Narrative Digital Finance
Research in business and management has increasingly begun to recognize the role that narratives play in guiding individual and collective decision-making.
Factsheet
- Schools involved Business School
- Institute(s) Institute for Applied Data Science & Finance
- Research unit(s) Finance, Accounting and Tax
- Funding organisation SNSF
- Duration (planned) 01.07.2023 - 30.06.2026
- Head of project Prof. Dr. Jörg Robert Osterrieder
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Project staff
Prof. Dr. Jörg Robert Osterrieder
Prof. Dr. Branka Hadji Misheva
Prof. Dr. Christian Hopp
Yiting Liu
Lennart John Baals
Gabin Taibi - Keywords DigitalFinance, structuralBreaks, financialmarkets, machineLearning, experimentalResearch, language, Narratives
Situation
Research in economics and management has begun to embrace the role that narratives play in guiding individual and collective decision- making. McCloskey (2011) describes unforeseen growth in economic development yet goes on to explain that no economic theory is able to capture this extent. She argues that a change in rhetoric had basically freed a social class (the bourgeoisie) and given it a sense of dignity and liberty. As such, economic change, she argues, depends to a great extent on social narratives that shape ideas and the beliefs of people. Yet, despite the notion that narratives, individual and collective actions, and market outcomes are inextricably linked, our knowledge about the mechanisms or processes through which they interact and how narratives can inform opinions or sway current thinking is still evolving. Entrepreneurs, for example, may use verbal communication to achieve plausibility (i.e., generate the sense that a given interpretation of events appears acceptable) or resonance (i.e., obtain alignment with the beliefs of the target audience; see van Werven et al., 2019). They may do so through rhetoric such as storytelling (Navis & Glynn, 2011) or crafting compelling arguments (van Werven et al., 2015) as well as employing combinations of figurative language and gesturing (Clarke et al., 2021) as they manage and conform with the expectation of their audience.
Course of action
We will extend quantitative research through novel measurement techniques, the creation of new data sets, offering new solutions towards prediction problems, and the induction of new theories. We will also contribute to recent works that demonstrated the potential of theoretical and methodological advancements through the application of machine learning in the research practice. In pursuit of both practical 'relevance' of our research and the contribution of "AI-integrated" research, our approach will provide actionable insights.
Looking ahead
The relevance of studying narratives in the financial sector can hardly be overstated, especially in light of the rapid developments in AI and data processing. The use of text data like Twitter feeds, financial news, and social media allows for a nuanced real-time view of the market. Text mining and Natural Language Processing (NLP) open up new possibilities for early detection of public sentiment and trends, thereby predicting market movements. Insights into structural changes in financial time series are also of great importance. They emphasize the need to develop flexible models that can respond to unexpected market changes. This is particularly true for detecting asset price bubbles and adjusting risk management strategies. The role of narratives in this context should not be underestimated. People strongly react to stories, and these can greatly influence economic decisions, whether in the fields of marketing, education, or philanthropy. A deep understanding of the interaction between narratives and financial markets could therefore be an important step in developing more effective financial models.
