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Bajaj Housing Finance Limited (BAJAJHFL) Fair Value & Analysis

Financial Services · IN · Market cap ₹701B

Price₹87.63
Fair Value₹56.65
Upside-35.4%
Quality97/100
Evidence: High Range ₹46.11 – ₹76.85

Analysis

Bajaj Housing Finance Limited (BAJAJHFL) currently trades at ₹87.63, while our model-based Fair Value estimate is ₹56.65 — implying the stock looks roughly 35.4% overvalued today. We read business quality at 97/100 (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

Bajaj Housing Finance Limited provides housing finance services in India. It offers finance to individuals and corporate entities for the purchase and renovation of homes or commercial spaces. The company also provides loans against property for business or personal needs, as well as working capital for business expansion purposes. In addition, it offers finance to developers engaged in the construction of residential and commercial properties, as well as lease rental discounting to developers and high-net-worth individuals; real estate investment trusts REITs, and sovereign wealth funds and corporations. Bajaj Housing Finance Limited was formerly known as Bajaj Financial Solutions Limited and changed its name to Bajaj Housing Finance Limited in November 2014. The company was incorporated in 2008 and is headquartered in Pune, India. Bajaj Housing Finance Limited operates as a subsidiary of Bajaj Finance Limited.

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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.