Guangdong Lvtong New Energy Electric Vehicle Technology Co (301322) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 7.9B CNY
Analysis
Guangdong Lvtong New Energy Electric Vehicle Technology Co (301322) currently trades at ¥57.41, while our model-based Fair Value estimate is ¥8.52 — implying the stock looks roughly 85.2% overvalued today. We read business quality at 87/100 (high quality), in the Consumer Cyclical 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
Guangdong Lvtong New Energy Electric Vehicle Technology Co., Ltd. engages in the research and development, production, and sale of electric field vehicles under the LVTONG brand name in China. The company provides electric sightseeing vehicles, golf sightseeing vehicles, electric antique vehicles, electric patrol vehicles, electric vintage cars, electric freight vehicles, electric special vehicles, commercial floor scrubbers, and commercial sweepers for use in scenic spots, golf courses, factories, residential buildings, universities, hotels, police patrols, freight transportation, and large supermarkets. It also offers after-sales services. The company also exports its products to the European Union, the United States, Canada, Russia, Japan, and South Korea. Guangdong Lvtong New Energy Electric Vehicle Technology Co., Ltd. was founded in 2004 and is headquartered in Dongguan, 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.