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DOI: 10.14569/IJACSA.2020.0110222
PDF

A Robust Deep Learning Model for Financial Distress Prediction

Author 1: Magdi El-Bannany
Author 2: Meenu Sreedharan
Author 3: Ahmed M. Khedr

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 2, 2020.

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Abstract: This paper investigates the ability of deep learning networks on financial distress prediction. This study uses three different deep learning models, namely, Multi-layer Perceptron (MLP), Long Short-term Memory (LSTM) and Convolutional Neural Networks (CNN). In the first phase of the study, different Optimization techniques are applied to each model creating different model structures, to generate the best model for prediction. The top results are presented and analyzed with various optimization parameters. In the second phase, MLP, the best classifier identified in the first phase is further optimized through variations in architectural configurations. This study investigates the robust deep neural network model for financial distress prediction with the best optimization parameters. The prediction performance is evaluated using different real-time datasets, one containing samples from Kuwait companies and another with samples of companies from GCC countries. We have used the technique of resampling for all experiments in this study to get the most accurate and unbiased results. The simulation results show that the proposed deep network model far exceeds classical machine learning models in terms of predictive accuracy. Based on the experiments, guidelines are provided to the practitioners to generate a robust model for financial distress prediction.

Keywords: Financial distress prediction; multi-layer perceptron; long short-term memory; convolutional neural network; deep neural network; optimized deep learning model

Magdi El-Bannany, Meenu Sreedharan and Ahmed M. Khedr, “A Robust Deep Learning Model for Financial Distress Prediction” International Journal of Advanced Computer Science and Applications(IJACSA), 11(2), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110222

@article{El-Bannany2020,
title = {A Robust Deep Learning Model for Financial Distress Prediction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110222},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110222},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {2},
author = {Magdi El-Bannany and Meenu Sreedharan and Ahmed M. Khedr}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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