Raval ACS Ltd (RVL) Fair Value & Analysis
Consumer Cyclical · Il · Market cap 140M ILA
Fair value as of: Jun 24, 2026
Analysis
Raval ACS Ltd (RVL) currently trades at 1.54 ILA, while our model-based Fair Value estimate is 1.42 ILA — implying the stock looks roughly 7.8% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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
Raval ACS Ltd., together with its subsidiaries, designs, develops, manufactures, and sells plastic component systems and assemblies intended for installation in various vehicle systems in Israel, China, the United States, Canada, Germany, Luxembourg, Spain, rest of Europe, and internationally. It operates through Automotive Systems and Automotive Structural Products segments. The company offers advanced ADAS cleaning and clearing systems, which includes headlamp cleaners, camera LiDAR and sensor cleaners, washer valves, telescopic and camera nozzles, static nozzles, and integrated water and air nozzles; breather valves for battery packs, including burst breather valves and pressure release breather valves, as well as electric motor breathers for electric engines and gearbox units; and fuel tank valves and peripherals, pressurized fuel tank valves, integrated venting tubing systems, and selective catalytic reduction valves. It also provides valve line and detection valves, including …
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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.