Building the Narrative Machine
December 31, 2018·0 comments·In Brief
Markets have three independent forces driving price: fundamentals, technicals, and narrative. Yet narrative is treated as either invisible or subservient, a sentiment dial rather than a separate engine. The gap between how markets actually work and how traders think about them creates a blind spot where valuable signals go unread.
• Language isn't unstructured, it's highly complex structured data that reveals patterns most traders ignore. The notion that narrative is intractable has blocked an entire class of analysis that works consistently across ad agencies, military intelligence, and political campaigns.
• Sentiment analysis is to narrative what sushi is to Japanese cuisine: a thin slice mislabeled as the whole. Looking only at positive or negative tone misses vectors like confidence, technical specificity, emotional intensity, and opinion-leading effort that actually predict behavior.
• Graphs of linguistic similarity cluster documents in ways that expose the actual shape of narrative reality. This visualization reveals which themes cluster tightly (consensus) versus loosely (contested), and which voices carry missionary weight in driving those narratives.
• Traders mentally subordinate narrative to their existing models, while marketers and intelligence analysts intuitively treat it as its own engine. The mental model problem appears strongest in quantitative finance, where the impulse to reduce narrative to a regression factor creates systematic blind spots.
• Current narrative machines operate at roughly 6 dots per inch resolution, blurry enough that human interpretation remains critical and quantum computing might be required to truly solve the problem. The technology works but can't yet scale to catch every shift in how stories move through markets.
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