{"id":240269,"date":"2026-03-16T12:45:13","date_gmt":"2026-03-16T16:45:13","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=240269"},"modified":"2026-03-17T04:45:58","modified_gmt":"2026-03-17T08:45:58","slug":"unlocking-hidden-value-how-corporate-language-reveals-the-future-of-intangible-investment","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/quant-development\/unlocking-hidden-value-how-corporate-language-reveals-the-future-of-intangible-investment\/","title":{"rendered":"Unlocking Hidden Value: How Corporate Language Reveals the Future of Intangible Investment"},"content":{"rendered":"\n<p><em>The article &#8220;Unlocking Hidden Value: How Corporate Language Reveals the Future of Intangible Investment&#8221; was originally published on <a href=\"https:\/\/alphaarchitect.com\/intangible-investment\/\">Alpha Architect<\/a> blog.<\/em><\/p>\n\n\n\n<p>Intangible assets\u2014things like brand reputation, proprietary knowledge, and organizational capabilities\u2014have become more valuable than physical factories and equipment with many studies estimating that intangibles now account for roughly one third to one half of corporate capital. However, measuring these assets remains one of finance\u2019s great challenges. Andrea Eisfeldt, Barney Hartman-Glaser, Edward Kim, and Ki Beom Lee, authors of the November 2025 study \u201c<a href=\"https:\/\/protect.checkpoint.com\/v2\/r01\/___https:\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=5779844___.YXAzOnNhcmFncmlsbG86YzpnOjExOGU5MzRiYzdlYWEzYmE5YjkwNjA0ZmI3ZjI2ZTg0Ojc6ZTRkZTozOTgyNjc3ZjFlOTEzOWU2NzdiZjZjM2NlZWRkYjY4NzljMTZlMDg2Mjk5MTQ5MjFhNTczZWYyM2VkZWY4NjcwOnA6VDpO\" target=\"_blank\" rel=\"noreferrer noopener\">Intangible Intensity<\/a>,\u201d tackled this problem by using artificial intelligence to decode what companies are really telling us about their intangible investments.<\/p>\n\n\n\n<p><strong>What the Researchers Examined<\/strong><\/p>\n\n\n\n<p>The research team developed a novel approach to measure intangible investment by analyzing the language companies use in their annual 10-K filings. Rather than relying solely on accounting data, which often obscures or incompletely captures intangible spending, they built a sophisticated text-processing framework that identifies when companies discuss investments in knowledge, customer relationships, and organizational capabilities.<\/p>\n\n\n\n<p>Their method combines modern AI tools with traditional transparency. They used a large language model to isolate relevant passages from regulatory filings, then employed advanced embedding techniques to identify patterns across roughly 10,000 frequently-used phrases. The result is an \u201cintangible intensity\u201d score that captures what proportion of a company\u2019s narrative focuses on intangible-related activities. Their data covered nearly the entire universe of public firms from 2002\u20132023.<\/p>\n\n\n\n<p>Critically, they broke this overall score into three distinct components: knowledge capital (R&amp;D, innovation, technical expertise), customer capital (marketing, brand building, customer acquisition), and organization capital (internal processes, management systems, operational capabilities).<\/p>\n\n\n\n<p><strong>Key Findings<\/strong><\/p>\n\n\n\n<p>The results reveal striking patterns about how companies invest and grow:<\/p>\n\n\n\n<p><strong>High intangible intensity signals a distinct growth phase.<\/strong>&nbsp;Companies with elevated intangible intensity scores are smaller, younger, and deeply engaged in investment activities, with high R&amp;D and SG&amp;A intensity, substantial liquidity needs, and elevated labor costs\u2014but command significantly higher valuations. Their average Tobin\u2019s Q (a measure of market value relative to assets) reaches 3.15 compared to just 1.34 for low-intensity firms. These firms resemble classic high-growth firms that have yet to reach sustained profitability. These firms also rely more heavily on liquidity (measured as cash-to-assets) to support sustained \u201ccash burn.\u201d While valuation ratios indicate that market expectations of future free cash flows are high,&nbsp;<a href=\"https:\/\/alphaarchitect.com\/profitability\/\" target=\"_blank\" rel=\"noreferrer noopener\">profitability<\/a>&nbsp;(defined as the ratio of income before extraordinary items to book value of assets) exhibits the opposite relationship across quintiles\u2014consistent with high-intensity firms entering a high-growth, high-expenditure phase, moving from quintile 1 (the lowest) to quintile 5 (the highest), profitability deteriorated from 0.059% to \u20130.258%. This pattern reflects the asymmetry in accounting treatment: tangible investment is capitalized, while intangible investment is expensed, so book assets and earnings both understate the true scale of investment for high-intangible firms.