent recovery; a book started in 2023 has seen one direction. No stress event in the sample means the tail is unmeasured.
   3. Third, concentration of the result. If the top three positions made the whole number over five years, the process claim is much weaker than the return suggests.
   4. Fourth, capacity. What was AUM through the period, how liquid were the positions relative to size, and what does the expected return look like at three times the assets? Almost every disappointing allocation is an asset growth story.
   5. Fifth, the people and the business. Is the performance attributable to one person, what is the team turnover, what is the fee and expense load, and how much of the manager's own money is in the fund?
   6. Sixth, operations, which is where allocators actually lose capital. Independent administrator, audited by someone real, who marks illiquid positions, what are the gates and lock-ups, and what is the history of using them. Then the terms question: if I want out in a bad market, can I get out?

   Where candidates lose it

   Focusing on returns and Sharpe. Those are the inputs to the question, not the answer. The differentiated parts are capacity at future AUM and the operational due diligence, and a candidate who mentions the administrator, the auditor and who marks the book sounds like they have sat in an allocator's seat.

   Expect next

   • What single question would you ask the manager?
   • How would you test capacity?
   • What would make you decline a fund with excellent numbers?
8. 048What is event-driven investing?Event-driven and merger arbCorephone / first roundEvent-drivenMulti-manager platforms

   Say this

   Investing where the return depends on a specific corporate event happening rather than on the business getting better. Mergers, spin-offs, restructurings, index changes, rights issues, activist campaigns. Because the payoff is tied to an event with a date, the main risk is completion and timing rather than valuation.

   Then walk it

   1. The sub-strategies: merger arbitrage, which is the biggest; spin-offs and stub trades; distressed and bankruptcy; capital structure arbitrage; index and technical events; activist and special situations.
   2. What unites them is a defined catalyst with a legal or contractual structure. You are underwriting a process, so the work is documents, regulators and counterparties rather than modelling ten years of cash flow.
   3. The payoff shape is characteristic: a high probability of a small gain and a small probability of a large loss. That is short optionality, and it means the return series looks smooth until it does not.
   4. Which has an important consequence for measurement. Event-driven strategies show attractive Sharpe ratios in benign markets because they are structurally short a tail. Any evaluation has to price that explicitly.
   5. Skill sits in unusual places: reading merger agreements, judging antitrust outcomes, understanding creditor classes and voting mechanics, and knowing the arbitrage community's positioning.
   6. The environmental dependency is worth naming. Deal flow is the raw material, so event-driven returns depend on corporate activity and on the regulatory climate. A hostile antitrust regime widens spreads, which raises returns and raises break risk at the same time.

   Where candidates lose it

   Describing it as 'investing in companies with catalysts', which is just fundamental investing with better timing. The defining feature is that the payoff comes from a structured event with legal mechanics, and the defining risk is that the event does not complete. Say the short-optionality point and you sound like someone who has looked at the return distribution.

   Expect next

   • Which event-driven strategy has the most capacity?
   • Why do these strategies show high Sharpe ratios?
   • What happens to event-driven returns when antitrust enforcement tightens?
9. 049Explain merger arbitrage and how the spread works.Event-driven and merger arbCoretechnicalEvent-drivenMerger arbitrage

   Say this

   You buy the target after a deal is announced at a discount to the offer and collect the gap when it closes. The spread exists because the deal might not close and because your capital is tied up until it does. So the spread is the market's price for break risk plus a time value of money.

   Then walk it

   1. The set-up for a cash deal: offer is 50, stock trades at 47.50, so the gross spread is 2.50 or about 5.3 percent. If it closes in four months, that is roughly 16 percent annualised before financing.
   2. The spread decomposes into three things: probability of break times the downside if it breaks, the time to close, and the financing cost of holding the position. You can invert it to extract the market-implied probability.
   3. That inversion is the standard piece of analysis and it is worth doing out loud. If the undisturbed price was 38, downside on a break is 9.50 and upside is 2.50, so the implied break probability is roughly 2.50 divided by 12, about 21 percent. Now you can compare the market's view with your own.
   4. The spread narrows as the deal clears hurdles: shareholder vote, financing, each regulatory approval. The P&L is earned in steps at those milestones, not smoothly.
   5. A stock-for-stock deal is different mechanically. You go long the target and short the acquirer at the exchange ratio, so you are trading the ratio rather than an absolute price, and you must handle the borrow on the acquirer and any dividends.
   6. The honest description of the payoff: you are writing insurance on deal completion. Low volatility, positive carry, and occasionally you lose several years of spread in one morning when a deal breaks. Which is why sizing, not spread hunting, is the skill.

   Where candidates lose it

   Calling it risk-free arbitrage. It is a short volatility, short tail trade. The two things that make an answer credible are computing the market-implied break probability from the spread and the undisturbed price, and naming the asymmetry of the payoff. Also get the annualisation right; a 5 percent spread over four months is not a 5 percent return.

   Expect next

   • What is the implied probability of completion in that example?
   • How does a stock-for-stock deal change the trade?
   • What is the undisturbed price and why does it matter?
10. 050A target trades at 46, the cash offer is 50, and the deal is expected to close in six months. What is your return, and what are you being paid for?Event-driven and merger arbIntermediatetechnicalMerger arbitrageEvent-driven

    Say this

    The gross spread is 4 on 46, which is about 8.7 percent over six months, or roughly 17 to 18 percent annualised before costs. You are being paid for the risk the deal breaks, and given where rates are, roughly half of that annualised number is just compensation for tying up capital.

    Then walk it

    1. Arithmetic first: 50 minus 46 is 4, over 46 is 8.7 percent. Doubling for the six-month period gives about 17.4 percent annualised, or 18.1 percent if you compound it. Say the simple number, then note the compounding refinement.
    2. Net it down. Subtract the financing cost of the long, add back any target dividend you receive, and subtract the cost of any hedge. At a 5 percent financing rate, roughly half the annualised spread disappears.
    3. Then the risk question, which is the real question. What is the undisturbed price? If the target traded at 34 before announcement, a break costs you 12 while success pays 4. Three to one against, so you need a completion probability well above 75 percent to break even.
    4. Compute the implied probability: 4 divided by 16 is 25 percent implied break risk. Then ask whether that is right. A friendly, all-cash, fully financed strategic deal with no antitrust overlap should be well below that, which would make the spread attractive.
    5. A spread this wide is a message. Eight percent over six months usually means antitrust review, a financing condition, a shareholder who has objected, or a regulatory regime with a track record of blocking. Find out which before you take the other side.
    6. And the sizing conclusion: because the payoff is three to one against you, position size and deal diversification do more for the return than spread selection. Twenty deals at 2 percent each beats four at 10 percent, and that is the whole discipline of the strategy.

    Where candidates lose it

    Quoting 8.7 percent as the return and stopping. You must annualise, and you must net the financing. Then the bigger trap: giving a return with no reference to the downside. Without the undisturbed price the spread is meaningless, and an arb interviewer will judge you almost entirely on whether you asked for it.

    Expect next

    • What was the price before the deal was announced?
    • What implied break probability does that spread give you?
    • How many deals would you hold, and why?

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.