Working Paper: NBER ID: w28615
Authors: Itay Goldstein; Chester S. Spatt; Mao Ye
Abstract: Big data is revolutionizing the finance industry and has the potential to significantly shape future research in finance. This special issue contains articles following the 2019 NBER/ RFS conference on big data. In this Introduction to the special issue, we define the “Big Data” phenomenon as a combination of three features: large size, high dimension, and complex structure. Using the articles in the special issue, we discuss how new research builds on these features to push the frontier on fundamental questions across areas in finance – including corporate finance, market microstructure, and asset pricing. Finally, we offer some thoughts for future research directions.
Keywords: big data; finance; machine learning; corporate finance; market microstructure; asset pricing
JEL Codes: G12; G14; G3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| big data characteristics (large size, high dimensionality, complex structure) (C55) | exploration of new questions and methodologies in finance (B26) |
| integration of machine learning techniques (C45) | better analysis of complex interactions within financial data (C38) |
| machine learning techniques (C45) | outperform traditional statistical approaches in predicting outcomes (C52) |
| machine learning (C45) | identify agency conflicts (D82) |
| unstructured data (processed correctly) (C55) | significant insights into corporate culture (M14) |
| corporate culture (M14) | impact on firm performance (L25) |