Models
WARREN TEA LTD.BSE 508494Agricultural Food & other Products
₹-91per 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 model₹(91)implied P/B (1.14)× on FY26 book
Against CMP ₹45.70−298.3%close of 2026-09-10
Cost of equity9.25%risk-free + beta × equity risk premium
Book equity, FY26₹79per share · excess returns add ₹(170)
This figure is the arithmetic of your inputs and nothing else. MarketPing publishes no fair value, target or rating; the model is yours.
Excess-return schedule · ₹ crore · book equity earns your ROE; value is book plus the returns above the cost of equity
| ₹ crore | FY27 | FY28 | FY29 | FY30 | FY31 |
|---|---|---|---|---|---|
| Opening book equity | 95 | 93 | 90 | 88 | 86 |
| Net income at -2.5% ROE | (2) | (2) | (2) | (2) | (2) |
| Cost of equity charge at 9.25% | (9) | (9) | (8) | (8) | (8) |
| Excess return | (11) | (11) | (11) | (10) | (10) |
| Present value | (11) | (10) | (9) | (8) | (7) |
| Closing book equity | 93 | 90 | 88 | 86 | 84 |
| Book equity today | 95 |
| PV of 5 years of excess return | (43) |
| PV of the terminal excess return, 5% flat | (160) |
| add non-operating investments | 0 |
| Equity value | (108) |
| ÷ 1.20 crore shares | ₹(91) |
ROE is at or below the cost of equity, so every year destroys value against book and the model lands below book value. That is the arithmetic, not a view.
Where the methods land · ₹ per share · the dashed line is the CMP
52-week rangetraded range, a fact not a value
₹33₹59
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -2.5% | — | 9.25% | 5% | ₹(91) | (298.3)% |
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.