Determinants of long-term institutional investors’ investment in South Korea: insights from a LASSO regression
Kiyoung Jeon,
Jangyoun Lee and
Seungduck Lee
Applied Economics Letters, 2025, vol. 32, issue 18, 2626-2631
Abstract:
This study examines the determinants of the decisions of long-term institutional investors on government bond investments in South Korea by performing a machine learning analysis, specifically, LASSO regressions. The analysis is based on a comprehensive set of financial and real variables spanning from 2004 to 2021. We consider 35 explanatory variables that are expected to influence the number of government bonds purchased by long-term institutional investors. Our analysis reveals that government bond investments of insurance companies and pension funds are driven by distinct factors. In the case of insurance companies, the purchase of government bonds with maturities exceeding five years is observed to be influenced by a wide range of factors, encompassing both domestic (e.g. core inflation) and global (e.g. US T-bill yield) influences. Conversely, much less significant determinants were found for investments of pension funds, implying that Korean pension funds have a pre-established and inflexible approach.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2024.2337324 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apeclt:v:32:y:2025:i:18:p:2626-2631
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20
DOI: 10.1080/13504851.2024.2337324
Access Statistics for this article
Applied Economics Letters is currently edited by Anita Phillips
More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().