₹-38,14,783per share · Base Model Note
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₹(38,14,783)implied P/B (1201656.72)× on FY26 book
Against CMP ₹49.35−7730157.2%close of 19 Oct 2026
Cost of equity8.08%risk-free + beta × equity risk premium
Book equity, FY26₹3per share · excess returns add ₹(38,14,786)
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 | 1 | (9) | 73 | (618) | 5,267 |
| Net income at -951.9% ROE | (10) | 81 | (691) | 5,885 | (50,136) |
| Cost of equity charge at 8.08% | (0) | 1 | (6) | 50 | (425) |
| Excess return | (10) | 82 | (697) | 5,935 | (50,561) |
| Present value | (9) | 73 | (574) | 4,522 | (35,646) |
| Closing book equity | (9) | 73 | (618) | 5,267 | (44,869) |
| Book equity today | 1 |
| PV of 5 years of excess return | (31,634) |
| PV of the terminal excess return, 5% flat | (11,70,024) |
| add non-operating investments | 0 |
| Equity value | (12,01,657) |
| ÷ 0.32 crore shares | ₹(38,14,783) |
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
₹24₹65
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -951.9% | — | 8.08% | 5% | ₹(38,14,783) | (7730157.2)% |
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.