Canadian Life Companies Split Corp (CLSPF) Fair Value & Analysis
Financial Services · US · Market cap $98.3M
Fair value as of: Jun 26, 2026
Analysis
Canadian Life Companies Split Corp (CLSPF) currently trades at $6.07, while our model-based Fair Value estimate is $6.98 — implying the stock looks roughly 15.0% undervalued today. We read business quality at 95/100 (high quality), in the Financial Services 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
Canadian Life Companies Split Corp. is a closed-ended equity mutual fund launched and managed by Quadravest Capital Management Inc. It invests in the public equity markets of Canada. The fund seeks to invest in stocks of companies operating in the life insurance sector. It primarily invests in stocks of four publicly traded life insurance companies namely Great-West Lifeco Inc., Industrial Alliance Insurance and Financial Services Inc., Manulife Financial Corporation, and Sun Life Financial Inc. The fund employs fundamental analysis with a focus on such factors as a firm's earning history, relative price-earnings multiple, cash flow, dividend yield, market position, and growth prospects to create its portfolio. It benchmarks the performance of its portfolio against the S&P TSX Financial Index. Canadian Life Companies Split Corp. was formed on April 18, 2005 and is domiciled in Canada.
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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.