KJTS Group (0293) Fair Value & Analysis
Industrials · MY · Market cap 508M MYR
Fair value as of: Jun 24, 2026
Analysis
KJTS Group (0293) currently trades at 0.7550 MYR, while our model-based Fair Value estimate is 0.5500 MYR — implying the stock looks roughly 27.2% 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
KJTS Group Berhad provides integrated building support in Malaysia, Singapore, and Thailand. It operates through Cooling Energy; Cleaning Services; Facilities Management; and Investment segments. It engages in the provision of cooling energy management services, including energy audits; design, construction, operation, maintenance, retrofit, and upgrade of district cooling systems (DCS) and chiller plants, as well as engineering, procurement, construction, and commissioning of cooling energy systems; and supplies chilled water for space cooling. The company also provides cleaning and other ancillary services for buildings and outdoor areas. In addition, it offers static and mobile facilities management services; waste management services; and integrates software systems. The company provides data centres; education facilities; hospitality; healthcare and facilities; industrial and manufacturing; transport infrastructures; township and mixed development; and commercial and retail sec…
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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.