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. 010How do you build a model that is detailed enough to be useful but simple enough that you can cover a lot of companies?ModellingHardtechnicalBalyasny Asset ManagementEquity Research · New York · 2026

   Say this

   Model deeply only where the variance is. For most companies two or three line items drive the outcome, so those get detailed driver builds and everything else gets a margin assumption or a percentage of sales.

   Then walk it

   1. Identify the swing factors first. For a retailer it is same-store sales and gross margin. For a bank it is net interest margin and provisions. For a software company it is net retention and sales efficiency. Model those properly.
   2. Everything else goes to ratios: other opex as a percent of revenue, working capital as days, tax at the guided rate. Precision there adds nothing and costs you maintenance time.
   3. Standardise the template across the coverage universe so the same row does the same thing in every file. That is what actually makes 15 names maintainable, because updating a quarter becomes mechanical.
   4. Build it around the disclosure you will actually receive. If the company only reports two segments, a five-segment model will be broken every quarter.
   5. And keep a one-page output: the drivers, the earnings bridge versus consensus, and the valuation. If the summary tab tells the story, the depth underneath can stay limited.
   6. The test I would apply: can I update this model in 20 minutes on results day? If not, it is too complex to cover 15 names with.

   Where candidates lose it

   Saying you would build the most detailed model possible. On the buy side, model complexity is a liability. The insight being tested is that modelling effort should be allocated to variance, not spread evenly.

   Expect next

   • How many names can one analyst realistically cover?
   • What goes on your summary tab?
   • How do you update on results day?

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

2. 036How would you forecast revenue for a company you have never modelled before?ModellingIntermediatetechnicalHoulihan LokeyInvestment Banking · New York · 2026

   Say this

   Build it from drivers, never from a growth rate. Find the two physical quantities that multiply to revenue, price and volume in some form, then forecast each separately against something observable.

   Then walk it

   1. Decompose first. A retailer is stores times sales per store. An airline is available seat miles times load factor times yield. A software business is customers times average revenue per customer. A bank is loan balances times net interest margin.
   2. Forecast each driver against something external: industry capacity, population, disposable income, an installed base, a contract backlog. That makes the forecast falsifiable and lets you update it when the external data moves.
   3. Cross-check top-down. If your bottom-up build implies the company takes six points of market share in two years, you need a reason. Reconciling bottom-up to market size is the sanity check that catches most bad models.
   4. Separate organic from acquired growth. A company growing 15 percent of which 10 is bought is a completely different business from one growing 15 organically, and blending them hides that.
   5. Then sanity-check against history: is the implied growth faster than the company has ever achieved? If so, say why this time is different, or lower it.
   6. A flat growth-rate assumption is acceptable only in the terminal years, and even then you should say what it implies.

   Where candidates lose it

   Applying a growth percentage to last year's revenue. It cannot be argued with, cannot be updated by new data, and gives you no basis for a variant view. Driver-based building is the entire point.

   Expect next

   • What is the driver for the company we cover?
   • How do you reconcile bottom-up to market size?
   • Where does your forecast differ from consensus?

   Reported by candidates at Houlihan Lokey (Investment Banking, New York, 2026). 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.