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This paper uses the global optimization of genetic algorithm to construct a genetic neural network model (GANN) forecasting listed company financial crisis. The model optimizes input variables of neural network model forecasting financial crisis. Forecasting of financial distress of listed companies in Shanghai and Shenzhen A share markets indicates that this model bears a better ability to predict...
Based on financial information of listed manufacturing companies, the research aims at predicting financial distress using the integrated model of factor analysis and discriminant analysis to establish the model, and tests the prediction accuracy of the model. The results show that the model in this paper has higher discriminant precision, and it makes further explanation that the choice of financial...
This paper samples 30 listed companies which were the first time to ST (special treatment) because of abnormal financial situation after the announcement of 2008 Annual Report. The paper sets out from the perspective of financial indicators, introduces a new indicator of "total stock market value / total liabilities", and establishes the financial distress alert model with the use of Binary...
Most scholars applied dichotomy to the company financial distress research, which classifies listed companies into two categories. We apply trisection method, which classifies listed companies into three categories: financial distress companies, financial unstable companies and financial healthy companies, and apply principal component analysis method and ternary Logistic model to construct a financial...
Western finance theory indicates that hedging increases firm value by reducing expected taxes, expected costs of financial distress, or other agency costs. This paper examines the use of financial derivatives for the purpose of risk management in a sample of 1151 China non-financial firms and its potential impacts on firm value and accounting performance. We find a positive relation between firm accounting...
This paper studies how to establish models for predicting financial distress in China's listed companies. We firstly select 26 companies with financial distress and 54 matching companies' panel data as samples, then use panel data model to conduct an empirical study. The research indicates that: (1) The predictability precision is 91.25%, 92.5%, 91.25% and 87.5% for T-1, T-2, T-3 and T-4, respectively,...
Uncertainties surrounding reverse logistics create the possibility that the retailer may be strained in meeting financial distress. The current research offers a Markov chain approach to build a random fluctuation model for the early-warning index and analyzes the financial risks stemming from retail reverse logistics activities. The worsened probability for the early-warning index can be inferred...
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