Work

Does accrual information impact municipal bond prices? Evidence from Japan using AI

Year: 2024

Type: article

Abstract: IMPACTThis article explains some aspects of the role of accrual-based information disclosed by local governments, which has been a subject of debate for some time. Using eXplainable AI (XAI), the authors demonstrate that accrual-based information is reflected in local government bond prices in Japan. The article has important findings for practitioners. The first is the pricing process for municipal bonds. This is useful for practices in municipal bond issuance and investment for financial instruments. The second is the applicability of machine learning in bond markets. The findings will also be useful to data scientists and public officers in local governments looking to create value through the use of machine learning (particularly XAI).

Source: Public Money & Management

DOI: 10.1080/09540962.2024.2392731

Authors: Kentaro Haraguchi, Yasuhiro Tamba, Daisuke Ikeda, Shuji Abe

Institutions: Seinan Gakuin University, Kyushu University, International Research Center for Space and Planetary Environmental Science, Kyushu University

Language: English

Topic: Credit Risk and Financial Regulations

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: Japan Society for the Promotion of Science

Awards: Hierarchical Sentiment Polarity Judgement and Explainability for Paragraphs and Sentences in Securities Reports, 地方債市場の発展のための要件に関する実証研究, Public Accounting Studies in Municipal Bond Market Using Machin Learning