Fairvalue-Calculator Fairvalue-Calculator
EN DE

Zhejiang Langdi Group (603726) Fair Value & Analysis

Industrials · CN · Market cap 4.7B CNY

Price¥28.53
Fair Value¥16.68
Upside-41.5%
Quality95/100
Evidence: High Range ¥10.94 – ¥20.97

Analysis

Zhejiang Langdi Group (603726) currently trades at ¥28.53, while our model-based Fair Value estimate is ¥16.68 — implying the stock looks roughly 41.5% 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

Zhejiang Langdi Group Co., Ltd. researches, develops, manufactures, and sells household air conditioning wheels, mechanical fans, and polymer composite materials in China and internationally. It offers forward direct driven, forward and backward belt driven, axial-flow, single inlet forward and backward, FCU, and other fans; metal impeller; fan motors, such as external DC and EC motor, single phase capacitor motor, and triple phase induction motor; and air conditioning filters; cross-flow and axial flow wheels, centrifugal wheels, and FCU wheels, and spare parts for impellers; and polymer composites, including polypropylene modified material, ASA modified alloy material, PC modified alloy material, PA modified material, ABS modified material. Zhejiang Langdi Group Co., Ltd. was incorporated in 1998 and is headquartered in Yuyao, China.

Open the full interactive analysis →

Similar stocks

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.