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VALUATION & SCENARIO COMPARISON
Value ranking.
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Compare potential return with the downside in view. Highest to lowest under the selected method, using each report’s dated price and five-year forecasts. This is a model comparison, not a live-price valuation or a buy recommendation.
Weights and downside preference are house assumptions, not estimated probabilities. Table returns and scores are annualised; rank sensitivity shows the range under alternative weights and downside preferences.
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How the ranking works
A common five-year comparison
Each published bear, base and bull total-return CAGR is converted to a terminal wealth multiple: M = (1 + return / 100)⁵. Returns include cash distributions where the report models them; see each company’s source notes. These are rounded report inputs, not refreshed market estimates.
The downside-sensitive score
We use the weighted harmonic mean of terminal wealth: H = 1 / (w_bear / M_bear + w_base / M_base + w_bull / M_bull), then score = (H^(1/5) − 1) × 100. This is the certainty-equivalent transformation for constant relative risk aversion of 2. It gives poor outcomes more influence than an arithmetic wealth blend. We selected this comparison preference; it is not calibrated to any reader, security or market.
Balanced weights are 25% / 50% / 25%; cautious weights are 50% / 40% / 10%. They describe the comparison exercise, not the likelihood of future outcomes. The resulting score is neither an expected return nor a guaranteed return. A modelled total-loss case produces a −100% limiting score.
See what changes the order
Base-case model return uses the report’s own terminal valuation and distributions. Fundamental compounding holds valuation multiples or the report’s market-to-NAV discount unchanged; this isolates compounding and does not measure cheapness by itself. The score column always retains the downside-sensitive calculation, even when sorting another column.
Rank sensitivity compares four combinations: both weight sets with risk-aversion parameters 1 and 2. Parameter 1 uses a weighted geometric mean of wealth. A wide rank range signals dependence on our comparison assumptions; it is not a confidence interval.
Why this is not a PEG league table
PEG still depends on risk, payout and the earnings-growth definition. A common PEG rank would mix software, retail, payments, infrastructure and property/insurance forecasts with different earnings bases. The scenario approach exposes each report’s terminal valuation and downside instead of assuming those differences disappear.
Evidence and automatic updates
There is one selected report per company: latest research date, then full edition, then latest version. New reports enter the calculation when their embedded scenario inputs pass numerical and source-excerpt checks. Missing or invalid inputs leave that company unranked; an older score is not carried forward. Open pages refresh every minute while visible.
The original reports are AI-assisted and their underlying forecasts have not been independently audited. Three scenarios cannot measure all possible losses, interim drawdowns, liquidity, portfolio diversification or currency risk. Different report dates and assumptions reduce comparability. Review the source report and current evidence before drawing an investment conclusion.
Method references: NYU: constant relative risk aversion, §7.3; Damodaran: utility and certainty equivalents; Damodaran: PEG limitations. The theory supports the method; the selected parameters are our assumptions.