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Investment Analysts Journal Volume 50, 2021 - Issue 3
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Articles

Predicting corporate defaults using machine learning with geometric-lag variables

Hyeongjun Kima Department of Business Administration, Yeungnam University, Gyeongsan, KoreaORCID Iconhttps://orcid.org/0000-0003-0386-005X
ORCID Icon,
Hoon Chob College of Business, Korea Advanced Institute of Science and Technology, Seoul, KoreaORCID Iconhttps://orcid.org/0000-0003-2322-320X
ORCID Icon &
Doojin Ryuc College of Economics, Sungkyunkwan University, Seoul, KoreaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-0059-4887
ORCID Icon
Pages 161-175 | Received 10 Dec 2020, Accepted 07 Jun 2021, Published online: 27 Aug 2021

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Hyeongjun Kim, Hoon Cho & Doojin Ryu. (2023) Measuring corporate failure risk: Does long short-term memory perform better in all markets?. Investment Analysts Journal 52:1, pages 40-52.
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Articles from other publishers (3)

Yihwan Kim, Hyeongjun Kim, Doojin Ryu & Hoon Cho. (2022) A Study on Apartment Sales Price Index Using Machine Learning Methodology. Journal of Real Estate Analysis 8:3, pages 1-29.
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Desheng Wu, Xiyuan Ma & David L. Olson. (2022) Financial distress prediction using integrated Z-score and multilayer perceptron neural networks. Decision Support Systems 159, pages 113814.
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Dohyun Chun, Hoon Cho & Doojin Ryu. (2022) Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios. SSRN Electronic Journal.
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