Models
Aspira Pathlab & Diagnostics LBSE 540788Healthcare Services
34per share · Base Model Note
Revenue growth, the horizon and scenarios are yours to change. Every other input is part of the Trader plan; saving, sharing a saved link and the live-formula workbook are part of the Institutional plan.
Scenario
Value per share, your model34implied FY25 P/E 14.7× · EV/EBITDA 9.9×
Against CMP ₹95.0064.0%close of 2026-09-10
Growth the CMP implies45.0%revenue, a year for 5 years, on your other inputs
Value after FY3068%share of enterprise value in the terminal
This figure is the arithmetic of your inputs and nothing else. MarketPing publishes no fair value, target or rating; the model is yours.

Where the methods land · ₹ per share · the dashed line is the CMP

DCF, rate ±1 · growth ±1your model across the sensitivity grid
2748
52-week rangetraded range, a fact not a value
49136

From enterprise to equity · ₹ crore

PV of FY26FY30 free cash flow11
PV of terminal value23
Enterprise value34
less net debt1
less non-controlling interest0
add non-operating investments0
Equity value35
÷ 1.03 crore shares34

Free cash flow, filed and modelled · ₹ '000 crore

00000FY25: ₹1 croreFY25FY26: ₹3 croreFY26FY27: ₹3 croreFY27FY28: ₹3 croreFY28FY29: ₹3 croreFY29FY30: ₹2 croreFY30
Filed, cash from operations − capexModelled free cash flow to firm

Sensitivity · ₹ per share

Down Across
WACCterminal growth4.0%4.5%5.0%5.5%6.0%
10.00%3538404448
10.50%3335374043
11.00%3132343639
11.50%2930323436
12.00%2729303133
The outlined cell is your model. Green figures sit above the CMP of ₹95.00; n/a marks a terminal growth at or above the discount rate. Steps: WACC and terminal growth ±0.5 point, growth ±2, margin ±1.

Distribution of outcomes · 4,000 draws · growth, margin and the discount rate vary together

P1027P5034P9042
10th · 50th · 90th percentile, ₹ per share27 · 34 · 42
Draws below the CMP100%
Rank correlation with ebitda margin+0.85
Rank correlation with discount rate0.43
Rank correlation with revenue growth+0.21
Each driver is drawn from a PERT distribution between the lowest and highest value across your scenarios (or ±50% growth, ±20% margin when there is one scenario), with the discount rate ±1.5 points. Seeded, so the same inputs give the same picture.

Projected cash flow to the firm · ₹ crore

History Forward
₹ croreFY25FY26FY27FY28FY29FY30
Revenue222426283032
growth %8.08.08.08.08.0
EBITDA344455
margin %15.815.815.815.815.815.8
less depreciation(1)(2)(2)(2)(2)(2)
EBIT222233
less tax on EBIT000000
NOPAT222233
add depreciation122222
less capex(0)(0)(1)(1)(2)(3)
less working-capital build(0)(0)(0)(0)(0)
Free cash flow to firm33332
Discount factor0.9490.8550.7700.6940.625
Present value33221
History columns are the filed years (free cash flow there is cash from operations − capex, as filed); the base year and everything to its right come from the engine. Forward is the explicit horizon of the model itself: 3, 5 or 10 years, then flat.

The three statements, projected · ₹ crore · debt held at 1, dividends at 0% of profit

₹ croreFY25FY26FY27FY28FY29FY30
Income statement
EBIT222233
Interest at 8% on debt(0)(0)(0)(0)(0)
Profit before tax22233
Profit after tax022233
Dividends000000
Balance sheet, year end
Cash258111315
Working capital222333
Net block and other assets141211111111
Debt111111
Equity121416192124
Balance check000000
Cash flow
From operations34445
Investing (capex)(0)(1)(1)(2)(3)
Financing (dividends)00000
Net change in cash33322
Free cash flow to equity33322
Other liabilities are held at their FY25 level, so the check tests only what the model moves: cash, working capital, net block and other assets, debt and equity. A non-zero check would mean the three statements no longer tie.

Scenarios side by side · ₹ per share

ScenarioTemplateGrowthMarginRateTerminal₹ / sharevs CMP
Base · editingDCF8%15.8%11.00%5%34(64.0)%
A scenario is a full set of inputs under a name. Keep Base as the filed history carried forward; add Bull and Bear by saving the current inputs under those names and moving the two or three assumptions you actually hold a view on. The distribution above draws each driver between the lowest and highest value across your scenarios, so three scenarios give it a real range; with one scenario it falls back to fixed bands.