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Hongli Group (HLP) Fair Value & Analysis

Basic Materials · US · Market cap $32.8M

Price$0.4470
Fair Value$0.3300
Upside-26.2%
Quality95/100
Evidence: High Range $0.2700 – $0.4600

Fair value as of: Jun 24, 2026

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Analysis

Hongli Group (HLP) currently trades at $0.4470, while our model-based Fair Value estimate is $0.3300 — implying the stock looks roughly 26.2% overvalued today. We read business quality at 95/100 (high quality), in the Basic Materials 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

Hongli Group Inc., together with its subsidiaries, manufactures and sells customized steel profiles in the People's Republic of China and internationally. It provides cold roll formed steel profile products in various forms and shapes, such as angles, bows, beams, brackets, channels, cross-members, flanges, hats, panels, plates, posts, rails, stakes, and tracks. The company serves mining and excavation, construction, agriculture, and transportation industries. Hongli Group Inc. was incorporated in 2021 and is headquartered in Weifang, the People's Republic of China. Hongli Group Inc. operates as a subsidiary of Hongli Development Limited.

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Frequently asked questions

Is Hongli Group (HLP) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.3300 versus a price of $0.4470 — about −26% (overvalued). Model-based estimate, not financial advice.
What is the fair value of HLP?
Our 21-model fair value for Hongli Group is $0.3300 (as of Jun 24, 2026), built from audited fundamentals. The current price is $0.4470.
What is the quality score of HLP?
Hongli Group 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.