Abstract
The analysis of different data sources to support financial decision making has been a subject of research for several decades. While early approaches mostly focus on structured data, recent studies also take into account unstructured data. In this paper, we build upon these two research streams and explore potential benefits that can be achieved by combining both approaches. Therefore, we present an approach that integrates both data types. From a theoretical perspective, our research angle is based on two fundamental theories in Finance: while the Efficient Market Hypothesis states that capital markets are information efficient, Behavioral Finance theory stresses that market efficiency may be limited, e.g. due to irrational behavior of market participants or market barriers. While the two theories provide arguments for and against the functioning of our approach, we can illustrate its superiority compared to other approaches. The implications are discussed from a methodological and theoretical perspective.
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Siering, M., Muntermann, J. (2013). The Role of Misbehavior in Efficient Financial Markets: Implications for Financial Decision Support. In: Rabhi, F.A., Gomber, P. (eds) Enterprise Applications and Services in the Finance Industry. FinanceCom 2012. Lecture Notes in Business Information Processing, vol 135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36219-4_3
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DOI: https://doi.org/10.1007/978-3-642-36219-4_3
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