Daesung Private Equity, Inc (027830) Fair Value & Analysis
Financials · KR · Market cap 62.6B KRW
Fair value as of: Jun 26, 2026
Analysis
Daesung Private Equity, Inc (027830) currently trades at 928.00 KRW, while our model-based Fair Value estimate is 102.13 KRW — implying the stock looks roughly 89.0% overvalued today. We read business quality at 95/100 (high quality), in the Financials 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
Daesung Private Equity, Inc. is a private equity and venture capital firm specializing in incubation and start-up to growth stages. It typically invests in venture companies. The firm also invests in corporate restructurings and secondary markets. It considers investments in the following sectors: biotechnology; broadcasting; clothing; cultural contents, including entertainment, such as movies, musicals, and Korean television series; digital television; display; electricity; electronics; environment and energy technology; food and beverage; fisheries and related sectors; information communication, such as telecommunications, and technology; machinery; nanotechnology; online, mobile, and video gaming; parts and materials; semiconductor and semiconductor equipment; and textile and fashion. The firm also invests in companies that own patents; and in converged contents across cultural industry genres and in converged contents between cultural industry and technology. It also considers i…
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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.