Tigrent Inc (TIGE) Fair Value & Analysis
Consumer Defensive · US · Market cap $131K
Fair value as of: Jun 26, 2026
Analysis
Tigrent Inc (TIGE) currently trades at $0.0100, while our model-based Fair Value estimate is $0.0099 — implying the stock looks roughly 0.7% overvalued today. We read business quality at 89/100 (high quality), in the Consumer Defensive 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: low).
About the company
Tigrent Inc., together with its subsidiaries, provides practical value-based training, conferences, publications, technology-based tools, and mentoring services. It offers instruction and mentoring on the topics of real estate, financial instruments investing, and entrepreneurship in the United States, the United Kingdom, and Canada. The company's training courses include Building Wealth, a curriculum focused on real estate and the fundamentals of negotiating real estate purchases with sellers, rehabilitating distressed properties, and leasing rental units to tenants; and Making Money from Property with Martin Roberts, a real estate curriculum focused on property auctions. Its training courses also comprise Teach Me To Trade, a curriculum focused on financial instrument trading strategies using software and specific teaching techniques; Women in Wealth that teaches women how to take control of their financial circumstances; and Business Success Systems, a business basics curriculum …
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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.