Shenzhen Friendcom Technology Co (300514) Fair Value & Analysis
Technology · CN · Market cap 2.1B CNY
Fair value as of: Jun 24, 2026
Analysis
Shenzhen Friendcom Technology Co (300514) currently trades at ¥9.98, while our model-based Fair Value estimate is ¥7.00 — implying the stock looks roughly 29.9% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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
Shenzhen Friendcom Technology Co., Ltd. provides internet of things (IoT) solutions in China. The company offers wireless communication products, including outdoor and indoor gateway, external pulse acquisition and wireless data transmission terminal, and RF module; wireless M-bus modules; data radio series; point to point transmission module series; L-CellMesh series; 4G LTE series; and NB-IoT series. It also provides single and three phase payment control smart energy meter, three phase three wire/four wire smart energy meter, single and three phase electronic payment control smart energy meter, and three-phase three-wire/four-wire multifunction smart energy meter; smart gas meter, smart camera direct reading wireless meter reader, and smart ultrasonic gas meter; and inductive water, photo-diode direct read water, ultrasonic water, and IC card wireless smart water meter. In addition, the company offers power consumption information collection, including communication unit and term…
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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.