Orion Energy Systems, Inc (OESX) Fair Value & Analysis
Industrials · US · Market cap $39.8M
Fair value as of: Jun 25, 2026
Analysis
Orion Energy Systems, Inc (OESX) currently trades at $9.57, while our model-based Fair Value estimate is $13.45 — implying the stock looks roughly 40.6% undervalued today. We read business quality at 97/100 (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
Orion Energy Systems, Inc., together with its subsidiaries, research, designs, develops, manufactures, markets, sells, installs, and implements energy management systems for commercial office and retail, area lighting, industrial applications, and government in North America and Germany. It operates through three segments: Lighting, Maintenance, and Electric Vehicle (EV). The company offers light emitting diode LED lighting products; construction and engineering services for commercial lighting and energy management system; lighting and electrical system maintenance, repair, and replacement services; and EV charging station and turnkey installation solutions. It also provides LED high bay fixtures and LED troffer retrofits; smart lighting controls, a wireless Internet of Things enabled control solution that provides lighting control options and data intelligence capabilities for building managers; and various LED fixtures for lighting and energy management needs comprising fixtures …
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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.