Models
NECTAR LIFESCIENCES LTD.NECLIFE
₹-10per 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₹(10)implied P/B (0.33)× on FY26 book
Against CMP ₹10.86−190.2%close of 2026-09-20
Cost of equity12.83%risk-free + beta × equity risk premium
Book equity, FY26₹30per share · excess returns add ₹(40)
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 | 582 | 289 | 144 | 71 | 36 |
| Net income at -50.3% ROE | (293) | (145) | (72) | (36) | (18) |
| Cost of equity charge at 12.83% | (75) | (37) | (18) | (9) | (5) |
| Excess return | (367) | (183) | (91) | (45) | (22) |
| Present value | (346) | (152) | (67) | (30) | (13) |
| Closing book equity | 289 | 144 | 71 | 36 | 18 |
| Book equity today | 582 |
| PV of 5 years of excess return | (608) |
| PV of the terminal excess return, 5% flat | (164) |
| add non-operating investments | 0 |
| Equity value | (190) |
| ÷ 19.43 crore shares | ₹(10) |
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
₹9₹22
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -50.3% | — | 12.83% | 5% | ₹(10) | (190.2)% |
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.