Tesla, Inc (TSLA) Fair Value & Analysis
Consumer Cyclical · AR · Market cap 152T ARS
Analysis
Tesla, Inc (TSLA) currently trades at 39,580 ARS, while our model-based Fair Value estimate is 29,866 ARS — implying the stock looks roughly 24.5% overvalued today. We read business quality at 90/100 (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
Tesla, Inc. designs, develops, manufactures, leases, and sells electric vehicles, and energy generation and storage systems in the United States, China, and internationally. The company operates in two segments, Automotive; and Energy Generation and Storage. The company offers electric vehicles, as well as sells automotive regulatory credits; and non-warranty maintenance services and collision, automotive insurance services, as well as part sales and retail merchandise sale. It also provides sedans and sport utility vehicles through direct and used vehicle sales, a network of Tesla Superchargers, and in-app upgrades; purchase financing and leasing services; services for electric vehicles through its company-owned service locations and Tesla mobile service technicians; and vehicle limited warranties and extended service plans. In addition, the company engages in the design, manufacture, installation, sale, and leasing of solar energy generation and energy storage products, and relate…
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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.