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ESIP (ESIP) Fair Value & Analysis

Consumer Cyclical · ID · Market cap 102B IDR

Price141.00 IDR
Fair Value22.03 IDR
Upside-84.4%
Quality95/100
Evidence: High Range 16.52 IDR – 27.54 IDR

Fair value as of: Jun 24, 2026

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Analysis

ESIP (ESIP) currently trades at 141.00 IDR, while our model-based Fair Value estimate is 22.03 IDR — implying the stock looks roughly 84.4% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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 Sinergi Inti Plastindo Tbk produces and distributes plastic packaging products in Indonesia. It offers high density polyethylene; low density polyethylene / low linear density polyethylene, including plastic and courier bags; PVC cling wrap; and degradable sealed bags. The company was founded in 2001 and is headquartered in Jakarta Selatan, Indonesia.

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Frequently asked questions

Is ESIP (ESIP) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 22.03 IDR versus a price of 141.00 IDR — about −84% (overvalued). Model-based estimate, not financial advice.
What is the fair value of ESIP?
Our 21-model fair value for ESIP is 22.03 IDR (as of Jun 24, 2026), built from audited fundamentals. The current price is 141.00 IDR.
What is the quality score of ESIP?
ESIP 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.