Models
CUPID BREWERIES AND DISTILLERIBSE 512361Beverages
₹-44per 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₹(44)implied P/B (0.58)× on FY26 book
Against CMP ₹24.17−282.1%close of 6 Nov 2026
Cost of equity11.29%risk-free + beta × equity risk premium
Book equity, FY26₹76per share · excess returns add ₹(120)
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 | 691 | 688 | 684 | 681 | 677 |
| Net income at -0.5% ROE | (3) | (3) | (3) | (3) | (3) |
| Cost of equity charge at 11.29% | (78) | (78) | (77) | (77) | (76) |
| Excess return | (81) | (81) | (81) | (80) | (80) |
| Present value | (77) | (69) | (62) | (55) | (49) |
| Closing book equity | 688 | 684 | 681 | 677 | 674 |
| Book equity today | 691 |
| PV of 5 years of excess return | (313) |
| PV of the terminal excess return, 5% flat | (780) |
| add non-operating investments | 0 |
| Equity value | (402) |
| ÷ 9.13 crore shares | ₹(44) |
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
₹19₹105
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -0.5% | — | 11.29% | 5% | ₹(44) | (282.1)% |
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.