Models
NEOPOLITAN PIZZA AND FOODS LIMBSE 544269Agricultural Food & other Products
7per 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 model7implied FY26 P/E 6.2× · EV/EBITDA 23.4×
Against CMP ₹6.75+2.9%close of 2026-09-10
Growth the CMP implies45.0%revenue, a year for 5 years, on your other inputs
Value after FY3172%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
510
52-week rangetraded range, a fact not a value
614

From enterprise to equity · ₹ crore

PV of FY27FY31 free cash flow3
PV of terminal value8
Enterprise value12
less net debt0
less non-controlling interest0
add non-operating investments0
Equity value12
÷ 1.70 crore shares7

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

0000000FY25: ₹(9) croreFY25FY26: ₹(2) croreFY26FY27: ₹1 croreFY27FY28: ₹1 croreFY28FY29: ₹1 croreFY29FY30: ₹1 croreFY30FY31: ₹1 croreFY31
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%788910
10.50%77889
11.00%67778
11.50%66677
12.00%56667
The outlined cell is your model. Green figures sit above the CMP of ₹6.75; 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

P106P507P908
10th · 50th · 90th percentile, ₹ per share6 · 7 · 8
Draws below the CMP38%
Rank correlation with discount rate0.97
Rank correlation with ebitda margin+0.23
Rank correlation with revenue growth0.03
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
₹ croreFY25FY26FY27FY28FY29FY30FY31
Revenue51302827252423
growth %(42.3)(5.0)(5.0)(5.0)(5.0)(5.0)
EBITDA100000
margin %1.71.71.71.71.71.7
less depreciation(0)(0)(0)(0)(0)(0)
EBIT000000
less tax on EBIT(0)(0)(0)(0)(0)(0)
NOPAT000000
add depreciation000000
less capex(3)(0)(0)(0)(0)(0)(0)
less working-capital build11111
Free cash flow to firm(9)11111
Discount factor0.9490.8550.7700.6940.625
Present value11111
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 0, dividends at 0% of profit

₹ croreFY26FY27FY28FY29FY30FY31
Income statement
EBIT000000
Interest at 4.8% on debt(0)(0)(0)(0)(0)
Profit before tax00000
Profit after tax000000
Dividends000000
Balance sheet, year end
Cash112345
Working capital181717161514
Net block and other assets121212121212
Debt000000
Equity292929292929
Balance check00000(0)
Cash flow
From operations11111
Investing (capex)(0)(0)(0)(0)(0)
Financing (dividends)00000
Net change in cash11111
Free cash flow to equity11111
Other liabilities are held at their FY26 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 · editingDCF-5%1.7%11.00%5%72.9%
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.