Title :
Analyzing financial distress of listed companies using neural network
Author :
Wang, Qiang ; Yang, Qian ; Zhang, Miaomiao
Author_Institution :
Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
Abstract :
Corporation financial distress has been an important issue for study in the financial fields. This paper uses traditional BP neural network model and proposes PNN model to predicate financial distress. The sample consists of 276 companies listed on the Shanghai Stock Exchange and Shenzhen Stock Exchange over the period 2001-2010. Factor analysis is used to lower correlation and reduce dimensionality. The results demonstrate that the PNN model has higher explanatory power in predicating financial distress than BPN model.
Keywords :
backpropagation; financial data processing; neural nets; probability; BP neural network model; Shanghai Stock Exchange; Shenzhen Stock Exchange; corporation financial distress; factor analysis; financial distress predication; financial field; listed companies; probabilistic neural network; Accuracy; Companies; Mathematical model; Neural networks; Predictive models; Probabilistic logic; Training; BP neural network; Financial predication; Probabilistic Neural Network;
Conference_Titel :
System Science, Engineering Design and Manufacturing Informatization (ICSEM), 2012 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0914-1
DOI :
10.1109/ICSSEM.2012.6340809
