Bankruptcy Prediction of Privately Held SMEs Using Feature Selection Methods
نویسندگان
چکیده
In this paper, we test alternative feature selection methods for bankruptcy prediction and illustrate their superiority versus popular models used in the literature. We these using a comprehensive dataset of more than one million financial statements from privately held Norwegian SMEs 2006-2017. Our are allowed to choose among 155 accounting-based input variables derived prior find that chosen by an embedded least absolute shrinkage operator (LASSO) method yield best in-sample fit, out-of-sample performance, stability. findings robust discrete hazard with either deep artificial neural network (DNN) or logistic regression (LR) estimation hold across different time periods. show simulation which mimics real-world competitive credit market LASSO predictors improves risk pricing decision making, resulting significantly higher bank profits.
منابع مشابه
Bankruptcy Prediction Using Feature Projection
Bankruptcy prediction has been an important decision-making process for nancial analysts. One of the most common approaches for the bankruptcy prediction problem is the Discrim-inant Analysis. Also, the k-Nearest Neighbor classiier is very successful in such domains. This paper proposes a Feature Projection based classiication algorithm, and explores its applicability to the problem of predicti...
متن کاملFeature Selection for Bankruptcy Prediction: A Multi-Objective Optimization Approach
In this work a Multi-Objective Evolutionary Algorithm (MOEA) was applied for feature selection in the problem of bankruptcy prediction. This algorithm maximizes the accuracy of the classifier while keeping the number of features low. A two-objective problem, that is minimization of the number of features and accuracy maximization, was fully analyzed using the Logistic Regression (LR) and Suppor...
متن کاملFeature Selection for Bankruptcy Prediction: A Multi-Objective Optimization Approach
In this work a Multi-Objective Evolutionary Algorithm (MOEA) was applied for feature selection in the problem of bankruptcy prediction. This algorithm maximizes the accuracy of the classifier while keeping the number of features low. A two-objective problem, that is minimization of the number of features and accuracy maximization, was fully analyzed using the Logistic Regression (LR) and Suppor...
متن کاملThe Incorporation Choices of Privately Held Corporations
Exploiting a large new database, this article explores the incorporation choices of closely held U.S. corporations. The majority of corporations in our sample incorporate in the state in which their primary place of business (PPB) is located. However, among the corporations with 1000 or more employees, only about half incorporate in their PPB state, and of those that do not, more than half are ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Social Science Research Network
سال: 2021
ISSN: ['1556-5068']
DOI: https://doi.org/10.2139/ssrn.3911490