Models
Machhar Industries LimitedBSE 543934Chemicals & Petrochemicals
100per 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 model100implied FY26 P/E 8.8× · EV/EBITDA 5.7×
Against CMP ₹425.0076.5%close of 2026-09-10
Growth the CMP implies45.0%revenue, a year for 5 years, on your other inputs
Value after FY3171%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
82137
52-week rangetraded range, a fact not a value
221444

From enterprise to equity · ₹ crore

PV of FY27FY31 free cash flow2
PV of terminal value5
Enterprise value6
less net debt1
less non-controlling interest0
add non-operating investments0
Equity value7
÷ 0.07 crore shares100

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

000000FY24: ₹(0) croreFY24FY25: ₹(0) croreFY25FY26: ₹1 croreFY26FY27: ₹1 croreFY27FY28: ₹0 croreFY28FY29: ₹0 croreFY29FY30: ₹0 croreFY30FY31: ₹0 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%103109116125137
10.50%96101107115124
11.00%9195100106113
11.50%86909499105
12.00%8285889397
The outlined cell is your model. Green figures sit above the CMP of ₹425.00; 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

P1084P50100P90119
10th · 50th · 90th percentile, ₹ per share84 · 100 · 119
Draws below the CMP100%
Rank correlation with ebitda margin+0.81
Rank correlation with discount rate0.56
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
₹ croreFY24FY25FY26FY27FY28FY29FY30FY31
Revenue1716161515151515
growth %(7.4)(0.8)(1.0)(1.0)(1.0)(1.0)(1.0)
EBITDA10111111
margin %6.42.97.37.37.37.37.37.3
less depreciation(1)(0)(0)(0)(0)(0)(0)(0)
EBIT10111111
less tax on EBIT(0)(0)(0)(0)(0)(0)
NOPAT111100
add depreciation10000000
less capex0(0)(0)(0)(0)(0)(0)(0)
less working-capital build00000
Free cash flow to firm(0)(0)10000
Discount factor0.9490.8550.7700.6940.625
Present value00000
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 2, dividends at 0% of profit

₹ croreFY26FY27FY28FY29FY30FY31
Income statement
EBIT111111
Interest at 6.7% on debt(0)(0)(0)(0)(0)
Profit before tax11111
Profit after tax000000
Dividends000000
Balance sheet, year end
Cash444555
Working capital222222
Net block and other assets888888
Debt222222
Equity101010111112
Balance check000000
Cash flow
From operations11111
Investing (capex)(0)(0)(0)(0)(0)
Financing (dividends)00000
Net change in cash00000
Free cash flow to equity00000
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-1%7.3%11.00%5%100(76.5)%
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.