Data Patterns (India) Limited DCF Valuation
DATAPATTNS · Capital Goods · Current price ₹4,060.2
Data Patterns (India) Limited cash-flow valuation
Our engine did not use a discounted-cash-flow model for Data Patterns (India) Limited. It routes each business to the methods that suit it, and a DCF is a poor lens where cash-flow forecasts are fragile or the business is capital-structure driven. The methods it did use, and why, are set out below. Our published estimate is ₹3,590.
Try your own assumptions
Prefer to build the discounted cash flow yourself? The DCF calculator below opens pre-filled with Data Patterns (India) Limited's reported free cash flow, net debt and share count, so you can set your own growth and discount rate.
How we got this fair value
Every number below is part of the same estimate for Data Patterns (India) Limited. Nothing here is a target price or a forecast of where the share price will go.
Workable, with real gaps. Weigh it alongside your own view rather than on its own.
Estimate range ₹3,231 – ₹3,948
Why this method for this business
The company operates in the aerospace and defense sector, which is capital-intensive and cyclical. A relative P/E and EV/EBITDA model are appropriate for capturing the value of its durable moat and normalized earnings power.
The models behind the number
Each method is weighted by how well its inputs held up for this company.
required inputs missing
- dcf: Not suitable for a capital-intensive sector with uncertain cash flows
- relative_pe: Not used as the primary model due to the need for a more robust valuation framework
What was missing
- Lack of forward EBITDA estimates
- Limited analyst coverage for the company
What drives it
15 inputs, grouped by how strong each claim is
- Sector-median P/E
- 48.75×
- Peers used
- 4
- EPS (TTM)
- 47.86 ₹/share
- Own-history median P/E
- 61.66×
peer-median
peer-median
computed
reconstructed (one feature, dampened — not a cap)
- Term: quality
- +2.5%
- Term: growth
- +40.0%
- Term: capital_allocation
- +10.9%
- Term: financial_strength
- +8.0%
- Term: history
- +7.9%
- Term: sector_rerating
- +0.0%
- Term: rate_regime
- +1.2%
- Term: risk
- +0.0%
quality 60/100 (high, stable returns) → premium
durable ~35% CAGR (ROCE 20% > hurdle) → premium
capital allocation: rising ROCE funded by strong FCF → premium
financial strength: effectively debt-free → premium
history: market paid +26% 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)
- Premium vs sector
- +53.8%
- Fair-multiple confidence
- 80%
- Fair P/E
- 75×
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 Data Patterns (India) 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 14 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 Data Patterns (India) Limited
DocStoX estimates are computed from reported financials, for informational purposes only, not investment advice. Consult a SEBI-registered advisor before investing.