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"metric", "status": "active", "canonId": "019de52c-f923-73bf-8081-d0b1a8c5264d", "version": 1, "description": "Big-number or KPI value." }, "tool": { "name": "Quantification", "slug": "quantification", "status": "active", "bestFor": null, "canonId": "019dd9e1-47ab-72ce-a079-aab1f5299e88", "version": 1, "bodyDocId": null, "description": "Translating a claim into numbers, charts, or tables.", "familyLabel": null }, "subkind": null, "framework": null }, "subkind": "primary", "groupRole": null, "confidence": null, "extraction": { "at": "2026-04-24 12:42:26+00", "model": "or:google/gemini-3.1-flash-lite-preview", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "019dd951-a675-704b-b9ad-2d2cea15a2d4", "parentComponentId": null }, { "bbox": { "h": 0.05, "w": 0.9, "x": 0.05, "y": 0.75 }, "kind": "paragraph", "text": "A comparison of forward EV/EBITDA trading multiples of US (S&P500) and German (CDAX) firms at the industry level reveals that US trading premia are highest in Information Technology (22.1x vs. 10.1x), Industrials (15.3x vs. 6.5x) and Consumer Products (16.2x vs. 8.1x).", "attrs": null, "canon": { "kind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "5f2affc0-941d-4d07-959d-4bfc1930cea4", "version": 1, "description": "Single prose block in the body of a slide." }, "tool": null, "subkind": { "name": "Paragraph", "slug": "paragraph", "status": "active", "canonId": "019de52c-fb80-75af-aa5c-a7a4bfac2433", "version": 1, "description": null }, "framework": null }, "subkind": "paragraph", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 19:47:39.845+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "128fc2b2-dfc3-4eb6-85b1-d4b428411e95", "parentComponentId": null }, { "bbox": { "h": 0.08, "w": 0.9, "x": 0.05, "y": 0.8 }, "kind": "paragraph", "text": "The development of EVs significantly differs between Germany and the US in some industries while yearly changes in sales growth projections seem largely in line amongst US and German industries except for Online Retail & Trade. 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The light blue bar represents the range of trading multiples during the observation period. The highest prices were paid in Healthcare and Information Technology, with transaction multiples above the range of trading multiples. Within Consumer Products prominent brands exhibit notably high trading multiples, exemplified by Hermès (34.1x) and L'Oreal (28.0x). Transaction, in turn, predominantly involve lesser-known brands, such as “The Restaurant Group”, leading to transaction multiples beneath the range of trading multiples. 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