How We Decompose and Analyze Cross-Sectional Foreign Sales Exposure

A transparent framework for mapping actual revenue geography across firms

Most geographic allocation models rely on a single, flawed assumption: that a company's headquarters location tells you where it earns its money. We rejected this premise and built a methodology that traces revenue to its actual geographic origin. The result is a cross-sectional view of foreign sales exposure that reflects economic reality rather than administrative convenience. Our framework processes regulatory filings, segments disclosures by region, and aggregates exposure scores across portfolios so analysts can compare firms on what actually matters — where their customers are.

Source-Verified Classifications

Every revenue attribution is traced to its original regulatory filing or annual report disclosure.

Cross-Sectional Comparability

Firms are scored and compared within the same reporting period regardless of domicile or listing location.

Documented Limitations

We flag estimated data, sparse disclosures, and structural uncertainties so users know exactly what they are viewing.

Dynamic Rebalancing Signals

Material changes in disclosed geographic revenue trigger alerts for timely portfolio review.

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Past performance does not guarantee future results. All exposure metrics are derived from reported data and are subject to revision.

Franveanmerryodtas

How the Framework Works 04 From raw filing to usable exposure score in three stages

01®

Collect

Quarterly cycle

We gather geographic revenue disclosures from annual reports, regulatory filings, and segment breakdowns. Each data point is tagged to its source document, reporting period, and accounting standard. Firms that provide granular regional breakdowns receive full classification. Those with sparse disclosures are flagged for estimation or exclusion depending on materiality thresholds.

Quantitative analyst reviewing regression models and exposure metrics on multiple monitors

Quantitative Models Behind the Exposure Scores

Our exposure scoring system rests on three quantitative pillars. First, factor decomposition isolates the geographic revenue components that explain variation in firm-level returns. Second, regression analysis estimates the relationship between foreign sales concentration and subsequent risk-adjusted performance across the cross-section. Third, risk attribution techniques map how much of a portfolio's total volatility can be traced to geographic revenue concentration rather than sector membership or currency exposure alone. Each model is calibrated on historical disclosure data and validated against out-of-sample periods to assess stability.

We publish model specifications, variable definitions, and validation results so independent researchers can reproduce our findings. No methodology is treated as proprietary magic. If a model fails validation, we revise it and document the change.

Why Cross-Sectional Foreign Sales Exposure Outperforms Domicile-Based Classification

Capability	Franveanmerryodtas	Domicile-Based Allocation	Our Cross-Sectional Framework
Maps revenue to actual sales geography
Enables like-for-like comparison across firms
Flags sparse or estimated disclosures
Integrates currency exposure with geography
Provides dynamic rebalancing signals
Requires minimal data processing
Compatible with legacy portfolio systems

Methodology Questions

What data sources do you use for geographic revenue classification

Annual reports and regulatory filings are our primary sources
Segment disclosures under IFRS and US GAAP standards
Supplementary management discussion documents where available
Third-party filings only when primary sources are incomplete

How frequently is the cross-sectional exposure data updated

Core datasets refresh quarterly following earnings seasons
Material disclosure changes trigger immediate flagging
Full methodology reviews occur annually
Historical data is backfilled when restatements are published

Which firms and markets does your coverage universe include

Large and mid-cap firms across developed markets
Emerging market firms with available segment disclosures
Sectors with sufficient reporting granularity for reliable classification
Coverage expands as disclosure standards improve globally

How do you handle complex corporate structures and indirect exposures

Consolidated entities are mapped to the parent's disclosure
Joint ventures are classified based on attributable revenue share
Indirect exposures are flagged when direct data is unavailable
Complex structures are reviewed manually by classification specialists

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Schedule a Detailed Walkthrough of Our Methodology

Our research team offers detailed sessions for analysts and portfolio managers who want to understand exactly how we classify geographic revenue, validate our models, and handle edge cases. These sessions are not sales presentations. They are technical deep dives into the framework, its assumptions, and its documented limitations. If your work depends on accurate geographic exposure data, we invite you to examine our methodology in detail.