Guangzhou Tongda Auto Electric Co (603390) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 4.1B CNY
Analysis
Guangzhou Tongda Auto Electric Co (603390) currently trades at ¥11.67, while our model-based Fair Value estimate is ¥5.18 — implying the stock looks roughly 55.6% 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: high).
About the company
Guangzhou Tongda Auto Electric Co., Ltd engages in the smart transportation and mobile medical care business in China. It offers Smart Transportation, a one-stop solution for smart transportation software and hardware for commercial vehicle manufacturers and operators, and Tongda Cloud, a smart traffic management cloud platform. The company also provides an intelligent dispatching management platform, a tire full life cycle management platform, an internet of vehicles safety warning cloud platform, the TDMS video management system, a passenger flow analysis and simulation platform, an intelligent cashier management cloud platform, and other vehicle management solutions, as well as mobile medical vehicles. In addition, it offers automotive electrical products, including vehicle-mounted intelligent systems, public transportation multimedia information release systems, and new energy vehicle motors and thermal management. The company was incorporated in 1994 and is headquartered in Gua…
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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.