1758 (1758) Fair Value & Analysis
Consumer Defensive · Market cap HK$114M
Fair value as of: Jul 2, 2026
From 2 valuation models · updated today
Share price +30.2% over the past month.
Price vs Fair Value (12 months)
12‑month range HK$0.0660 – HK$0.1700 · fair‑value band HK$0.0400 – HK$0.0900 · the HK$0.1250 price screens above the HK$0.0600 fair value. As of Jul 2, 2026.
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1758 (1758) currently trades at HK$0.1250, while our model-based Fair Value estimate is HK$0.0600 — implying the stock looks roughly 52.0% overvalued today. We read business quality at 26/100 (below-average quality), in the Consumer Defensive sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).
Over the trailing twelve months, 1758 generated revenue of HK$352M at a net margin of -46.1%. Revenue declined 12.9% year over year. It earns a return on equity of -63.7%. Net debt stands at HK$1.8B. Fundamentals as of Jul 2, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 2, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2021 – FY2025 · reported fiscal years
1758 reported revenue of HK$375M in FY2025 versus HK$0 in FY2021. Reported net income was −HK$130M in FY2025.
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Similar stocks
6 more Education & Training Services stocks, each showing price versus our Fair Value estimate (as of Jul 2, 2026).
| Stock | Price | Fair Value | vs Fair Value |
|---|---|---|---|
| New Oriental Education & Technology Group EDUN | 966.48 MXN | 895.77 MXN | -7% |
| 9901 9901 | HK$36.30 | HK$4.84 | -87% |
| TAL Education Group T1AL34 | R$4.84 | R$0.5800 | -88% |
| Graham Holdings GHC | $1,147 | $1,170 | +2% |
| Laureate Education, Inc LAUR | $37.19 | $41.45 | +11% |
| Covista Inc CVSA | $119.28 | $137.46 | +15% |
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.