Konka Group (000016) Fair Value & Analysis
Technology · CN · Market cap 6.8B CNY
Analysis
Konka Group (000016) currently trades at ¥2.56, while our model-based Fair Value estimate is ¥7.39 — implying the stock looks roughly 188.7% undervalued today. We read business quality at 94/100 (high quality), in the Technology 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
Konka Group Co., Ltd., together with its subsidiaries, researches, develops, produces, and sells electronic products. The company offers refrigerators, washing machines, air conditioners, dishwashers, and freezers; semiconductors and memory chips; color TVs, white goods, optoelectronic displays, and storage and printed circuit boards; and micro LED-related products. It also provides housing leasing; enterprise management consulting and incubation management; sale of home appliance; industrial park development and operation management; research and experiment development; computer, telecommunications, and other electronic equipment manufacturing; electrical machinery and equipment manufacturing; real estate; trade and services; retail trade; wholesale of computers, software, and auxiliary equipment; capital market; utilization of renewable resources; and export and import of electronics, as well as manufactures household cleaning and sanitary electrical appliances. In addition, the c…
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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.