NIIT Learning Systems Limited Intrinsic Value
NIITMTS · Consumer Services · Current price ₹199.06
Is NIIT Learning Systems Limited undervalued?
We estimate the fair value of NIIT Learning Systems Limited at ₹605 per share, against a market price of ₹230. That puts the share price about +163.2% below our estimate, at low confidence. This is our view of what the business is worth, not a target price or a forecast of where the share price will go.
How this fair value is calculated
This estimate comes from 2 methods: Fair multiple (P/E) (₹346), Residual income (excess return on book) (₹864). These methods disagree materially, so the estimate is their midpoint rather than a weighted blend, and the disagreement is part of the finding. The full working, including the assumptions and what data was missing, is set out below.
The range around this estimate
Our estimate for NIIT Learning Systems Limited spans ₹346 to ₹864. That range is wide, which is the honest signal here: read the range rather than the single number. A margin of safety means buying meaningfully below the estimate: the wider the range, the more room the assumptions leave for error.
Margin of safety
Value investors look for a margin of safety: a discount to estimated value that absorbs being wrong. At ₹230 against an estimated value of ₹605, NIIT Learning Systems Limited trades at +163.2%, i.e. a discount to our estimate. How much margin to demand depends on how much you trust the inputs, which is what the confidence band below is for.
How we got this fair value
Every number below is part of the same estimate for NIIT Learning Systems Limited. Nothing here is a target price or a forecast of where the share price will go.
The inputs are thin or the models disagree sharply. This is our least reliable kind of estimate, so read the range rather than the single number.
Estimate range ₹346 – ₹864
Why this method for this business
The business is asset-light and earns returns through a durable moat, making relative PE and residual income the most appropriate models. DCF is less relevant due to the lack of capital intensity and the difficulty in forecasting earnings growth.
The models behind the number
These methods disagree materially, so the estimate is their plain midpoint rather than a weighted blend. The disagreement is itself the finding.
Book value plus the present value of returns earned above the 10.6% cost of equity
- dcf: Not suitable for an asset-light, earnings-driven business with a durable moat
What was missing
- Lack of forward EPS data
- Limited analyst coverage
- Insufficient historical data on moat durability
What drives it
20 inputs, grouped by how strong each claim is
- Sector-median P/E
- 24.2×
- Peers used
- 7
- EPS (TTM)
- 18.63 ₹/share
- Own-history median P/E
- 24.59×
- ROE (normalized)
- 24.4%
- Book value / share
- 112 ₹
peer-median
peer-median
computed
reconstructed (one feature, dampened — not a cap)
computed
reported
- Cost of equity
- 10.6%
building-block
- Term: quality
- -3.4%
- Term: growth
- -22.0%
- Term: capital_allocation
- -6.3%
- Term: financial_strength
- +7.0%
- Term: history
- +0.5%
- Term: sector_rerating
- +0.0%
- Term: rate_regime
- +1.2%
- Term: risk
- +0.0%
- Moat
- Wide
- Excess-return horizon
- 20 yrs
quality 48/100 (weak/erratic returns) → discount
weak ~-1% CAGR (ROCE 31% > hurdle) → discount
capital allocation: falling ROCE / weak cash generation → discount
financial strength: effectively debt-free → premium
history: market paid +2% vs sector, dampened ×0.3 (one feature, not the anchor)
sector re-rating: no sector-norm history → not used
rates: risk-free 6.9% below ~7.1% normal → higher multiple
risk: no analyst-dispersion signal available → neutral (lowers confidence, not PE)
computed
computed
- Premium vs sector
- -23.2%
- Fair-multiple confidence
- 78%
- Fair P/E
- 18.59×
fundamentals + macro (not capped at own history)
data completeness + term agreement
sector median × ∏(1+term) — Dynamic Fair Multiple
Who computed this
A language model (qwen3:8b) selects the valuation method and the judgement inputs for NIIT Learning Systems Limited: which models suit the business, the moat, the growth and margin assumptions. It does not produce the number. The fair value itself is computed in Python by a deterministic engine (version 2026.08.1) from those inputs, so the same inputs always give the same result and every figure above can be traced to a source.
Estimated 15 Sept 2026. Re-run as new financials and news arrive.
How we value stocks
We estimate what a business is worth from its own economics: cash flows, returns on capital, and a multiple justified by its quality, rather than from where the share price has been. A fair value estimate is a view, not a verdict, and it is only as good as the inputs listed above.
Read the full fair-value methodologyMore on NIIT Learning Systems Limited
DocStoX estimates are computed from reported financials, for informational purposes only, not investment advice. Consult a SEBI-registered advisor before investing.