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Shanghai Chinafortune Co (600621) Fair Value & Analysis

Financial Services · CN · Market cap 13.2B CNY

Price¥13.49
Fair Value¥10.19
Upside-24.5%
Quality95/100
Evidence: High Range ¥7.64 – ¥12.73

Analysis

Shanghai Chinafortune Co (600621) currently trades at ¥13.49, while our model-based Fair Value estimate is ¥10.19 — implying the stock looks roughly 24.5% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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: high).

About the company

Shanghai Chinafortune Co., Ltd., through its subsidiaries, engages in the securities business in China. The company is also involved in the securities and futures brokerage business, agency sales of financial products business, investment consulting business, investment transactions in securities and derivative financial instruments, collective and targeted asset management, and asset management business; securities sponsorship, underwriting, and financial advisory business; and margin trading, stock pledge repurchase, agreed repurchase securities, and equity investment businesses. Additionally, it issues securities research reports and develops trading systems for exchanges and financial institutions. The company was formerly known as Shanghai Jinling Co., Ltd. and changed its name to Shanghai Chinafortune Co., Ltd. in January 2013. Shanghai Chinafortune Co., Ltd. was founded in 1952 and is based in Shanghai, 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.