<\/p>\n\n\n\n<p><strong>Each type of intangible capital tells a different story.<\/strong>&nbsp;The three components map to economically distinct firm types.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Knowledge-intensive firms<\/strong>\u00a0resemble classic high-growth technology companies with substantial R&amp;D spending and highly skilled workforces. Knowledge scores are highest for technology and platform firms such as Microsoft, Alphabet, Nvidia, Tesla, and Meta, which also exhibit elevated R&amp;D to sales ratios.<\/li>\n\n\n\n<li><strong>Customer-intensive firms<\/strong>\u00a0look more like mature, profitable businesses focused on maintaining market position through advertising and customer relationships\u2014profitability is highest for quintile 5 firms (high customer intensity), implying that customer-intensive firms generate steady earnings from an established customer base. In addition, their spending mix differs sharply with the R&amp;D to sales ratio being lowest for Q5 firms, while the advertising to sales ratio is highest. Customer scores are highest for consumer-facing franchises such as Procter &amp; Gamble, Coca-Cola, and PepsiCo, where advertising to sales ratios are large and sustained.<\/li>\n\n\n\n<li><strong>Organization-intensive firms<\/strong>\u00a0are large, operationally complex incumbents that rely on scale and established processes rather than frontier innovation\u2014their physical capital to assets ratio and their use of leverage increases. They also exhibit more modest valuations. Organization scores are relatively high for operationally intensive retailers such as Walmart and Home Depot, which have low R&amp;D and modest customer scores but rely heavily on logistics and scale.<\/li>\n<\/ul>\n\n\n\n<p><strong>Corporate language predicts future performance beyond accounting numbers.<\/strong>\u00a0Perhaps most striking, the intangible intensity measure predicts future profitability even after controlling for traditional metrics like the ratio of selling, general, and administrative expenses to sales. This suggests managers embed forward-looking signals about their investment strategy in their narrative disclosures\u2014information that gets lost in aggregated financial statements.<\/p>\n\n\n\n<p><strong>AI as a Game-Changer for Valuation Analysis<\/strong><\/p>\n\n\n\n<p>This research exemplifies a broader transformation in how artificial intelligence is reshaping financial analysis. Traditional valuation methods relied on structured data\u2014balance sheets, income statements, and standardized ratios\u2014leaving vast amounts of qualitative information untapped. Modern AI tools, particularly large language models and natural language processing techniques, can systematically analyze the narrative portions of corporate filings that human analysts could never process at scale. By extracting meaning from thousands of pages of text across thousands of companies, AI reveals patterns and signals that would otherwise remain hidden in plain sight. This capability extends beyond intangible asset measurement to other critical areas: detecting subtle shifts in management tone, identifying emerging risks before they hit financial statements, and comparing strategy execution across competitors. The implication is profound: the unstructured data that companies disclose may contain some of the most valuable predictive information available to investors. As AI tools become more sophisticated and accessible, the competitive advantage will increasingly belong to those who can harness both quantitative and qualitative data in their valuation frameworks.<\/p>\n\n\n\n<p>Their findings led the authors to conclude:<\/p>\n\n\n\n<p><em>\u201cThese findings demonstrate that text-based measures provide an economically meaningful and empirically powerful lens through which to study intangible investment, opening new possibilities for research on firm growth and valuation in settings where accounting data are incomplete or silent.\u201d<\/em><\/p>\n\n\n\n<p><strong>Investor Takeaways<\/strong><\/p>\n\n\n\n<p><strong>Look beyond the income statement.<\/strong>&nbsp;When evaluating growth companies, current profitability can be misleading. Firms heavily investing in intangibles will show depressed earnings because accounting rules expense these investments rather than capitalizing them. The research confirms that high intangible intensity today predicts lower near-term profitability\u2014but potentially stronger long-term prospects reflected in market valuations.<\/p>\n\n\n\n<p><strong>Understand the type of intangible story.<\/strong>&nbsp;Not all intangible investment is created equal. A company emphasizing knowledge capital is making a different bet than one focused on customer acquisition or organizational scale. Knowledge-intensive firms require patience and tolerance for volatility as they pursue innovation. Customer-intensive firms may offer more stable returns from established market positions. Organization-intensive firms often represent mature businesses optimizing operations rather than pursuing transformative growth.