Shunfa Hengneng Corporation (000631) Fair Value & Analysis
Real Estate · CN · Market cap 7.5B CNY
Fair value as of: Jun 25, 2026
Analysis
Shunfa Hengneng Corporation (000631) currently trades at ¥3.08, while our model-based Fair Value estimate is ¥2.49 — implying the stock looks roughly 19.2% overvalued today. We read business quality at 92/100 (high quality), in the Real Estate 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
Shunfa Hengneng Corporation engages in the real estate development and operation business. The company primarily develops residential real estate projects. It also engages in the natural gas power generation and on-grid sales; supporting mechanical and electrical equipment production and sales; and sale of hot water produced by waste heat, as well as power grid auxiliary service project development, operation, maintenance, and technical services. In addition, the company offers development and sales of real estate; property management business; canteen catering services; wind power generation, such as wind power, solar energy and other clean energy power generation business; and comprehensive smart energy services. The company was formerly known as Shunfa Hengye Corporation and changed its name to Shunfa Hengneng Corporation in July 2024. The company was founded in 1993 and is based in Zhangzhou, China. Shunfa Hengneng Corporation is a subsidiary of Wanxiang Group Corporation.
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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.