Tianfeng Securities Co (601162) Fair Value & Analysis
Financial Services · CN · Market cap 33.0B CNY
Analysis
Tianfeng Securities Co (601162) currently trades at ¥3.38, while our model-based Fair Value estimate is ¥1.76 — implying the stock looks roughly 47.9% overvalued today. We read business quality at 94/100 (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
Tianfeng Securities Co., Ltd. provides financial securities services in China. The company offers industry/listed company research, custom research consulting, and research findings presentation; equity and bond financing; investment consulting, financial product distribution, and margin trading; collective, targeted, and specialized asset management; and investment banks and security brokerage. It also provides equity propriety trading, bond trading, and RMB interest rate swap; PE/VC, and government-guided and venture capital funds; pre-IPO/direct equity investment/equity funds, and STAR market/growth enterprise market; and future brokerage, future asset management, and risk management. In addition, the company offers securities brokerage; securities investment consulting; financial advisory services related to securities trading and securities investment activities; agency sales of securities investment funds; securities underwriting and sponsorship; proprietary securities trading…
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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.