Models
LERTHAI FINANCE LIMITEDBSE 502250Other Construction Materials
₹-863per 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₹(863)implied P/B (6.04)× on FY26 book
Against CMP ₹407.05−312.0%close of 2026-09-10
Cost of equity6.03%risk-free + beta × equity risk premium
Book equity, FY26₹143per share · excess returns add ₹(1,006)
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 | 10 | 10 | 9 | 9 | 8 |
| Net income at -4.4% ROE | (0) | (0) | (0) | (0) | (0) |
| Cost of equity charge at 6.03% | (1) | (1) | (1) | (1) | (1) |
| Excess return | (1) | (1) | (1) | (1) | (1) |
| Present value | (1) | (1) | (1) | (1) | (1) |
| Closing book equity | 10 | 9 | 9 | 8 | 8 |
| Book equity today | 10 |
| PV of 5 years of excess return | (4) |
| PV of the terminal excess return, 5% flat | (66) |
| add non-operating investments | 0 |
| Equity value | (60) |
| ÷ 0.07 crore shares | ₹(863) |
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
₹409₹774
Scenarios side by side · ₹ per share
| Scenario | Template | Growth | Margin | Rate | Terminal | ₹ / share | vs CMP |
|---|---|---|---|---|---|---|---|
| Base · editing | Excess return | ROE -4.4% | — | 6.03% | 5% | ₹(863) | (312.0)% |
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.