Shenzhen Lions King Hi-Tech Co (301305) Fair Value & Analysis
Industrials · CN · Market cap 7.4B CNY
Analysis
Shenzhen Lions King Hi-Tech Co (301305) currently trades at ¥29.55, while our model-based Fair Value estimate is ¥12.99 — implying the stock looks roughly 56.0% overvalued today. We read business quality at 93/100 (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
Shenzhen Lions King Hi-Tech Co., Ltd engages in the investment, construction, and operation of biomass waste resource treatment projects in China and internationally. The company is involved in the biomass waste resource recycling business, including the treatment and resource utilization of urban biomass waste, such as catering and kitchen waste, and animal solid and domestic waste; and the production of various resource products comprising biodiesel, green electricity, and biogas. It also engages in property leasing, supply chain, investment, synthetic biology, medical research and experimental development, bioenergy, other electricity production, biotechnology extension, technology promotion and application, and energy storage activities. The company was formerly known as Shenzhen Leo-King Environmental Group Company Limited and changed its name to Shenzhen Lions King Hi-Tech Co., Ltd in November 2024. Shenzhen Lions King Hi-Tech Co., Ltd was incorporated in 2001 and is headquart…
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.