Equity Research interview preparation

Questions

100

Traced to a firm

72

Firms

45

Updated

September 2026

Asked at

All firmsMorningstar12Man Group6Balyasny Asset Management5BLBlackRock5FTFranklin Templeton5MSCI5Jefferies4CSCredit Suisse3Fidelity Investments3Moody's3Perella Weinberg Partners3Point723S&P Global3The Vanguard Group3WMWellington Management3Advent International2Apollo Global Management2Bank of America2Carlyle Group2DED.E. Shaw2Houlihan Lokey2HSBC2Piper Sandler2Sequoia Capital2SSState Street2Viking Global Investors2WBWilliam Blair2ACAQR Capital Management1BGBaupost Group1BMBNY Mellon1Centerview Partners1Coatue Management1Goldman Sachs1GSGuggenheim Securities1HWHarris Williams1Insight Partners1Invesco1Mizuho1Moelis & Company1MSMorgan Stanley1PIMCO1SCSchroders1Scotiabank1T. Rowe Price1TSTruist Securities1

Topic

All topicsResearch process9Stock pitch6Company analysis8Investment philosophy5Valuation14Modelling2Portfolio and risk8Macro8Sector knowledge2Accounting8Career and fit12Industry knowledge6Quantitative research1Sector: technology3Sector: consumer1Sector: healthcare1Sector: energy1Sector: financials2Sector: industrials1Case and estimation2

Level

AnyCoreIntermediateHard

Type

AnyTechnicalCaseFitBrainteaserMarket view

1. 029How do you construct a factor, and how would you decide whether it is real?Quantitative researchHardtechnicalACAQR Capital ManagementInvestment Research · New York · 2021

   Say this

   Define the signal, rank the universe on it, form long-short portfolios from the extremes, and measure the spread after controlling for known factors. It is real only if it survives transaction costs, out-of-sample testing and an economic explanation.

   Then walk it

   1. Construction: choose the metric, neutralise for size, sector and region so you are not just picking up a sector bet, then sort into quantiles and go long the top and short the bottom with rebalancing at a defined frequency.
   2. Measure the spread return, its volatility, the information ratio, and the turnover it requires. Turnover matters because a signal that needs daily rebalancing can be profitable on paper and unprofitable after costs.
   3. Control for known factors. If your new signal's returns disappear once you regress against value, momentum, quality and size, you have rediscovered an existing factor with a new name.
   4. Then the tests that actually matter: out-of-sample and out-of-region performance, stability across sub-periods, and how many specifications you tried before finding this one. Data mining is the default explanation for any new factor.
   5. And demand an economic story. A factor should be compensation for a risk, or exploitation of a behavioural bias, or a structural constraint on other investors. Without that, decay after publication is the base case.
   6. The honest position: most published factors do not survive replication, so the prior on any new one should be skeptical.

   Where candidates lose it

   Describing the mechanics with no discussion of multiple testing and data mining. The intellectual content of modern factor research is that backtests are easy and robustness is hard. Say so.

   Expect next

   • How would you optimise the construction?
   • Why do factors decay after publication?
   • How would you know if you had overfitted?

   Reported by candidates at AQR Capital Management (Investment Research, New York, 2021). 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.