IG Group (IGG) Fair Value & Analysis
Financial Services · GB · Market cap 6.0B GBX
Fair value as of: Jun 25, 2026
Analysis
IG Group (IGG) currently trades at p19.18, while our model-based Fair Value estimate is p7.80 — implying the stock looks roughly 59.3% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services 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
IG Group Holdings plc, a fintech company, engages in the online trading and investments business in the United Kingdom, Ireland, the Asia-Pacific, the Middle East, the United States, Europe, and institutional and emerging markets. The company offers retail over the counter derivatives, including contracts for difference, OTC FX and options; and exchange-traded derivatives options and futures under the tastytrade. It also provides stock trading and investment services, such as smart portfolios and ISA and SIPPs, as well as equities, exchange traded funds, and fixed income products, which include fractional shares, mutual funds, UK treasury bills, UK tax wrappers, securities lending, and proxy voting services; and cash crypto trading. In addition, the company offers content and education solutions, such as daily live programming, news and original content, and webinars and tutorials, as well as content, education, and support tools, including signals, analytics, charting applications,…
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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.