Martin Midstream Partners L.P., (MMLP) Fair Value & Analysis
Energy · US · Market cap $93.5M
Fair value as of: Jun 24, 2026
Analysis
Martin Midstream Partners L.P., (MMLP) currently trades at $2.18, while our model-based Fair Value estimate is $1.13 — implying the stock looks roughly 48.2% overvalued today. We read business quality at 95/100 (high quality), in the Energy 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
Martin Midstream Partners L.P., together with its subsidiaries, provides terminalling, processing, and storage services for petroleum products and by-products in the United States. It operates through four segments: Terminalling and Storage, Transportation, Sulfur Services, and Specialty Products. The company owns or operates various marine shore-based terminal facilities and specialty terminal facilities, as well as naphthenic lubricants refinery; and offers storage, refining, and handling services for producers and suppliers of petroleum products, handling services for molten sulfur and asphalt, land rental services to oil and gas companies, and storage and handling services for lubricants and fuels. It also engages in the operation of land and marine transportation assets that transport petroleum products and by-products, petrochemicals, and chemicals; and provides refinery and petrochemical services, including transportation of heavy tank bottoms by-products and other petroleum …
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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.