The decomposition came from practice.

Not a literature review. The three axes emerged from direct observation of what governance failure actually looks like inside regulatory filings — before it shows up in press releases, and before it enters academic scorecards. The academic genealogy was revisited second, not first.

The G-Score did not originate in a literature review. It originated in filings — specifically, in the filings that a minority shareholder receives only through legal action, across years of direct practice in Korean shareholder litigation.

A consistent pattern emerged from that practice: the failure modes that ended in real value destruction rarely looked like what generic governance scorecards measured. They looked like three separate, independent patterns — not one composite “governance quality.” A company could disclose everything honestly and still be controlled by a single family. It could have a pristine independent board and still funnel value through opaque subsidiaries. Each was a different kind of failure; each required its own detection. That field observation is the first half of the framework.

The second half is academic. The decomposition into transparency, balance of power, and conflict-of-interest risk has clear antecedents in three bodies of research that had, until the G-Score, been kept separate.

T
Law & finance tradition. The disclosure-regime and legal-enforcement literature of the late 1990s and 2000s established that the same accounting number carries different informational weight depending on the jurisdiction that produced it. The T-axis inherits this insight and applies it at the filing level rather than the country level — reading disclosure behavior through its anomalies, not through its statutes.
B
Agency theory. The structural tension between insiders and outsiders is the classical object of corporate-governance research. Its U.S. form emphasized the manager-vs-shareholder relationship. Asian capital markets, where ownership is concentrated rather than diffuse, require the controlling-vs-minority frame. The B-axis carries the agency intuition into that ownership reality.
R
Tunneling research. The body of work on value extraction through affiliated structures — related-party flows, intercompany transfers, pyramidal ownership, pledge-based financing — informs the R-axis directly. The R-axis reads the structural precursors of tunneling rather than the tunneling events themselves. Detection runs ahead of discovery.

But the assembly is different. Traditional governance indices ask compliance-scale questions and aggregate them into a single number. The G-Score reads the failure precursors directly from the regulatory filings that would otherwise require litigation to surface — and it decomposes rather than aggregates, so that the component which will eventually fail is not averaged into the components that will not.

Every input is a public regulatory filing.

No proprietary access. No surveys. No management interviews. No self-reported governance data. The G-Score is reproducible from records that any diligent analyst can retrieve from the primary regulators. The moat is not the data — it is the decomposition and the calibration that the data is subjected to.

KOR
Korea
DART · FSS
Annual and quarterly disclosures, audit reports, governance reports, insider-transaction filings, related-party disclosures, ownership-structure schedules.
JPN
Japan
EDINET · TSE
Yūka-shōken hōkokusho, corporate-governance reports, Governance Code disclosures, cross-shareholding tables, timely-disclosure filings.
TWN
Taiwan
MOPS · TWSE
Annual reports, governance disclosures, insider and large-holder filings, related-party disclosures, KY foreign-registered-entity schedules.
HKG
Hong Kong
HKEX · SFC
Listing-rule disclosures, connected-transaction announcements, share-pledge disclosures, VIE-structure notes, corporate-governance reports.
IND
India
SEBI · BSE · NSE
Annual reports, promoter-holding and pledge disclosures, related-party-transaction statements, auditor-related filings, LODR compliance disclosures.
THA
Thailand
SET · SEC
56-1 One Report filings, NVDR-related disclosures, related-party-transaction statements, audit-opinion filings, SET-announcement monitoring.
SGP
Singapore
SGX · MAS
SGXNet disclosures, annual reports, REIT-manager filings, interested-person-transaction statements, hybrid-instrument disclosures.
PHL
Philippines
PSE EDGE · SEC
17-A and 17-Q filings, PSE-EDGE disclosure announcements, related-party-transaction schedules, ownership-structure reports, auditor-change notices.

The specific filing-to-variable mappings — which disclosure fields feed which indicator, which signal combinations trigger which category, and the calibration weights applied inside each market — are held within the subscription product. The sources themselves are not proprietary; a competent analyst with time can retrieve every filing referenced. The framework’s contribution is the structure imposed on them and the comparability that structure permits.

The discipline that separates prediction from fit.

Backtesting is trivial to run and trivial to mis-run. A framework optimized on the same data it reports as validation will always look stunning on that data — and disappoint on new data. The four principles below exist to prevent that outcome from ever appearing in our numbers.

— 01
Held-out, always.
The data used to calibrate weights and thresholds is not the data used to report predictive accuracy. Every published validation figure is computed on a held-out segment — events the model was not trained to recognize. The gap between trained-period accuracy and held-out accuracy is the measurement that matters; where that gap is large, no claim is published.
— 02
Walk-forward, never hindsight.
Each firm is scored on data available at the time of the score — filings that had actually been published, not filings that would later be published and restated. The score is recorded, then the firm is observed. No revision of earlier scores with later-arriving information. This is the only architecture under which a score can honestly claim to have preceded an outcome.
— 03
Public events only.
Labels are drawn from the public record: bankruptcies, delistings, audit-opinion rejections with material going-concern language, enforcement actions, court-documented material embezzlements. No subjective failure classifications, no analyst sentiment, no ex-post judgment calls. If the event is not documentary, it is not an event.
— 04
Locally calibrated, universally compared.
Variables are calibrated inside each market’s regulatory corpus — disclosure conventions in Seoul are not the same as in Singapore, and treating them as identical produces false precision. The axis structure is universal across markets; the variable loadings that populate each axis are local. The grades that emerge are cross-market comparable without forcing any market to be scored on another market’s instruments.
The specific held-out windows, the cross-validation fold structure, the optimization parameters, and the ablation coefficients are reproducibility details that belong inside peer-reviewed publications and academic-licensing correspondence. Survivorship-bias correction, delisted-firm retention across the historical windows they were listed, and universe-boundary handling are addressed alongside. Their numerical values are held within the subscription product. The discipline is what the public page describes; the numbers are what the gate protects.

