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Xizang Tianlu Co (600326) Fair Value & Analysis

Industrials · CN · Market cap 9.8B CNY

Price¥7.09
Fair Value¥4.97
Upside-29.9%
Quality80/100
Evidence: Medium Range ¥3.34 – ¥7.09

Analysis

Xizang Tianlu Co (600326) currently trades at ¥7.09, while our model-based Fair Value estimate is ¥4.97 — implying the stock looks roughly 29.9% overvalued today. We read business quality at 80/100 (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: medium).

About the company

Xizang Tianlu Co., Ltd. engages in general contracting business in China. It is involved in the general contracting of highway engineering construction, building, municipal public, railway engineering, power engineering, electromechanical engineering, and water conservancy and hydropower engineering construction works; professional contracting of bridge engineering, highway pavement construction, and road subgrade engineering works; and engineering contracting activities. The company also engages in the production and sales of cement, concrete, sand, gravel, aggregates, and ores; research and development, production, wholesale, retail, and sales of building materials; exploration, mining, processing, and sale of mineral resources; processing and sale of asphalt mixture; construction labor services; photovoltaic power generation; and financial leasing. Xizang Tianlu Co., Ltd. was founded in 1999 and is based in Lhasa, China.

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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.