Progressive Impact Corporation (7201) Fair Value & Analysis
Industrials · MY · Market cap 29.5M MYR
Fair value as of: Jun 26, 2026
Analysis
Progressive Impact Corporation (7201) currently trades at 0.0700 MYR, while our model-based Fair Value estimate is 0.0560 MYR — implying the stock looks roughly 20.0% overvalued today. We read business quality at 95/100 (high 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: high).
About the company
Progressive Impact Corporation Berhad, an investment holding company, provides environmental consulting, monitoring equipment and systems integration, environmental data management and laboratory testing services, and wastewater treatment solutions. It offers environmental monitoring services, such as air quality management, continuous particulate monitoring, continuous and predictive emission monitoring systems, stack monitoring, water resource management, and ocean data monitoring services; and environmental data management, and GIS services. The company also provides analytical testing services, including soil, sediment, and solid waste testing; water testing; air and water quality sampling and testing; stack emission sampling and analysis; food testing; tribology; and minerals services; chemical testing services; and wastewater treatment and solutions, as well as engages in property investment activities. It offers its services to oil and gas, energy, petrochemicals, food manufa…
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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.