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Valvoline Inc (VVV) Fair Value & Analysis

Consumer Cyclical · US · Market cap $4.3B

Price$38.32
Fair Value$24.57
Upside-35.9%
Quality95/100
Evidence: High Range $14.27 – $31.95

Fair value as of: Jun 24, 2026

Analysis

Valvoline Inc (VVV) currently trades at $38.32, while our model-based Fair Value estimate is $24.57 — implying the stock looks roughly 35.9% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

Valvoline Inc. provides automotive preventive maintenance through its retail stores in the United States and Canada. The company offers oil changes; battery, bulb, and wiper replacements; tire rotations; and other maintenance services. It also operates and franchises service centers and retail locations. The company was founded in 1866 and is headquartered in Lexington, Kentucky.

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Frequently asked questions

Is Valvoline Inc (VVV) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $24.57 versus a price of $38.32 — about −36% (overvalued). Model-based estimate, not financial advice.
What is the fair value of VVV?
Our 21-model fair value for Valvoline Inc is $24.57 (as of Jun 24, 2026), built from audited fundamentals. The current price is $38.32.
What is the quality score of VVV?
Valvoline Inc has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.