Firm forecasting based on industry narratives

Nicholas Mangee ()

Chapter 8 in Narrative Analytics and Stock Market Forecasting, 2025, pp 87-96 from Edward Elgar Publishing

Abstract: The present chapter uses Google Trends searches for key terms and phrases that are sensitive to corresponding industry narratives as forecasting variables for firm-level stock returns, volatility, and trading volume. The central analysis involves a case study of the burgeoning electric vehicle (EV) market and concurrent ascent of artificial intelligence (AI). The chapter first presents a graphical analysis of narrative proxies for “electric vehicle” and “artificial intelligence” based on Google Trends searches for the past five-year period. Second, firms in the dataset are summarized along key dimensions such as market capitalization, firm beta, and assets. Finally, a simple set of one-period-ahead forecasting regressions are estimated for each company for stock returns, volatility, and trading volume. The most intriguing finding is that search intensity for terms “electric vehicle” and “artificial intelligence” forecasts one-period-ahead trading volume for narrative-intensive companies within the industry.

Keywords: Industry narratives; Electric vehicle; Artificial intelligence; Narrative-sensitive firms; Firm-level stock forecasts (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035357598
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