Range Impact, Inc (RNGE) Fair Value & Analysis
Basic Materials · US · Market cap $47.8M
Fair value as of: Jun 24, 2026
Analysis
Range Impact, Inc (RNGE) currently trades at $0.4500, while our model-based Fair Value estimate is $0.5400 — implying the stock looks roughly 20.0% undervalued today. We read business quality at 80/100 (high quality), in the Basic Materials 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: medium) — always confirm before acting.
About the company
Range Impact, Inc., together with its subsidiaries, develops and operates solutions focused on acquiring, reclaiming, and repurposing mine sites and undervalued land in economically disadvantaged communities, primarily throughout Appalachia. It operates through two segments: Range Land and Range Services. The Range Land segment acquires mine lands and repurposes them for non-fossil fuel uses, including commercial, industrial, residential, and recreational developments, with emphasis on power generation facilities, data centers, agricultural installations, and projects enhancing air, land, and waterways. The Range Services segment provides environmental and operational support services, such as reclamation, water treatment, and site security, to reclaim and repurpose company-owned mine land. Its services include grading, recontouring, revegetation, erosion control, water treatment using passive and active systems, including proprietary biochar water, and physical site security and ac…
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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.