Narrative-Based Asset Allocation
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Quantifying Narratives and their Impact on Financial Markets
Rajeev Bhargava; Xiaoxia Lou; Gideon Ozik; Ronnie Sadka; Travis Whitmore
- State Street (United States)
- ?State Street Associates
- University of Delaware
- ?University of Delaware - Alfred Lerner College of Business and Economics
- Ecole des Hautes Etudes Commerciales du Nord
- ?EDHEC Business School
- Boston College
- ?Boston College - Carroll School of Management
- ?State Street Corporate
Strategy in a nutshell
The paper shows how media narratives influence financial markets by analyzing over 150,000 daily news articles. Articles are tagged by topic, asset, sentiment, and narrative intensity. Changes in narrative intensity—such as “Market Crash,” “Trade War,” or “COVID-19”—are tracked and linked to market movements using regression analysis. The authors find that negative media coverage, especially of the “Market Crash” narrative, strongly coincides with lower stock returns. They also demonstrate that narrative-based signals can predict future returns and improve strategies, such as rotating out of equities during periods of abnormally high crash coverage or building narrative-sensitive portfolios like the COVID-19 recovery portfolio.
Economic rationale
The rationale is that narratives shape investor behavior and market outcomes, even though they are intangible. By quantifying them with natural language processing, the authors show that narratives contain predictive information for asset prices. Using these signals, investors can build better asset allocation strategies and portfolios. The success of strategies like the COVID-19 recovery portfolio proves that narratives are powerful drivers of markets and can be systematically harnessed for investment decisions.