Models
Srestha Finvest LimitedBSE 539217Finance
₹-1per 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)implied P/B (0.61)× on FY26 book
Against CMP ₹0.26−318.5%close of 2026-09-10
Cost of equity13.41%risk-free + beta × equity risk premium
Book equity, FY26₹1per share · excess returns add ₹(2)
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 | 164 | 156 | 149 | 142 | 136 |
| Net income at -4.6% ROE | (8) | (7) | (7) | (7) | (6) |
| Cost of equity charge at 13.41% | (22) | (21) | (20) | (19) | (18) |
| Excess return | (30) | (28) | (27) | (26) | (24) |
| Present value | (28) | (23) | (20) | (17) | (14) |
| Closing book equity | 156 | 149 | 142 | 136 | 130 |
| Book equity today | 164 |
| PV of 5 years of excess return | (101) |
| PV of the terminal excess return, 5% flat | (163) |
| add non-operating investments | 0 |
| Equity value | (100) |
| ÷ 175.75 crore shares | ₹(1) |
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
₹0₹0
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -4.6% | — | 13.41% | 5% | ₹(1) | (318.5)% |
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.