JLT Mobile Computers AB (JLT) Fair Value & Analysis
Technology · SE · Market cap 54.6M SEK
Fair value as of: Jun 25, 2026
Analysis
JLT Mobile Computers AB (JLT) currently trades at kr 1.82, while our model-based Fair Value estimate is kr 3.24 — implying the stock looks roughly 78.0% undervalued today. We read business quality at 95/100 (high quality), in the Technology 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
JLT Mobile Computers AB (publ) produces and sells rugged computing solutions in the Nordic countries, the rest of Europe, the Middle East, Africa, Oceania, the Americas, and internationally. The company offers vehicle-mount computers; rugged tablets and handheld devices; accessories, such as barcode scanners, mounts, keyboards and stylus, antennas and antenna connectors, power supply and cables, and ingress protection and screen protectors; software solutions; and Winmate, which includes enterprise mobility, industrial panel PCs, and HMIs, and vehicle mounted computers. It provides customized rugged computers and custom-made devices, including antennas, cables and mounting, GPS boards and connectors, and CAN-bus. The company sells its products through a network of resellers and system integrators to various industries, including warehousing and distribution, agriculture, manufacturing, mining, ports, and transportation. JLT Mobile Computers AB (publ) was incorporated in 1984 and is …
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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.