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

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1. 026What is the Kelly criterion, and why does nobody run full Kelly?Portfolio constructionIntermediatesuperdayQuantitative hedge fundsMulti-manager platforms

   Say this

   Kelly gives the bet size that maximises the long-run growth rate of capital: you bet your edge divided by the odds. For a simple even-money bet it reduces to twice your win probability minus one. Nobody runs it full because it assumes you know your edge precisely, and overestimating it is punished geometrically.

   Then walk it

   1. The formula for an even-money bet: f equals 2p minus 1. With a 55 percent chance of winning, Kelly says bet 10 percent of capital. With a 60 percent chance it says 20 percent, which already feels reckless to anyone who has run a book.
   2. It maximises the expected log of wealth, which is the geometric mean, not the arithmetic mean. That is the right objective if you are compounding one pot of capital forever, and it is why the answer is a fraction of wealth rather than a fixed amount.
   3. Full Kelly produces brutal drawdowns by design. The expected maximum drawdown on a full Kelly strategy is roughly 50 percent. No fund with outside capital survives that, because investors redeem long before the long run arrives.
   4. The estimation problem is worse than the volatility problem. Kelly is very sensitive to the edge, and betting twice the Kelly fraction takes your expected growth rate to zero. Since we estimate edge from short, noisy samples, err low.
   5. So in practice people run a quarter to a half Kelly, which gives up a modest amount of growth for a large reduction in drawdown. That trade is almost always worth it with client money.
   6. The other limitation for an equity book: Kelly is single-bet. Real portfolios have correlated positions, so the useful version is a mean-variance or risk-parity construction with a Kelly-style scaling on the whole book, not per position.

   Where candidates lose it

   Reciting the formula and stopping, or claiming you would use it. The interesting part is the estimation error and the drawdown profile. A candidate who says 'half Kelly because I cannot estimate my edge to two decimal places' has answered the question properly; one who says 'bet edge over odds' has quoted a Wikipedia line.

   Expect next

   • What happens if you bet twice Kelly?
   • How would you extend it to correlated positions?
   • How would you estimate your edge in the first place?
2. 028How do you beta-hedge a long position?Portfolio constructionIntermediatetechnicalLong-short equity

   Say this

   Short an index exposure equal to the position value times its beta. If you are long 10 million of a stock with a beta of 1.4, you short 14 million of index to be market neutral on that position. The residual is what you were trying to own in the first place.

   Then walk it

   1. The arithmetic is just that: hedge notional equals position notional times beta. Do it with index futures or an ETF, and futures are usually cheaper because there is no borrow and the financing is embedded.
   2. Beta is estimated, so it is wrong. Which lookback, which frequency, which index? A daily two-year beta and a weekly five-year beta on the same stock can differ by 0.4, and your hedge ratio inherits that error.
   3. Betas also drift with the business. A company that delevers or shifts mix becomes a different beta, and a hedge set once and forgotten stops hedging.
   4. Sector beta is usually the better hedge. If the thesis is company-specific, shorting the sector rather than the broad index strips out more of the noise you do not want, and you are left closer to pure idiosyncratic risk.
   5. The trade-off is that a sector hedge may remove exposure you wanted. If part of your edge was calling the cycle, hedging the sector hedges away your alpha.
   6. State the honest limitation: beta hedging removes the average market sensitivity, not the tails. In a sharp sell-off high-beta stocks fall much more than their historical beta implies, correlations go to one, and the hedge under-delivers exactly when you need it. That is why net exposure limits exist alongside hedges.

   Where candidates lose it

   Hedging one for one. Shorting 10 million of index against a 10 million position with beta 1.4 leaves you materially net long, and that error shows up as an unexplained market P&L in your attribution. Also, say which beta you used and over what window; interviewers probe that immediately.

   Expect next

   • Which beta would you use and over what window?
   • Index hedge or sector hedge, and why?
   • What happens to your hedge in a crash?
3. 031How do you understand portfolio risk?Portfolio constructionIntermediatetechnicalMan GroupInvestment Management · Boston · 2022

   Say this

   As three separate questions, not one number. How much do I expect to lose in a normal month, what happens in a bad one, and what am I unknowingly concentrated in? Volatility answers the first, stress tests answer the second, and factor decomposition answers the third.

   Then walk it

   1. Layer one, the normal case: volatility, VaR and contribution to risk per position. Useful for sizing and for spotting that one position is carrying a third of the risk.
   2. Layer two, the bad case: stress tests and scenarios. Rerun the book through 2008, March 2020, the 2021 momentum unwind, a 100 basis point rate shock. This is where you learn the hedges stop working.
   3. Layer three, the hidden case: factor and thematic decomposition. What is the book's net exposure to growth, to momentum, to oil, to the dollar, to one supply chain? Most surprises are a concentration nobody had named.
   4. Then liquidity risk, which sits underneath all of it. Days to exit at 20 percent of volume, and what the book looks like if you have to raise 20 percent of cash in a week. Illiquidity converts a paper loss into a realised one.
   5. And correlation instability, which is the one that actually hurts. Correlations rise in stress, so a diversified book is less diversified precisely when it matters. I would assume correlations go to one in the tail rather than trusting the historical matrix.
   6. The limitation to volunteer: every number here is backward looking and conditional on a covariance matrix estimated from a period that may not resemble the next one. That is why hard limits and drawdown stops exist alongside the models, rather than instead of them.

   Where candidates lose it

   Answering only with VaR or only with volatility. A single risk number is the wrong shape of answer to this question. Name the three layers, then add liquidity and correlation instability, and say explicitly that the models are backward looking. That last admission is what a risk-focused interviewer is listening for.

   Expect next

   • What does VaR miss?
   • How would you stress test a long-short equity book?
   • How do you think about transaction cost?

   Reported by candidates at Man Group (Investment Management, Boston, 2022). 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.