Tongdao Liepin Group (TGDLF) Fair Value & Analysis
Industrials · US · Market cap $222M
Fair value as of: Jun 25, 2026
Analysis
Tongdao Liepin Group (TGDLF) currently trades at $0.4833, while our model-based Fair Value estimate is $0.6700 — implying the stock looks roughly 38.6% undervalued today. We read business quality at 89/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.
About the company
Tongdao Liepin Group, an investment holding company, provides talent acquisition services in the People's Republic of China. The company offers acquisition services, proprietary online platform, and SaaS solutions, and to registered individual users, business users and headhunters over the internet; AI technology and big data analytics; mobile app, website, branded WeChat official account and mini program; talent development services to individual users; other human resources services; and AI interviewing and assessment, as well as other HR services and advertising services. It serves advertising service providers, headhunters and other talent service providers, and server hosting and bandwidth providers. The company was formerly known as Wise Talent Information Technology Co., Ltd. and changed its name to Tongdao Liepin Group in July 2020. Tongdao Liepin Group was incorporated in 2018 and is headquartered in Beijing, the People's Republic of 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.