Evolution of Financial Studies Over Forty Years: What Can We Learn from Machine Learning?

56 Pages Posted: 27 Mar 2018

See all articles by Po-Yu Liu

Po-Yu Liu

The University of Hong Kong - Faculty of Business and Economics

Zigan Wang

The University of Hong Kong - School of Economics and Finance; Columbia University

Date Written: March 27, 2018

Abstract

How did the finance research topics evolve in the past forty years? We apply machine learning models of textual analysis on 20,185 abstracts of finance articles published between 1976 and 2015, and identify 38 research topics. We present the fastest growing topics of published and working papers. Our algorithm can be used to categorize the articles without JEL codes. We use citation network to present how topics are related, and cluster the topics in five “territories”. Moreover, we find a strong bibliometric regularity: the number of researchers covering n topics is approximately 1/2^n of those covering just one topic.

Keywords: Textual Analysis, Machine Learning, Network Analysis, Evolution of Financial Studies

JEL Classification: G00, G10, G20, G30, B26

Suggested Citation

Liu, Po-Yu and Wang, Zigan, Evolution of Financial Studies Over Forty Years: What Can We Learn from Machine Learning? (March 27, 2018). Available at SSRN: https://ssrn.com/abstract=3150224 or http://dx.doi.org/10.2139/ssrn.3150224

Po-Yu Liu

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China
64706505 (Phone)

Zigan Wang (Contact Author)

The University of Hong Kong - School of Economics and Finance ( email )

8th Floor Kennedy Town Centre
23 Belcher's Street
Kennedy Town
Hong Kong

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

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