À繫¿¬±¸ Á¦ ±Ç È£ (2023³â 11¿ù)
Asian Review of Financial Research, Vol., No..
pp.1139~1156
pp.1139~1156
An Ensemble Based Default Forecasting Model for Economic Payoff Maximization
Seungyoo Jeon Ph.D. Candidate, Department of Financial Technology Convergence, Soongsil University
Chan Park Ph.D. Candidate, Department of Financial Technology Convergence, Soongsil University
Kisung Yang Assistant Professor, Department of Finance, Soongsil University
This study addresses default prediction through ensemble techniques and cost-sensitive learning. It introduces a novel stacking method, focusing on instances with varying misclassification costs. Previous research lacks this comprehensive approach, highlighting a research gap. The proposed technique proves advantageous in terms of economic payoff and performance, offering practical utility. It complies with regulatory monitoring standards without incurring statistical cost penalties. This study demonstrates potential revenue gains even without precise cost ratios. Empirical results using Taiwanese company bankruptcy data (1999-2009, 95 financial ratios) reveal significant outcomes. Firstly, the proposed algorithm markedly improves economic payoff. Secondly, its statistical performance remains unaffected, even considering the dependency on overall prediction errors related to misclassifying defaults. Lastly, the method is computationally efficient, robust across cost scenarios.
Seungyoo Jeon
Chan Park
Kisung Yang
This study addresses default prediction through ensemble techniques and cost-sensitive learning. It introduces a novel stacking method, focusing on instances with varying misclassification costs. Previous research lacks this comprehensive approach, highlighting a research gap. The proposed technique proves advantageous in terms of economic payoff and performance, offering practical utility. It complies with regulatory monitoring standards without incurring statistical cost penalties. This study demonstrates potential revenue gains even without precise cost ratios. Empirical results using Taiwanese company bankruptcy data (1999-2009, 95 financial ratios) reveal significant outcomes. Firstly, the proposed algorithm markedly improves economic payoff. Secondly, its statistical performance remains unaffected, even considering the dependency on overall prediction errors related to misclassifying defaults. Lastly, the method is computationally efficient, robust across cost scenarios.
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