Xiangyang Automobile Bearing Co (000678) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 4.5B CNY
Fair value as of: Jun 25, 2026
Analysis
Xiangyang Automobile Bearing Co (000678) currently trades at ¥8.97, while our model-based Fair Value estimate is ¥6.85 — implying the stock looks roughly 23.6% overvalued today. We read business quality at 95/100 (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: low).
About the company
Xiangyang Automobile Bearing Co., Ltd. researches, develops, manufactures, and sells automobile bearings in China. The company provides ball, TRB, CRB, NRB, CHB, CVJ, CJ, and other bearings. It also offers various bearing products in the areas of machinery, agricultural machinery, household appliances, wind power, etc. The company's products are used in heavy-duty, medium-duty, light-duty, and mini-duty trucks, as well as cars. It also exports its products to Europe, the United States, Southeast Asia, and other countries and regions. In addition, the company engages in automotive and machinery manufacturing, as well as investment business. Xiangyang Automobile Bearing Co., Ltd. was founded in 1968 and is headquartered in Xiangyang, China.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is Xiangyang Automobile Bearing Co (000678) undervalued?
What is the fair value of 000678?
What is the quality score of 000678?
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.