Autocount Dotcom Berhad, a software development company, (0276) Fair Value & Analysis
Technology · MY · Market cap 352M MYR
Fair value as of: Jun 24, 2026
Analysis
Autocount Dotcom Berhad, a software development company, (0276) currently trades at 0.5850 MYR, while our model-based Fair Value estimate is 1.02 MYR — implying the stock looks roughly 74.4% undervalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
Autocount Dotcom Berhad, a software development company, develops and distributes financial management software under the AutoCount brand in Malaysia, Singapore, and internationally. The company's software solutions include AutoCount Accounting, Point of Sale, Cloud Accounting, Cloud Payroll, and OneSales. It also engages in the development and wholesale of computer hardware, and software and peripherals, as well as trading of software; and development of other software and programming activities. In addition, the company provides technical support and maintenance services, as well as offers software-related services. It serves small and medium enterprises, accounting firms, and corporate clients across various industries. The company sells its products through a network of authorized dealers, and internal sales and marketing team. Autocount Dotcom Berhad was founded in 1996 and is headquartered in Petaling Jaya, Malaysia.
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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.