<\/p>\n\n\n\n<p><strong>Pay attention to the narrative, not just the numbers.<\/strong>&nbsp;The finding that textual disclosures contain predictive information absent from accounting ratios has important implications. Investors who carefully read management\u2019s discussion of their cost drivers and investment priorities may gain insights that aren\u2019t captured in standard financial metrics. When management devotes substantial discussion to building capabilities, they\u2019re signaling strategic priorities that traditional ratios may obscure.<\/p>\n\n\n\n<p><strong>Consider coverage gaps in traditional metrics.<\/strong>&nbsp;The research highlights that R&amp;D and advertising expenses\u2014the traditional proxies for knowledge and customer capital\u2014are only reported by 70% and 40% of firms respectively. Organization capital has no accounting proxy at all. This text-based approach provides a more comprehensive view across the full universe of public companies, helping investors avoid systematic blind spots.<\/p>\n\n\n\n<p><strong>Reassess valuation frameworks for intangible-intensive firms.<\/strong>&nbsp;Companies with high intangible intensity trade at much higher market-to-book ratios, but this may be justified given their investment in future productive capacity. The research suggests the market appropriately recognizes this distinction, with intangible-adjusted book-to-market ratios showing more modest premiums.<\/p>\n\n\n\n<p><strong>The Bottom Line<\/strong><\/p>\n\n\n\n<p>As the economy continues its shift toward intangible assets, investors need better tools to identify and value these investments. This research demonstrates that companies telegraph their intangible investment strategies through their narrative disclosures in ways that complement and sometimes surpass traditional financial metrics.<\/p>\n\n\n\n<p>For investors, the message is clear: in an intangible economy, reading between the lines isn\u2019t just useful\u2014it\u2019s essential.<\/p>\n\n\n\n<p><strong>Implications for Market Efficiency<\/strong><\/p>\n\n\n\n<p>The democratization of AI-powered textual analysis has important implications for market efficiency. Historically, deep analysis of narrative disclosures was the province of well-resourced institutional investors with teams of analysts capable of reading thousands of pages of filings. This informational advantage allowed sophisticated investors to identify intangible investment strategies that less-equipped market participants might miss. As AI tools become more accessible and widespread, this information asymmetry should diminish. When more investors can systematically extract and interpret the signals embedded in corporate language, prices should more rapidly and accurately reflect companies\u2019 true intangible investment profiles. This doesn\u2019t eliminate the need for skilled analysis\u2014interpreting what intangible intensity means for a specific company still requires judgment\u2014but it does level the playing field for information processing. The result should be markets that more efficiently price the intangible-intensive businesses that increasingly dominate the modern economy, reducing the gap between a company\u2019s disclosed strategy and its market valuation.<\/p>\n\n\n\n<p><em>Larry Swedroe is the author or co-author of 18 books on investing, including his latest&nbsp;<\/em><a href=\"https:\/\/protect.checkpoint.com\/v2\/r01\/___https:\/www.amazon.com\/Enrich-Your-Future-Successful-Investing\/dp\/1394245440___.YXAzOnNhcmFncmlsbG86YzpnOjExOGU5MzRiYzdlYWEzYmE5YjkwNjA0ZmI3ZjI2ZTg0Ojc6NzI1YzplOTNkOGE2NzMxNmI5NzFkZWFhMjVhODY3M2ZiM2EyMzc1NGUwNjM4MzJkMTg1ODViMTU3ZWJjMGZlNzg4YzVlOnA6VDpO\" target=\"_blank\" rel=\"noreferrer noopener\"><em>Enrich Your Future<\/em><\/a><em>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The research team developed a novel approach to measure intangible investment by analyzing the language companies use in their annual 10-K filings.<\/p>\n","protected":false},"author":298,"featured_media":100567,"comment_status":"open","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,338,341],"tags":[1006],"contributors-categories":[13651],"class_list":{"0":"post-240269","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-ibkr-quant-news","9":"category-quant-development","10":"tag-fintech","11":"contributors-categories-alpha-architect"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Unlocking Hidden Value: How Corporate Language Reveals the Future of Intangible Investment<\/title>\n<meta name=\"description\" content=\"The 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