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Fundamental Analysis
Updated 2025-06-04·Editorial policy·Trading system

What is EPS (Earnings Per Share)?

Earnings per share is net profit attributable to common shareholders divided by shares outstanding.

Formula

Basic EPS = (Net Income - Preferred Dividends) ÷ Weighted Average Shares Example: Net Income: ₹500 crore Preferred Dividends: ₹0 Shares Outstanding: 50 crore EPS = 500 ÷ 50 = ₹10 per share Meaning: Each share represents ₹10 of annual profit If you own 100 shares, your portion of profit = ₹1,000

Indian market context (NSE)

Reference levels: Nifty 50 at 24,300, Reliance Industries at ₹1,300, Bank Nifty futures at 55,000 (lot size 30). Examples below show how EPS (Earnings Per Share) shows up on Indian index, equity, and futures books — update to live quotes in your journal.

Nifty 50 perspective

Nifty at 24,300: index-level earnings per share (eps) aggregates 50 names — useful macro filter for allocation, less useful for Bank Nifty scalps the same afternoon.

Reliance Industries perspective

Earnings Per Share (EPS) for Reliance at ₹1,300: pull from latest exchange filings and investor presentation — compare to Nifty 50 median for context, not as a timing signal for intraday futures.

How to validate

  • Validate EPS (Earnings Per Share) trades against the published event calendar.
  • Separate earnings trades from non-event technical tags in analytics.
  • Re-read news source in journal note to avoid hindsight bias in review.
  • Compare results only within the same market regime (bull/bear/sideways).

How to track in TradeLyser

  • Link trade to catalyst note (event, date, source) in comments.
  • Tag “event trade” vs “technical only” before entry.
  • Calendar review after results season for tag-level P&L.
  • Export event-tagged trades for annual tax and process reconciliation.

Best practices

  • Trade smaller into unknown event risk around EPS (Earnings Per Share).
  • Verify source quality before tagging fundamental triggers.
  • Do not retrofit fundamental narratives onto technical entries.
  • Keep investment and trading books separate in analytics.

Common pitfalls

  • Trading headlines without time-stamped journal proof.
  • Holding losers because the “story” behind EPS (Earnings Per Share) must recover.
  • Mixing tax-loss harvesting with active trading tags.
  • Using stale data after earnings revisions.

How to use this in TradeLyser

Tag earnings-week trades; note reported vs expected EPS in notebook for post-review.

Related terms

FAQ

EPS and stock splits?

Adjust for splits when comparing historical EPS.

Trade only on EPS beat?

Tag beat/miss reactions — your stats decide edge.

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