Models
MOHITE INDUSTRIES LTD.MOHITETextiles & Apparels
2per 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 model2implied FY26 P/E 8.3× · EV/EBITDA 8.4×
Against CMP ₹2.7114.5%close of 2026-09-10
Growth the CMP implies45.0%revenue, a year for 5 years, on your other inputs
Value after FY3166%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
15

From enterprise to equity · ₹ crore

PV of FY27FY31 free cash flow48
PV of terminal value93
Enterprise value142
less net debt(95)
less non-controlling interest0
add non-operating investments0
Equity value47
÷ 20.10 crore shares2

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

00000000FY21: ₹1 croreFY21FY22: ₹(5) croreFY22FY23: ₹3 croreFY23FY24: ₹(20) croreFY24FY25: ₹32 croreFY25FY26: ₹23 croreFY26FY27: ₹15 croreFY27FY28: ₹14 croreFY28FY29: ₹12 croreFY29FY30: ₹10 croreFY30FY31: ₹9 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%33445
10.50%22334
11.00%22233
11.50%12223
12.00%11122
The outlined cell is your model. Green figures sit above the CMP of ₹2.71; 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

P101P502P903
10th · 50th · 90th percentile, ₹ per share1 · 2 · 3
Draws below the CMP68%
Rank correlation with discount rate0.73
Rank correlation with ebitda margin+0.66
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
₹ croreFY23FY24FY25FY26FY27FY28FY29FY30FY31
Revenue84125167153146138131125119
growth %(45.5)48.133.4(8.0)(5.0)(5.0)(5.0)(5.0)(5.0)
EBITDA211923171615141413
margin %25.415.513.510.910.910.910.910.910.9
less depreciation(7)(7)(7)(6)(6)(5)(5)(5)(5)
EBIT141216111010998
less tax on EBIT(3)(3)(2)(2)(2)(2)
NOPAT887776
add depreciation777665555
less capex(24)(10)(0)(2)(2)(3)(4)(5)(6)
less working-capital build54444
Free cash flow to firm3(20)32151412109
Discount factor0.9490.8550.7700.6940.625
Present value1512976
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 95, dividends at 0% of profit

₹ croreFY26FY27FY28FY29FY30FY31
Income statement
EBIT111010998
Interest at 11% on debt(10)(10)(10)(10)(10)
Profit before tax(0)(1)(1)(2)(2)
Profit after tax4(0)(1)(1)(1)(2)
Dividends000000
Balance sheet, year end
Cash0814182122
Working capital908681777370
Net block and other assets162159157156156157
Debt959595959595
Equity129128128127126124
Balance check000000
Cash flow
From operations109877
Investing (capex)(2)(3)(4)(5)(6)
Financing (dividends)00000
Net change in cash86431
Free cash flow to equity86431
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%10.9%11.00%5%2(14.5)%
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.