Hi Sun Technology (China) Limited (HISNF) Fair Value & Analysis
Technology · US · Market cap $52.9M
Fair value as of: Jun 26, 2026
Analysis
Hi Sun Technology (China) Limited (HISNF) currently trades at $0.0195, while our model-based Fair Value estimate is $0.0193 — implying the stock looks roughly 0.9% overvalued today. We read business quality at 89/100 (high quality), in the Technology 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).
About the company
Hi Sun Technology (China) Limited, an investment holding company, provides payment and digital services, fintech services, and platform operation and financial solutions in Hong Kong, Mainland China, and internationally. The company operates through four segments: Payment and Digital Services; Fintech Services; Platform Operation Solutions; Financial Solutions; and Others. The Payment and Digital Services segment offers payment processing, SAAS catering, and related digital products and solutions. Its Fintech Services segment provides supply chain financing, factoring business, credit assessment services and related products and solutions. The Platform Operation Solutions segment offers telecommunication and mobile payment platform operation services, as well as operation value-added services. Its Financial Solutions segment provides information system consultancy, integration, and operation services, as well as information technology products to financial institutions and banks. Th…
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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.