Models
INDAG RUBBER LTD.BSE 509162Auto Components
14per 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 model14implied FY26 P/E 3.5× · EV/EBITDA 4.8×
Against CMP ₹131.6089.6%close of 2026-09-10
Growth the CMP implies45.0%revenue, a year for 5 years, on your other inputs
Value after FY3153%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
1119
52-week rangetraded range, a fact not a value
77147

From enterprise to equity · ₹ crore

PV of FY27FY31 free cash flow20
PV of terminal value22
Enterprise value42
less net debt(6)
less non-controlling interest0
add non-operating investments0
Equity value36
÷ 2.63 crore shares14

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

000000FY20FY21: ₹3 croreFY21FY22: ₹4 croreFY22FY24: ₹6 croreFY24FY25: ₹(1) croreFY25FY26: ₹6 croreFY26FY27: ₹8 croreFY27FY28: ₹6 croreFY28FY29: ₹5 croreFY29FY30: ₹3 croreFY30FY31: ₹2 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%1415161719
10.50%1314151617
11.00%1213141415
11.50%1212131314
12.00%1112121313
The outlined cell is your model. Green figures sit above the CMP of ₹131.60; 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

P1011P5014P9017
10th · 50th · 90th percentile, ₹ per share11 · 14 · 17
Draws below the CMP100%
Rank correlation with ebitda margin+0.88
Rank correlation with discount rate0.44
Rank correlation with revenue growth0.02
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
₹ croreFY22FY24FY25FY26FY27FY28FY29FY30FY31
Revenue167251228215204194184175166
growth %(1.7)50.5(9.1)(6.1)(5.0)(5.0)(5.0)(5.0)(5.0)
EBITDA1172988877
margin %0.46.60.84.14.14.14.14.14.1
less depreciation(4)(5)(7)(7)(7)(6)(6)(6)(5)
EBIT(4)11(5)222221
less tax on EBIT(1)(1)(0)(0)(0)(0)
NOPAT111111
add depreciation457776665
less capex(4)(11)(4)(3)(3)(4)(5)(6)(6)
less working-capital build32222
Free cash flow to firm46(1)86532
Discount factor0.9490.8550.7700.6940.625
Present value75421
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 10, dividends at 62.1% of profit

₹ croreFY26FY27FY28FY29FY30FY31
Income statement
EBIT222221
Interest at 11.8% on debt(1)(1)(1)(1)(1)
Profit before tax11000
Profit after tax1000000
Dividends(6)(0)(0)(0)(0)(0)
Balance sheet, year end
Cash41015192122
Working capital525047454340
Net block and other assets250247244243243244
Debt101010101010
Equity234234234234234234
Balance check000000
Cash flow
From operations109988
Investing (capex)(3)(4)(5)(6)(6)
Financing (dividends)(0)(0)(0)(0)(0)
Net change in cash65421
Free cash flow to equity75421
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%4.1%11.00%5%14(89.6)%
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.