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DONGBANG AGRO Corporation (007590) Fair Value & Analysis

Basic Materials · KR · Market cap 72.1B KRW

Price5,750 KRW
Fair Value13,361 KRW
Upside+132.4%
Quality95/100
Evidence: High Range 10,020 KRW – 16,701 KRW

Fair value as of: Jun 25, 2026

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Analysis

DONGBANG AGRO Corporation (007590) currently trades at 5,750 KRW, while our model-based Fair Value estimate is 13,361 KRW — implying the stock looks roughly 132.4% undervalued today. We read business quality at 95/100 (high quality), in the Basic Materials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.

About the company

DONGBANG AGRO Corporation engages in the production and sales of pesticides and fertilizers in South Korea. The company was founded in 1971 and is headquartered in Seoul, South Korea.

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Frequently asked questions

Is DONGBANG AGRO Corporation (007590) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 13,361 KRW versus a price of 5,750 KRW — about +132% (undervalued). Model-based estimate, not financial advice.
What is the fair value of 007590?
Our 21-model fair value for DONGBANG AGRO Corporation is 13,361 KRW (as of Jun 25, 2026), built from audited fundamentals. The current price is 5,750 KRW.
What is the quality score of 007590?
DONGBANG AGRO Corporation 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.