Millennium Group (MGC) Fair Value & Analysis
Consumer Cyclical · TH · Market cap 7.0B THB
Fair value as of: Jun 25, 2026
Analysis
Millennium Group (MGC) currently trades at 6.75 THB, while our model-based Fair Value estimate is 19.60 THB — implying the stock looks roughly 190.4% undervalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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: high) — always confirm before acting.
About the company
Millennium Group Corporation (Asia) Public Company Limited, together with its subsidiaries, sells automobiles, yachts, and spare parts in Thailand. The company buys, sells, rents, and provides services for automotives under various brand names. It also offers after-sales services, including sale of automotive parts, accessories, body kits, and other products; paint and body repair services; and organizes events and roadshows, as well as long and short-term car rental and chauffeur services under the Sixt Rent a Car brand name. In addition, the company provides IT services, such as infrastructure and application installation and development; consultancy services related to IT; data services; customer contact services; data center services; training and development activities; and digital marketing services comprising marketing strategy planning, campaign development, and communication with external media buyers. Further, it is involved in management consulting services; sale and main…
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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.