Ask ten different unlisted-shares investors how they arrive at a "fair" price, and you'll likely get ten different answers. Some swear by the last traded price in the grey market. Others insist on running a full DCF before they touch a single share. The truth sits somewhere in between — fair market value isn't a single number pulled out of a formula, it's a range that gets narrower the more methods you cross-check against each other.
For anyone investing in India's pre-IPO and unlisted space, this matters more than it does in listed markets. There's no ticker flashing a real-time price, no order book depth to lean on, and no SEBI-mandated disclosure cadence forcing companies to keep the market updated every quarter. You're often working with an annual report that's eight months old, a couple of broker quotes, and your own judgment. Getting the valuation right — or at least defensible — is the difference between buying into genuine value and overpaying for a story.
Fair market value (FMV) is the price at which a share would change hands between a willing buyer and a willing seller, neither under compulsion to transact, both reasonably informed about the business. For listed stocks, the market does this work for you every second. For unlisted shares, you have to reconstruct that willing-buyer-willing-seller price yourself, using a mix of methods that Indian tax law, merchant bankers, and RBI/FEMA valuation norms all recognise in some form.
There isn't one "correct" formula. There are several, and each one covers for the others' blind spots.
This is perhaps the most straightforward place to start, and often is the very first place where Planify’s research desk looks. Essentially, you pick up an unlisted firm, find a similar-listed firm that does the same type of business, and multiply its metrics, be it P/E, P/B, EV/EBITDA, or industry-specific multiples like AUM-based valuation for asset managers, against the unlisted firm’s financials.
But it's hard to choose peers that are really comparable by size, development stage, margins, and to use illiquidity discount, because after all, an unlisted firm cannot be disposed of within a single day like a listed company would be. Otherwise, you’ll always overestimate the price of every unlisted company.
Whereas Comparable Company Approach asks what the business is worth compared to its peers, DCF asks what the business is worth based on its future cash flows. It's the most theoretically sound method and the one auditors and merchant bankers lean on for statutory valuations under the Companies Act and Income Tax Act (Rule 11UA).
Its weakness is also its strength — it's only as good as your assumptions. Push the terminal growth rate up half a percent or shave the discount rate down, and the valuation swings meaningfully. For an early-stage or pre-profit company, this method can be almost meaningless. For an established, cash-generative business, it's often the most reliable anchor.
Here you simply value the company based on its assets minus liabilities, adjusted to fair value where needed — real estate marked to market, investments marked to current prices, and so on. This method matters most for asset-heavy businesses: NBFCs, holding companies, real estate players, and financial institutions where book value is a meaningful anchor rather than an afterthought.
For an asset-light services or tech business, NAV tells you almost nothing about what the company is actually worth, since most of its value sits in intangibles the balance sheet doesn't capture.
If the company has raised a funding round recently, or if there's been a documented block deal in the unlisted market, that transaction price is often the single most reliable data point you have — provided the deal is recent and at arm's length. A primary funding round six months ago, priced by an institutional investor who did their own diligence, tells you more than any spreadsheet model built from outside the company.
The risk is relying on stale or thin-volume data. A single trade of 500 shares between two individuals, six months back, in a company that's since changed its growth trajectory, isn't a price you should anchor to blindly.
In practice, none of these methods stands alone. A credible fair value estimate usually triangulates two or three approaches and looks at where they converge. If your DCF says ₹1,800, the peer multiple method says ₹2,100, and the last real transaction happened at ₹1,950 — your fair value band is probably somewhere in that ₹1,850–₹2,050 zone, not any single point estimate. Divergence between methods is itself informative: a big gap usually means either your assumptions are off, or the market is mispricing something the fundamentals haven't caught up with yet.
National Stock Exchange (NSE) can be considered a relatively valuable example of a live case exactly because it lies on the crossroads of all the approaches listed above and because actual figures are available for analysis.
Where the stock trades: The stock is trading in a wide band between around ₹1,960 and ₹2,065 per share with a 52-week range between around ₹1,600 and ₹2,350 at the end of July 2026. Such a range alone is quite revealing – a stock so close to liquidity should not typically fluctuate by more than 40% during a single year and the fluctuations coincide with IPO news almost perfectly.
Comparable company approach: As of financial year 2026, the PAT of NSE comes in at ₹7,710 crore with an EPS of ₹41.62, down from ₹49.24 for FY25 due to lower volume of trades and margins throughout the year. At an approximate market price of ₹1,960, such EPS would make for a trailing P/E of 47.1x (1,960 ÷ 41.62). Compare that with BSE — NSE's closest listed peer — which has been trading at a P/E closer to 54.1x over the same period. Applying BSE's multiple to NSE's updated EPS gives a comparable-value estimate of roughly ₹2,252 (41.62 × 54.1) — about 15% above where the unlisted market currently prices the stock. That's a narrower gap than a P/E built on the older, higher FY25 EPS would suggest, which is exactly why using the latest reported earnings — not last year's — matters when you're running this method.
Recent transaction data: NSE's own IPO-related valuation chatter has pegged the business at approximately ₹5.19 lakh crore, based on regulatory filings and board-approved processes following SEBI's no-objection steps earlier in 2026. That figure, divided across NSE's outstanding share base, gives a valuation reference point that sits reasonably close to the upper end of the current trading band — which makes sense, since anticipation of a listing tends to pull unlisted prices toward the expected IPO price as the timeline firms up.
Reading the gap: The roughly 15% delta between the comparable-company fair value (~₹2,252) and the current traded price (~₹1,960) isn't necessarily "free money" waiting to be captured. It reflects real, priced-in risks — continued regulatory delays, uncertainty on the final IPO valuation band, and the simple fact that unlisted shares carry liquidity and lock-in constraints that BSE's listed stock doesn't. Worth noting too: the gap has actually compressed year-on-year, since FY26's softer PAT and EPS pull the comparable-value estimate down even as the traded price has held up in its ₹1,960–2,065 band. A disciplined investor treats the remaining gap as the illiquidity and event-risk discount the market is demanding, not as a mispricing to arbitrage away. If the IPO timeline concretizes and the discount narrows further, that's the re-rating thesis; if earnings keep softening, the gap could close from the other direction instead — the fair-value estimate coming down to meet the price, not the price rising to meet it.
Calculating fair market value for an unlisted share isn't about finding the "right" formula — it's about building a defensible range using methods that check each other's assumptions, then understanding why the market price sits where it does relative to that range. When the gap is wide, ask what risk is being priced in before you assume it's an opportunity. That discipline is what separates informed pre-IPO investing from simply following momentum in a grey market.
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