HL Corp (002105) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 2.0B CNY
Fair value as of: Jun 25, 2026
Analysis
HL Corp (002105) currently trades at ¥5.27, while our model-based Fair Value estimate is ¥8.79 — implying the stock looks roughly 66.8% undervalued today. We read business quality at 89/100 (high quality), in the Consumer Cyclical 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: low) — always confirm before acting.
About the company
HL Corp (Shenzhen) engages in the research and development, manufacture, and marketing of bicycle parts, sports and fitness equipment, and rehabilitation equipment in America, Europe, Asia, and internationally. The company provides bicycle parts, such as handlebars, stems, seat tubes, shock absorber front forks, disc brakes, etc. It also offers sports and fitness equipment, including electric scooter, 3-wheel scooters for kids, trikers, push bikes, 2 in 1 scooters, wingflyers, and kick scooters; and e-bikes, NOT, and mountain and trekking bikes. In addition, the company provides health-care equipment comprising wheelchairs, tri-walkers, rollators, cane products, overbed tables, and mobility scooters. Further, it offers seat post accessories and handlebars. The company offers its products under the ZOOM brand. It also exports its products. The company was founded in 1991 and is headquartered in Shenzhen, the People's Republic of China.
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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.