TY - JOUR
T1 - Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine
AU - Santoso, Noviyanti
AU - Wibowo, Wahyu
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/3/13
Y1 - 2018/3/13
N2 - A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.
AB - A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.
UR - http://www.scopus.com/inward/record.url?scp=85044418137&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/979/1/012089
DO - 10.1088/1742-6596/979/1/012089
M3 - Conference article
AN - SCOPUS:85044418137
SN - 1742-6588
VL - 979
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012089
T2 - 2nd International Conference on Science, ICOS 2017
Y2 - 2 November 2017 through 3 November 2017
ER -