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. 082Talk me through your research process for a systematic signal. How do you avoid fooling yourself?Quant and systematicHardtechnicalBalyasny Asset ManagementQuantitative Trading · London · 2025

   Say this

   Start with an economic reason the signal should work, then test it in a way that can fail. Hypothesis first, then data preparation, then a simple specification, then out-of-sample and out-of-region validation, then costs, then capacity. The discipline is that the hypothesis comes before the backtest, not after it.

   Then walk it

   1. State the economic mechanism first and write it down before running anything. Who is on the other side, and why are they there? A signal with no story about who is losing money is almost certainly a data artifact.
   2. Then the data work, which is most of the time and all of the risk. Point-in-time data with correct reporting lags, restated figures handled properly, delisted and merged companies included, corporate actions adjusted, and survivorship bias eliminated. Look-ahead bias is the most common silent killer and it always flatters the result.
   3. Then the simplest possible specification. One parameter, no optimisation, sensible defaults. If the effect does not show up in the naive version, it probably is not there. Elaboration after validation, never before.
   4. Then validation that can actually fail: hold out a period you never look at, test in other regions and other asset classes, test across sub-periods, and check that the result is not driven by a handful of stocks or one month. Report the number of specifications you tried, because a t-statistic loses its meaning after the twentieth attempt.
   5. Then costs and capacity, which kill more signals than statistics do. Model spread and impact, compute net-of-cost performance at realistic size, and check whether the signal survives a one-day implementation lag. A signal requiring same-second execution is not a signal for a fundamental-horizon book.
   6. Then the honest self-checks: decide the kill criteria before the test, keep a research log of everything tried including the failures, and have someone else reproduce the pipeline. The uncomfortable truth is that most published anomalies do not replicate out of sample, so my prior on my own new signal should be low.

   Where candidates lose it

   Describing a backtest rather than a research process. The order of operations is the answer: hypothesis, then data hygiene, then a naive test, then validation, then costs. A candidate who does not mention point-in-time data, look-ahead bias and the multiple-testing problem will not get through a quant research interview.

   Expect next

   • How many specifications did you try on your last project?
   • How do you handle restated financials in a backtest?
   • What is your kill criterion for a signal?

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

2. 089What SEBI rules would you need to know before running a long-short book in India?India and Category III AIFsHardtechnicalIndian hedge fundsCategory III AIFs

   Say this

   Four bodies of rules: the AIF Regulations that govern the fund itself, the derivative and position limit framework that governs how you short, the insider trading regulations, and the disclosure thresholds on large positions. Plus the operational rules on valuation, reporting and custody.

   Then walk it

   1. The AIF Regulations of 2012 first: registration, the Category III leverage limit expressed as gross exposure not exceeding twice NAV, the 1 crore investor minimum, the manager's continuing interest, periodic reporting to SEBI, and the requirement to disclose the leverage and risk framework in the placement memorandum.
   2. Then the derivatives framework, because that is how you short. Which names are in the futures and options segment, market-wide and client-level position limits, margining including SPAN and exposure margin, and the periodic tightening of index option rules. Your short capacity is defined by these, not by your conviction.
   3. Then insider trading, which is SEBI's Prohibition of Insider Trading Regulations of 2015. Unpublished price sensitive information is the Indian formulation, and the regime requires a code of conduct, a structured digital database recording who received what information, trading windows and pre-clearance. The structured digital database requirement is a genuinely distinctive Indian feature worth naming.
   4. Then disclosure. Takeover Regulations require disclosure at 5 percent and on changes of 2 percent thereafter, which matters for a concentrated book. Short positions must also be disclosed to the exchanges under the framework that prohibits naked short selling; institutional investors cannot square off intraday.
   5. Then the operational layer: valuation policy and independent valuation of unlisted holdings, custodian requirements, benchmarking of AIF performance, and the compliance test report the manager files.
   6. The honest caveat: this is an actively changing rulebook, with amendments most years on derivative limits, disclosure and AIF structuring. So I would give you the framework and say that the specific thresholds need checking against the current circulars rather than quoting them from memory as though they were fixed.

   Where candidates lose it

   Bluffing specific numbers. Indian regulation changes frequently and an interviewer who works under it will know when a threshold is stale. Give the four buckets confidently, name the distinctive items such as the structured digital database and the no-naked-shorting rule, and flag that the exact limits need verification.

   Expect next

   • What is a structured digital database and who has to keep one?
   • Can an institutional investor square off a short intraday in India?
   • How does the 5 percent disclosure threshold affect a concentrated book?

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.