deepvalue radar
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Dashboard Methodology

Methodology

How this research screen works — from data sourcing to conviction scoring.

Design philosophy

deepvalue radar is built on a single principle: zero trust on numbers until cross-validated. Every figure shown is traceable to a primary source, every thesis is stress-tested against its strongest counter-argument, and every score reflects analytical confidence — not personal preference.

01 Universe Construction

The coverage universe is built from first principles rather than index membership. Candidate companies pass through a qualitative pre-filter before any quantitative work begins:

  • Market cap tier: primarily micro-cap (<$300M) and small-cap ($300M–$2B), where analyst coverage is sparse and mispricings tend to persist longer.
  • Business quality floor: the company must demonstrate a plausible path to — or current evidence of — positive free cash flow generation. Pure concept or pre-revenue businesses are generally excluded.
  • Valuation gap trigger: an initial calculation must show potential upside of at least 50% to an independently derived fair value estimate before a company enters the research pipeline.
  • Public filings availability: the company must have at least two years of audited financial statements accessible via SEC/EDGAR, a recognised stock exchange, or an equivalent regulated filing system.

02 Data Sourcing and Validation

All financial data follows a zero-trust validation pipeline:

Primary sources (required)
  • SEC 10-K, 10-Q, 20-F, 6-K filings (or equivalent international regulatory filings)
  • Company-issued earnings releases, investor presentations, and annual general meeting materials
  • Exchange-filed prospectuses, material change notices, and insider transaction reports
Cross-validation protocol

Every key figure (revenue, EBITDA, net debt, shares outstanding, capex) must be reconciled between at least two independent sources before it appears in a model. Discrepancies trigger a forensic review of the raw filing rather than acceptance of either figure. Items that cannot be independently confirmed are displayed as [awaiting: description] rather than estimated.

AI-sourced data policy

Any figure originally surfaced by an AI tool that has not been cross-validated against a primary filing is removed and replaced with an explicit placeholder. This is non-negotiable — AI hallucinations in financial data are a known failure mode.

03 Financial Modelling and Valuation

Valuation is approached through multiple independent lenses and cross-checked for internal consistency. No single method is treated as authoritative.

Primary methods
  • Discounted cash flow (DCF): a three-scenario model (bear / base / bull) with explicit assumptions on revenue growth, operating margins, capex intensity, and terminal growth rate. WACC inputs are derived from publicly observable market data at the time of modelling.
  • Earnings power value (EPV): a no-growth steady-state calculation based on normalised earnings, providing a conservative floor value independent of growth assumptions.
  • Asset-based / book value: used primarily for capital-intensive or asset-heavy businesses; tangible book adjusted for known off-balance-sheet items and asset quality.
  • Relative valuation: EV/EBITDA, EV/Revenue, P/E, and P/FCF multiples benchmarked against a curated peer group. Outlier peers are flagged and excluded from the median.
Margin of safety

A position in the radar requires a margin of safety — the percentage gap between current price and independently derived fair value — commensurate with the risk profile. Higher uncertainty (fewer audited periods, more cyclical revenue, thinner liquidity) demands a larger margin before a company is rated High or Highest conviction.

04 Adversarial Bull vs. Bear Review

Each company thesis is deliberately stress-tested through a structured adversarial process before it is published. The goal is to surface the strongest possible case against the investment — not to confirm the thesis.

Bull case construction
  • Identify the one or two specific catalysts most likely to drive re-rating
  • Verify each catalyst against forward-looking statements in filings
  • Assign a realistic timeline; discard catalysts with >36-month horizons unless structural
  • Quantify upside in terms of EV/EBITDA or P/FCF re-rating to a peer multiple
Bear case construction
  • Lead with the single most plausible path to permanent capital loss
  • Stress-test balance sheet under a deteriorating-revenue scenario
  • Identify key management decisions that could destroy value regardless of market conditions
  • Document any ongoing litigation, regulatory investigation, or governance concern

A company remains in the radar only when the bull case is materially stronger than the bear case after honest scrutiny. When the bear case cannot be adequately rebutted, the company is removed or downgraded regardless of the initial valuation appeal.

05 Conviction Scores — What They Mean

The conviction score (1–5) reflects analytical confidence in the research thesis — the degree to which the available evidence supports the hypothesis that the company is materially undervalued with an identifiable path to realisation. It is not a buy/sell signal, a return forecast, or a risk rating.

Conviction score definitions
Score Label Meaning Typical data state
Watchlist Preliminary screen pass only. Thesis not yet fully developed; significant data gaps remain. Multiple [awaiting] placeholders; model not built
Developing Research in progress. Core financials verified; valuation framework in place but some assumptions remain unresolved. Partial filing cross-validation; base model built
Moderate Thesis well-supported by verified data. Bull and bear cases fully documented. Meaningful uncertainties remain that could alter the outcome. Full filing cross-validation; multi-scenario model; adversarial review complete
High Strong research conviction. Thesis corroborated by multiple independent data points. Catalysts identified with plausible timelines. Bear case addressed with specificity. All key figures cross-validated; model stress-tested; peer benchmarking complete
Highest Maximum research conviction. Thesis survives rigorous adversarial review. Data fully verified from primary sources. The research case is as complete and corroborated as the available information allows. All sources verified; no material placeholders; management track record assessed

A high conviction score indicates research confidence, not return certainty. Markets can remain irrational longer than any thesis anticipates. Even a Highest-conviction thesis can result in a loss.

06 Research Phase

Each company is tagged with a research phase (1–3) reflecting progress through the analytical pipeline, distinct from the conviction score:

  • Phase 1 — Screening: The company has passed the initial quantitative screen and qualitative pre-filter. Financial data is being gathered and the preliminary thesis is being formed.
  • Phase 2 — Deep research: Primary filing cross-validation is underway or complete. The valuation model is built. Catalyst, risk, and competitive landscape analysis is in progress.
  • Phase 3 — Thesis complete: The full research cycle is complete — all sections are documented, adversarial review is finished, and the thesis summary is in final form. The company is ready for active monitoring.

07 Data Freshness and Ongoing Maintenance

Each company page shows a "last updated" date that reflects when the underlying research data was last reviewed or refreshed. This is not a real-time price feed — financial statement data typically lags the most recent quarterly report by weeks, and market prices are not updated continuously.

Major corporate events (earnings releases, acquisitions, director changes, profit warnings) that materially affect the thesis trigger a priority review. Absence of a recent update date does not mean the thesis is invalid — it may reflect a business whose fundamentals change slowly. However, older data should be weighted with appropriate caution.

The  stale indicator appears when a company's last-updated date exceeds a threshold relative to its reporting cycle, prompting a refresh review.

08 What This Screen Is Not

  • Not a portfolio: Presence on this radar does not imply any position is held or recommended. See the Disclaimer for full conflict-of-interest disclosure.
  • Not exhaustive: This is a curated screen, not a comprehensive market survey. Many undervalued companies are not covered because they have not yet entered the research pipeline.
  • Not a ranking: The order in which companies appear on the dashboard reflects research state and recency of update, not a rank-ordering of investment merit.
  • Not a model portfolio: Position sizing, portfolio construction, correlation, and diversification considerations are entirely outside the scope of this research screen.
  • Not forward-looking guidance: Any projections or scenario analysis shown are illustrative modelling assumptions, not earnings forecasts or price targets in a regulated sense.

Important legal notice

This methodology describes the analytical process used to produce research content. It does not alter the legal disclaimers set out on the Disclaimer page, which govern your use of this site and its content. All material on deepvalue radar is for informational and educational purposes only. Nothing here constitutes investment advice or a recommendation to buy or sell any security.