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PT Sarana Mitra Luas Tbk (SMIL) Fair Value & Analysis

Industrials · ID · Market cap 2.1T IDR

Price280.00 IDR
Fair Value127.03 IDR
Upside-54.6%
Quality95/100
Evidence: High Range 88.92 IDR – 165.14 IDR

Fair value as of: Jun 24, 2026

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Analysis

PT Sarana Mitra Luas Tbk (SMIL) currently trades at 280.00 IDR, while our model-based Fair Value estimate is 127.03 IDR — implying the stock looks roughly 54.6% 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

PT Sarana Mitra Luas Tbk operates as a forklift rental company in Indonesia. It offers material handling equipment, such as engine counterbalance forklifts, electric counterbalance forklifts, reach trucks, warehouse equipment, loaders, and forklift attachments, as well as BSLBATT forklift lithium batteries and chargers. The company also provides material handling solutions, including rental units and operators, output-based rental, machine installation, and forklift sales and repair. PT Sarana Mitra Luas Tbk was founded in 1996 and is headquartered in Bekasi, Indonesia.

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Frequently asked questions

Is PT Sarana Mitra Luas Tbk (SMIL) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 127.03 IDR versus a price of 280.00 IDR — about −55% (overvalued). Model-based estimate, not financial advice.
What is the fair value of SMIL?
Our 21-model fair value for PT Sarana Mitra Luas Tbk is 127.03 IDR (as of Jun 24, 2026), built from audited fundamentals. The current price is 280.00 IDR.
What is the quality score of SMIL?
PT Sarana Mitra Luas Tbk has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.