Transcat, Inc (TRNS) Fair Value & Analysis
Industrials · US · Market cap $836M
Analysis
Transcat, Inc (TRNS) currently trades at $89.46, while our model-based Fair Value estimate is $12.09 — implying the stock looks roughly 86.5% overvalued today. We read business quality at 97/100 (high quality), in the Industrials 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
Transcat, Inc. provides calibration and laboratory instrument services in the United States, Canada, and internationally. The company operates through two segments: Service and Distribution. The Service segment offers calibration, repair, inspection, analytical qualification, preventative maintenance, consulting, and other related services. This segment also provides CalTrak, a proprietary document and asset management system that is used to manage the workflow of its calibration service centers and customers' assets; and Compliance, Control, and Cost, an online customer portal that provides its customers with web-based asset management capability, as well as a safe and secure off-site archive of calibration and other service records. The Distribution segment sells and rents test, measurement, and control instruments for customers' test and measurement instrumentation needs, as well as value-added services, such as calibration/certification of equipment purchase, equipment rental, u…
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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.