Landai Technology Group (002765) Fair Value & Analysis
Consumer Cyclical · CN · Market cap 5.3B CNY
Analysis
Landai Technology Group (002765) currently trades at ¥7.75, while our model-based Fair Value estimate is ¥6.14 — implying the stock looks roughly 20.8% 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
Landai Technology Group Corp., Ltd. engages in the research, development, production, and sales of automotive powertrain components, touchscreens, and touch display modules in China. The company provides manual transmission assembly, automatic transmission assembly, new energy transmission assembly, balancing box, balancing shaft. It offers transmission case/housing, such as lower shell, CVT housing, flywheel housing, and radiator cap; automobile engine gears, shafts, and other parts; textile machinery parts; tooth and shafts, including one-stage gear assembly, spindle 2, gear, secondary gear, internal gear, new energy intermediate shaft assembly, new energy motor shaft, main spindle three-speed, and AT gears; cover glasses, such as consumer laptop cover, commercial interactive cover plate, consumer laptop glass cover, industrial control instrument glass cover plate, car dual-screen glass cover, large-size 3d hot-bent glass, 2d glass cover plate, and automotive 3d hot-bent glass; an…
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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.