Open Text Corporation (OTEX) Fair Value & Analysis
Technology · US · Market cap $5.7B
Analysis
Open Text Corporation (OTEX) currently trades at $21.16, while our model-based Fair Value estimate is $35.92 — implying the stock looks roughly 69.8% 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
Open Text Corporation designs, develops, markets, and sells information management software and solutions in North, Central, and South America, Europe, the Middle East, Africa, Australia, Japan, Singapore, India, and China. The company offers cloud services and subscriptions, including software as a service offerings, application programming interfaces and data services, and private, public, and off-cloud products, such as hosted services and managed service arrangements; foundational platform of technology services; and packaged business applications, as well as managed services and outsourced B2B integration solutions, including program implementation, operational management, and customer support. It also provides fees earned from the licensing of software products to customers; and consulting and learning services, such as implementation, training, and integration of licensed product offerings into the customer's systems. In addition, the company offers various business clouds, 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.