How to Start a Career in Equity Research? Ft. Pragnya Pattnaik Ep. 72 | Fintelligents

Main Ideas / Concepts Covered

• Equity research is not just “giving stock recommendations.”

  • A good equity research analyst must understand the business and story behind the numbers, not merely generate a valuation or opinion.
  • Candidates often misunderstand the role by expecting to “recommend stocks from day one.”

• Financial modeling is connected to research, but not the whole job.

  • “Modeling” can be superficial if done with back-of-the-envelope assumptions.
  • The real value comes from the research and rationale that support model inputs (e.g., why revenue growth should be 4% vs 5%).
  • Effective modeling depends on strong financial statement analysis and assumptions driven by research.

• Core skills emphasized for equity research

  • Attention to detail
    • Including correcting/restating prior-period numbers to match filings.
  • Analytical skills
    • Understanding what each number implies (e.g., why operating profit is called operating profit and how it connects to performance).
  • Storytelling / explanation ability
    • Answering client questions like: “what changed?” and “why did revenue drop?”
  • Reading and research discipline
    • Using tools (e.g., Bloomberg) and reading to understand margins, competitive positioning, and potential premium/discounts in relative valuation.

• Sector knowledge is dynamic; “picking one sector forever” is unrealistic.

  • A common misconception is that analysts become permanent experts only within one sector.
  • Instead, demand and client opportunity change, so analysts may move between sectors (e.g., real estate → infrastructure → FMCG) depending on where opportunities and clients need them.

• Differences between equity research, credit research, and investment banking

  • Equity research (asset class: equity)
    • Work generally extends to EPS and related equity metrics.
    • Analysts produce outputs like earnings updates and commentary based on changes.
  • Credit research (asset class: fixed income)
    • Focus is more on free cash flow and EBITDA rather than EPS.
    • Evaluates debt products: instrument terms, ratings, and suitability/quality of credit based on fixed-income conventions.
    • Outputs depend on client needs and may be more condensed than a full written report.
  • Investment banking
    • Deal-focused: building materials like pitch books and creating competitive/peer sets and industry landscapes.
    • A peer set cannot be “click-and-take” from data terminals; analysts must ensure peers are genuinely comparable (business class, margins, comparability).

• Other KPO research/business functions beyond equity research

  • Business research / market research
    • Often includes consulting-style research problems, such as:
      • market sizing and demand for new products,
      • survey-based work (interviewing customers/industry players),
      • analysis of margins and operational constraints from a business perspective.
  • Broader takeaway: KPOs may cover five broad research areas:
    • equity research,
    • credit research,
    • investment-banking-related research,
    • business/market research,
    • marketing/customer-survey-type work (as described in the discussion).

• Buy-side vs sell-side (and what “clients” expect)

  • Buy-side (asset managers)
    • Investors using their own money/portfolio mandates.
    • They do portfolio monitoring and may already have committee processes.
    • A KPO analyst may provide tracked information, modeling support, and updates—not necessarily “choosing stocks from scratch” (sometimes ideas are fed into committee workflows).
  • Sell-side
    • Produces reports/recommendations for publication and distribution.
    • Analysts communicate insights to fund managers/clients, where strong analysis is tested by questions.

• Career progression in equity research roles

  • Common starting points:
    • management trainee (often via MBA),
    • junior analyst / trainee analyst.
  • Typical advancement path described:
    • Junior Analyst → Analyst → Senior Analyst
    • then may become Project Manager / Senior Project Manager
    • then roles like VP / AVP / Director (depending on the company’s structure).
  • Seniority often changes responsibilities:
    • junior: input/data work, updating models, basic quarterly earnings inputs,
    • analyst: analysis + commentary (earnings update explanations),
    • senior: building full models and reviewing/tightening junior work,
    • manager levels: overseeing idea review and ensuring correctness.

• Common “mistake patterns” new entrants make

  • Entering numbers without checking restated/prior-year alignment to filings.
  • Treating financial modeling as standalone “number punching.”
  • Not updating prior period figures when discrepancies show up in model inputs.
  • Lacking the ability to explain the “why” behind financial changes when questioned by clients.

• How the market is changing (digital/alternative data)

  • Research is increasingly shaped by alternative data and faster insight generation.
  • Example:
    • retail footfall data from “Jio locations”/maps-style tracking and alternative data providers.
    • analysts incorporate footfall/behavior signals into models without waiting for quarterly filings.
  • Emphasis: it’s not “AI replacing everything,” but using tools/automation to process data faster, freeing analysts for insight generation.

Methodology / Practical Instruction Points (as Described)

• How to build equity research capability (step-by-step approach)

  • Start with financial statement basics
    • identify line items (e.g., revenue = sales),
    • understand how each line item drives the company.
  • Analyze performance drivers
    • understand why operating profit is operating (and what causes it).
  • Progress from company → sector
    • first understand one company deeply (business model, how it earns money, challenges),
    • then expand to the industry/sector once the company logic is clear.
  • Build models based on explained assumptions
    • do not “plug numbers” arbitrarily,
    • ensure every modeling assumption is backed by research (e.g., growth rate “why,” not just “what”).
  • Do rigorous peer and competitive analysis
    • verify peers are truly comparable (business class, margins, competitive position), not just sourced from terminals.
  • Maintain diligence in updates
    • when updating earnings:
      • confirm whether old-period values are restated and must be updated in the model as well.
  • Develop the “client-question” skill
    • practice explaining changes and impacts in a coherent narrative, especially:
      • what changed in revenue/earnings and why.

• Interview preparation focus (implied “how to be the right candidate”)

  • Expect questions testing core financial understanding:
    • depreciation/adjustments,
    • subscription-based models,
    • how metrics like EBIT vs EBITDA should be interpreted and used.
  • Don’t rely on memorized coursework; demonstrate conceptual grasp.
  • Show you can explain assumptions and business logic, not only definitions.

• Analyst-to-client communication discipline

  • Analysts must be able to speak to fund managers/clients and handle many questions.
  • The value is not only what you write, but how correctly your underlying analysis and inputs reflect reality.

Speakers / Sources Featured

• Pragnya Pattnaik (guest; equity research / investment research / investment banking experience)
• Ganesh Nayak (host; finance professional educator; leads the podcast conversation)