PT Shield On Service Tbk, (SOSS) Fair Value & Analysis
Industrials · ID · Market cap 755B IDR
Fair value as of: Jun 24, 2026
Analysis
PT Shield On Service Tbk, (SOSS) currently trades at 775.00 IDR, while our model-based Fair Value estimate is 344.37 IDR — implying the stock looks roughly 55.6% overvalued today. We read business quality at 86/100 (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: medium).
About the company
PT Shield On Service Tbk, together with its subsidiaries, provides outsourcing services in Indonesia. It operates through Security Services, Human Resource Provider Services, Cleaning Services, Parking Management Services, and Other segments. The company offers security services, including security and guarding, certified security training, security consulting, and digital patrol services; outsourcing cleaning services comprising daily and general cleaning, high-rise cleaning, garden maintenance, and pest control services; and workforce outsourcing solutions, such as recruitment assessment, labor supply, payroll, and output-based services. It also provides automatic parking systems and services, including valet parking, parking management, cashless payment, technology parking equipment, and valet parking services, as well as security system solutions comprising CCTV and video surveillance systems, access control systems, fire and alarm systems, automated external defibrillators, and…
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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.