Choice International Limited (CHOICEIN) Fair Value & Analysis
Financial Services · IN · Market cap ₹161B
Fair value as of: Jun 29, 2026
Analysis
Choice International Limited (CHOICEIN) currently trades at ₹723.85, while our model-based Fair Value estimate is ₹105.04 — implying the stock looks roughly 85.5% overvalued today. We read business quality at 90/100 (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
Choice International Limited, together with its subsidiaries, provides various financial services in India. It operates through Broking & Distribution Services, Advisory Services, and NBFC Services segments. The company offers equity broking; wealth management, such as asset allocation, risk management, investment products, and estate planning; health, life, commercial, and vehicle insurance; solar, business, and vehicle loans, as well as loans against securities; and corporate advisory services, including investment and merchant banking, corporate finance, and IPO readiness services. It also provides business and transaction advisory; taxation; governance, risk, and compliance; corporate services; and research and survey, bid process management, policy formation and advisory, and monitoring and evaluation services. In addition, the company offers direct, indirect, and international taxation services; insurance and mutual fund distribution; and management consulting services, as wel…
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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.