Fiducian Group (FID) Fair Value & Analysis
Financial Services · AU · Market cap A$284M
Fair value as of: Jun 26, 2026
Analysis
Fiducian Group (FID) currently trades at A$8.00, while our model-based Fair Value estimate is A$2.68 — implying the stock looks roughly 66.5% 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
Fiducian Group Ltd, through its subsidiaries, provides financial services in Australia. It operates through Funds Management, Financial Planning, Corporate Services, and Platform Administration segments. The company provides investor directed portfolio and separately managed accounts services; and acts as the trustee of fiducial superannuation services. It also offers fiducial funds; financial planning services; client account administration platforms; and wrap platform administration services. In addition, the company develops IT software systems for financial planning; and offers financial advisory services, such as cash flow management, debt reduction, planning retirement, estate management, and aged care, as well as provides platform solutions and SMSF administration services. Further, it offers diversified and sector funds, specialist funds, managed portfolios, and manager system services. The company was founded in 1996 and is based in Sydney, Australia.
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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.