Bitmax Co (377030) Fair Value & Analysis
Technology · KR · Market cap 16.4B KRW
Fair value as of: Jun 24, 2026
Analysis
Bitmax Co (377030) currently trades at 1,300 KRW, while our model-based Fair Value estimate is 1,786 KRW — implying the stock looks roughly 37.4% 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
Bitmax Co., Ltd operates a metaverse platform in South Korea and internationally. It operates through Software Advisory, Development, and Supply; IT Services; and Game Content segments. The company offers BITMAX AR SKD, an augmented reality (AR) development platform that provides image tracker and cloud recognizers, instant and object trackers, space and marker trackers, QR code and AR fusion trackers, and QR/barcode readers; and Widearth, a digital twin platform based on real space, which includes workspace, studio, and viewer capabilities. It also provides industrial AR solutions comprising AR inspection and AR remote; digital twin solutions; and smart glasses. In addition, the company invests in Bitcoin. Further, it develops hack-and-slash role-playing games on PC and mobile. The company was formerly known as MAXST Co., Ltd. and changed its name to Bitmax Co., Ltd in February 2025. Bitmax Co., Ltd was founded in 2010 and is headquartered in Seoul, South Korea.
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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.