Willfar Information Technology Co (688100) Fair Value & Analysis
Industrials · CN · Market cap 15.3B CNY
Analysis
Willfar Information Technology Co (688100) currently trades at ¥31.66, while our model-based Fair Value estimate is ¥21.60 — implying the stock looks roughly 31.8% overvalued today. We read business quality at 95/100 (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
Willfar Information Technology Co., Ltd. provides smart utility services and IoT solutions in China and internationally. The company offers EV charging station, power monitoring, data concentrator unit, integrated power solutions, communication module, energy efficient management, head-end system, smart vending solutions, and intelligent street lighting. It also provides electricity, water, gas, and heat metering products; meters for power distribution; power quality monitoring equipment; energy data concentrators, relay protection equipment, switchgear products, and equipment related to metering automation system; and various application systems, as well as services, which cover the demand of the whole process of energy production, distribution, transmission, and consumption. Willfar Information Technology Co., Ltd. was founded in 2004 and is based in Changsha, China. Willfar Information Technology Co., Ltd. is a subsidiary of Wasion Holdings Limited.
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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.