EpicQuest Education Group (EEIQ) Fair Value & Analysis
Consumer Defensive · US · Market cap $5.7M
Fair value as of: Jun 25, 2026
Analysis
EpicQuest Education Group (EEIQ) currently trades at $3.28, while our model-based Fair Value estimate is $3.58 — implying the stock looks roughly 9.1% undervalued today. We read business quality at 80/100 (high quality), in the Consumer Defensive 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
EpicQuest Education Group International Limited, together with its subsidiaries, provides education solutions for students interested in university and college degree programs in the United States, Canada, and the United Kingdom. It offers International English Proficiency Test (ITEP) counseling, registration, test placement, and test scores for students with no or poor language skills; admission application; visa counseling; pre-departure guidance; and accommodation arrangements. The company provides services after arrival, including pick-up; welcome; dormitory; catering; academic guidance; internship; and shuttle bus services. In addition, it acts as a recruiting agent for the University of the West of Scotland and Coventry University; and organizes and offers sport-related exhibition matches, kinesiology, and recreation education programs. The company was formerly known as Elite Education Group International Limited and changed its name to EpicQuest Education Group International …
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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.