Models
VAPI ENTERPRISE LIMITEDBSE 502589Paper, Forest & Jute Products
₹-1,014per 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₹(1,014)implied P/B (6.25)× on FY26 book
Against CMP ₹124.65−913.5%close of 2026-09-10
Cost of equity5.15%risk-free + beta × equity risk premium
Book equity, FY26₹162per share · excess returns add ₹(1,176)
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 | 37 | 38 | 40 | 42 | 43 |
| Net income at 4% ROE | 1 | 2 | 2 | 2 | 2 |
| Cost of equity charge at 5.15% | (2) | (2) | (2) | (2) | (2) |
| Excess return | (0) | (0) | (0) | (0) | (0) |
| Present value | (0) | (0) | (0) | (0) | (0) |
| Closing book equity | 38 | 40 | 42 | 43 | 45 |
| Book equity today | 37 |
| PV of 5 years of excess return | (2) |
| PV of the terminal excess return, 5% flat | (266) |
| add non-operating investments | 0 |
| Equity value | (231) |
| ÷ 0.23 crore shares | ₹(1,014) |
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
₹90₹173
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE 4% | — | 5.15% | 5% | ₹(1,014) | (913.5)% |
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.