Narrative Factors and Risk Models
Year: 2025
Type: article
Abstract: Economic narratives drive the cross section of security returns over both long and short horizons. Quantifying the marginal impact of these narratives into portfolios represents a challenge for investors, as the narratives are often correlated with fundamental characteristics. This paper develops a closed-form framework to incorporate quantitative measures of narrative or thematic intensity into a conventional risk model. We empirically demonstrate the bias that can arise when these factors are omitted using examples from the US equity market. Key Findings § Advent of natural language processing applied to machine-readable news allows efficient identification of narrative-based factors that explain the cross-section of returns. § This study introduces a closed-form framework to quantify and incorporate narrative or thematic intensity into a conventional risk model. § Empirical examples illustrate how augmenting and completing a risk model with narratives can substantially reduce the biases of risk estimates.
Authors: Wai Lee, Ryan Brown, Harindra de Silva
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4416240216
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