Jolimark Holdings (JLMKF) Fair Value & Analysis
Technology · US · Market cap $66.2M
Fair value as of: Jun 26, 2026
Analysis
Jolimark Holdings (JLMKF) currently trades at $0.0900, while our model-based Fair Value estimate is $0.0720 — implying the stock looks roughly 20.0% overvalued today. We read business quality at 93/100 (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
Jolimark Holdings Limited, an investment holding company, manufactures and sells printers, and other electronic and non-electronic products in the People's Republic of China. It operates through Printers and Other Products segments. The company provides rolling and flatbed dot matrix, passbook, laser, and inkjet printers, including red letter-headed and smart finance e-office; and thermal and dot matrix POS solutions, POS terminals, projectors, and other electronic products. It also engages in software development, system integration and technology consulting; and computer system services, data processing, software applications and technology consulting; issuance of digitalized electronic invoices and collection of big data; cloud printing products; smart government services; medical care services; and services related to lottery industry, as well as wearable armor customization courses. In addition, the company provides cloud printing products, latte art machines, manicure machines…
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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.