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FarGlory Hotel Co (2712) Fair Value & Analysis

Consumer Cyclical · TW · Market cap 1.6B TWD

Price15.05 TWD
Fair Value3.58 TWD
Upside-76.2%
Quality95/100
Evidence: Medium Range 1.66 TWD – 5.51 TWD

Fair value as of: Jun 25, 2026

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Analysis

FarGlory Hotel Co (2712) currently trades at 15.05 TWD, while our model-based Fair Value estimate is 3.58 TWD — implying the stock looks roughly 76.2% 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: medium).

About the company

FarGlory Hotel Co.,Ltd engages in the operation of hotel under the Farglory Hotel name in Taiwan. The company provides rooms, dining, weddings, meetings and events, and facilities, including leisure, outdoor pool, spa, and stores. It also operates restaurants. The company was founded in 1980 and is based in Hualien City, Taiwan.

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Frequently asked questions

Is FarGlory Hotel Co (2712) undervalued?
As of Jun 25, 2026, our model estimates a fair value of 3.58 TWD versus a price of 15.05 TWD — about −76% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 2712?
Our 21-model fair value for FarGlory Hotel Co is 3.58 TWD (as of Jun 25, 2026), built from audited fundamentals. The current price is 15.05 TWD.
What is the quality score of 2712?
FarGlory Hotel Co has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.