Shinkong Insurance Co (2850) Fair Value & Analysis
Financial Services · TW · Market cap 46.9B TWD
Analysis
Shinkong Insurance Co (2850) currently trades at 141.00 TWD, while our model-based Fair Value estimate is 159.58 TWD — implying the stock looks roughly 13.2% undervalued today. We read business quality at 95/100 (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: high) — always confirm before acting.
About the company
Shinkong Insurance Co., Ltd. provides property insurance to individuals and corporates in Taiwan. It offers motor insurance, such as voluntary physical damage and automobile liability, and compulsory motor motorcycle liability; fire insurance, including residential fire, earthquake pool, commercial, typhoon, and flood; and marine insurance comprising marine cargo and hull, fishing vessel, aviation, commercial property floater, carriers liability, and forwarders liability. The company also provides engineering insurance, such as contractors and erection all risks, contractors plant and machinery, boiler pressure vessel, machinery breakdown, and electronic equipment insurance; liability insurance, including general and professional liability, bond, personal and commercial comprehensive, and miscellaneous; as well as group and individual personal accident insurance. Shinkong Insurance Co., Ltd. was incorporated in 1963 and is headquartered in Taipei, Taiwan.
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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.