FULONGMA GROUP Co (603686) Fair Value & Analysis
Industrials · CN · Market cap 6.0B CNY
Analysis
FULONGMA GROUP Co (603686) currently trades at ¥14.10, while our model-based Fair Value estimate is ¥13.74 — implying the stock looks roughly 2.6% overvalued today. We read business quality at 87/100 (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
FULONGMA GROUP Co.,Ltd., together with its subsidiaries, manufactures and sells sanitation equipment under the FULONGMA brand in China and internationally. It operates through Environmental Industry Ecological Operation; Smart Equipment; and Others segments. The company offers road cleaning equipment, such as pavement maintaining trucks, road guardrail cleanout vehicles, clear wall tankers, suction-type sewer scavengers, sewer dredging and cleaning vehicles, multi-functional dust suppression trucks, high-pressure and street sprinklers, cleaning sweeper trucks, dirty-suction vehicles, and sweeper trucks. It also provides garbage transfer equipment, including compression refuse collectors, dock with self-discharging garbage trucks, movable refuse compactors, detachable container garbage collectors, self-loading garbage trucks, sealed garbage bin carriers, waste crushing trucks, and kitchen garbage trucks. In addition, the company offers waste disposal equipment comprising water treatm…
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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.