ClearSign Technologies Corporation (CLIR) Fair Value & Analysis
Industrials · US · Market cap $23.5M
Fair value as of: Jun 24, 2026
Analysis
ClearSign Technologies Corporation (CLIR) currently trades at $3.71, while our model-based Fair Value estimate is $4.62 — implying the stock looks roughly 24.5% undervalued today. We read business quality at 95/100 (high quality), in the Industrials sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: low) — always confirm before acting.
About the company
ClearSign Technologies Corporation designs and develops products and technologies for the purpose of decarbonization and improving key performance characteristics of industrial and commercial systems in the United States and the People's Republic of China. The company's technologies include ClearSign core burner technology consists of an industrial burner body and a downstream porous ceramic or metal flame stabilizing structure; ClearSign core process burner technology that provides a direct burner replacement for traditional refinery process heaters; ClearSign core boiler burner technology; ClearSign core flaring burners that can be used to provide a flare product with extremely low nitrogen oxide emissions; and ClearSign eye flame sensor, an electrical flame sensor for industrial applications. It serves energy, institutional, commercial and industrial boiler, chemical, and petrochemical industries. ClearSign Technologies Corporation was formerly known as ClearSign Combustion Corpo…
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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.