0365 (0365) Fair Value & Analysis
Industrials · Market cap HK$815M
Fair value as of: Jul 1, 2026
From 26 valuation models · updated today
Share price −47.2% over the past month.
Price vs Fair Value (12 months)
12‑month range HK$0.2300 – HK$1.28 · fair‑value band HK$0.1600 – HK$0.3500 · the HK$0.5600 price screens above the HK$0.2800 fair value. As of Jul 1, 2026.
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0365 (0365) currently trades at HK$0.5600, while our model-based Fair Value estimate is HK$0.2800 — implying the stock looks roughly 50.0% overvalued today. We read business quality at 71/100 (solid quality), in the Industrials 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: medium).
Over the trailing twelve months, 0365 generated revenue of HK$338M at a net margin of 5.7%. Revenue grew 53.4% year over year. It earns a return on equity of 9.3%. Net debt stands at HK$272M. Fundamentals as of Jul 1, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 1, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2021 – FY2025 · reported fiscal years
0365 reported revenue of HK$338M in FY2025 versus HK$323M in FY2021, a compound +1.1%/yr. Reported net income was HK$19.2M in FY2025, compounding −15.8%/yr from FY2021.
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Similar stocks
6 more Specialty Industrial Machinery stocks, each showing price versus our Fair Value estimate (as of Jul 1, 2026).
| Stock | Price | Fair Value | vs Fair Value |
|---|---|---|---|
| GE Vernova Inc GEV | $1,128 | $185.61 | -84% |
| SIEGY SIEGY | $155.06 | $89.54 | -42% |
| SMAWF SMAWF | $307.12 | $176.28 | -43% |
| SMNS SMNS | C$31.76 | C$22.85 | -28% |
| SIE SIE | €279.00 | €140.38 | -50% |
| Schneider Electric S.E. SBGSF | $334.00 | $148.44 | -56% |
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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.