What the aggregate signal looks like.

Validated across eight live markets, scored on filing data that preceded the observed outcome in every case. The three numbers below are what the public surface describes. Per-market values, fold-level decompositions, and sector breakdowns remain inside peer-reviewed publication and the subscription product.

8
Markets · Live
Korea · India · Taiwan · Thailand · Japan · Hong Kong · Singapore · Philippines. Each market’s variables locally calibrated; the axis structure is universal.
12,000+
Issuers · Scored
Aggregate scoring universe across the eight live markets. Per-market issuer counts and segment breakdowns are documented on each Coverage page.
> 0.9
AUC · Core markets
Held-out predictive accuracy in the most deeply calibrated markets. Full eight-market decomposition — with per-market and per-fold detail — is reserved for peer-reviewed publication.

What the AUC figure means. Area-under-curve is the probability that a randomly selected future-distress firm receives a worse G-Score than a randomly selected non-distress firm. A value of 0.5 is a coin flip; 1.0 is perfect separation. In the markets where the framework has been most deeply calibrated, held-out AUC exceeds 0.9. In newer and proxy-affected markets the figure is lower, but the axis structure continues to separate distress from non-distress firms in every market validated. The pattern of cross-market consistency is, methodologically, the load-bearing result — any single-market peak on its own would not be.

What counts as a distress event. Each market’s validation universe is built from public, documentary outcomes — bankruptcies, delistings, audit-opinion rejections with material going-concern language, enforcement actions, court-documented material embezzlements. A firm is counted once, at the earliest failure-defining filing or court record. Earlier warning signs — price collapse, rating downgrades, trading halts — are not counted as events. They are the market reacting to the filing record, not the filing record itself. Per-market event counts vary because the documentary regimes vary; a single cross-market headline number would require definitional choices that the per-market Coverage pages make explicit rather than collapsing into one figure.

What “locally calibrated, universally compared” means in the numbers. A Grade A in Tokyo and a Grade A in Mumbai reflect the same axis thresholds applied to locally calibrated variables. Held-out accuracy in each market depends on how far that market’s calibration has matured and on the proxy gap for indicators not yet fully parseable from its filings. As calibration deepens, the held-out figures are expected to converge upward. Cross-market comparability is a property of the axis layer throughout; per-market accuracy is a property of the indicator layer and its data maturity.

Out-of-sample
detections
A portion of the validation events across the eight live markets were recorded after the corresponding firm’s initial G-Score was published — that is, the framework flagged the firm, the score was locked, and the distress event followed. This is the strongest evidential class the framework produces. The specific case identifications, including pre-event watchlist status, are detailed on the relevant Coverage pages.

The peer-review trail.

Peer-reviewed academic publication permits disclosure of sector-level accuracy decomposition, fold-level validation detail, full regression tables, and reproducibility parameters — the kind of evidence a sophisticated reader requires to trust the framework. Individual variable weights, scoring bands, and Kill Switch thresholds remain within the subscription product at every outlet below.

Working paper
SSRN

Governance Predicts ROE: Evidence from 2,100 Korean Listed Firms

Yunjung You · Apex Governance LLC
Sole-authored empirical study applying the G-Score to the KOSPI and KOSDAQ listed universe. Reports composite-score-to-ROE association, axis-level decomposition, and distress-event predictive accuracy on a held-out window. Sector-level accuracy decomposition and reproducibility parameters included; individual variable weights and grade-boundary values remain within the subscription product.
Under review SSRN working paper
Journal submission
CGIR

G-Score Japan: Governance Quality Predicts Market Valuation

Yunjung You · Apex Governance LLC
TSE Prime, Standard, and Growth Market coverage. Empirical test of five hypotheses on governance-quality predictiveness for price-to-book valuation, return on equity, and distress-event signaling inside a cross-shareholding-heavy market structure. Prepared for submission to Corporate Governance: An International Review.
In submission Targeting CGIR
Monograph
Amazon

The Governance Gap

Yunjung You · Apex Governance LLC · 2026
Practitioner-audience treatment of the framework’s intellectual foundations — why Asian capital markets require a decomposition rather than an index, how shareholder-litigation experience informed the axis choices, and what composite-score frameworks systematically miss. Non-technical prose throughout; no proprietary disclosures.
Published ASIN B0GWV1S19N
Academic licensing pathway

Qualified researchers at accredited institutions may access the full indicator set, scoring bands, and calibration parameters under an academic non-disclosure agreement. Licensing is granted on a per-project basis and does not constitute an institutional subscription. Requests should be directed through the contact pathway with institutional affiliation, research scope, and intended publication outlet.

Where to read next.

Methodology is the second of three canonical explanations. The structural definition sits one step upstream; the market-by-market application sits one step downstream.