GuanHua Corporation (GHGH) Fair Value & Analysis
Financial Services · US · Market cap $36.3K
Fair value as of: Jun 26, 2026
Analysis
GuanHua Corporation (GHGH) currently trades at $0.1200, while our model-based Fair Value estimate is $0.1500 — implying the stock looks roughly 25.0% undervalued today. We read business quality at 89/100 (high quality), in the Financial Services 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
GuanHua Corporation, a holding company, operates in the telecommunications and real estate sectors. The company offers next generation communication solutions and produces various kinds of terminals and platforms, such as handheld computing equipment; multiple automatic diagnostic strip reader for woman's hormone test, cardiac test, and tumor test; video on demand solutions; DWDM-PON solutions; and DWDM tunable transceiver modules. It also engages in the investment, buying, development, construction, operation, marketing, and sale of real estate. The company primarily focuses on distressed real estate and raw land development, including development of raw land into multi-family housing, retail centers, offices, and industrial facilities. In addition, it provides EB-5 immigrant investor visa program, which is a permanent U.S. visa based upon an immigrant investment that creates American employment. The company was formerly known as AuGRID Global Holdings Corporation and changed its n…
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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.