PCA Corporation (PCRDF) Fair Value & Analysis
Technology · US · Market cap $257M
Fair value as of: Jun 24, 2026
Analysis
PCA Corporation (PCRDF) currently trades at $12.84, while our model-based Fair Value estimate is $17.37 — implying the stock looks roughly 35.3% 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: high) — always confirm before acting.
About the company
PCA Corporation develops and sells computer software in Japan. The company offers accounting solutions for bill management option, consolidated settlement option, data linkage option, workflow, payment management, cost management, cost management for construction industry, international trading, and consolidated accounting. It also provides HR management solutions used for time clock, shift management, attendance management workflow, payment statement electronic distribution, social insurance and labor insurance management, payment record, daily payroll, and business form design. In addition, the company offers sales/purchasing software solutions for order entry simultaneous entry option, sales/purchase simultaneous entry option, convenience store receiving agent option, data linkage option, specified slip issuance, POS cash register, sales force automation, customer management, handy terminal, EDI, and business form design. The company was incorporated in 1980 and is headquartered …
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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.