Models
Naperol Investments LimitedBSE 500298Finance
₹-58per 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₹(58)implied P/B (0.04)× on FY23 book
Against CMP ₹654.75−108.9%close of 2026-09-10
Cost of equity13.34%risk-free + beta × equity risk premium
Book equity, FY23₹1,583per share · excess returns add ₹(1,642)
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 | FY24 | FY25 | FY26 | FY27 | FY28 |
|---|---|---|---|---|---|
| Opening book equity | 910 | 950 | 991 | 1,035 | 1,080 |
| Net income at 4.7% ROE | 43 | 45 | 47 | 49 | 51 |
| Cost of equity charge at 13.34% | (121) | (127) | (132) | (138) | (144) |
| Excess return | (79) | (82) | (86) | (89) | (93) |
| Present value | (74) | (68) | (63) | (58) | (53) |
| Closing book equity | 950 | 991 | 1,035 | 1,080 | 1,128 |
| Book equity today | 910 |
| PV of 5 years of excess return | (315) |
| PV of the terminal excess return, 5% flat | (628) |
| add non-operating investments | 0 |
| Equity value | (34) |
| ÷ 0.57 crore shares | ₹(58) |
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
₹490₹990
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE 4.7% | — | 13.34% | 5% | ₹(58) | (108.9)% |
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.