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In today's competitive environment, having a customer oriented approach is inevitable for organizations. At this point, in order to achieve customer satisfaction, customer relationship management (CRM) targets to provide products and services which meet customer expectation. Data which is collected about customers is an important source to determine their needs. Therefore, analysis is made to determine...
This paper presents the construction of the ProfileSEEKER the information system for early warning small and medium-sized enterprises from bankruptcy. The developed system is a set of five classifiers, using a variety of topologies of artificial neural networks and Bayes belief network, supported by supervised machine learning methods. System performance was evaluated using the original validation,...
This paper discusses the second-order mining of the results of data mining. There is still gap between the knowledge which can direct the operation of company and the knowledge got from data mining. We take the knowledge from data mining as primary knowledge and the knowledge from second-order data mining as intelligent knowledge. We discuss the importance of intelligent knowledge and the way to find...
It is the most important to effectively conduct enterprise credit evaluation in the issuing process of relationship lending. As Chinese market economy is not developed, the current enterprise credit evaluation model in developed countries can only serve as a reference instead of being completely imitated. The enterprise loan signaling game model proposed by domestic scholars gives consideration to...
From a new view of financial distress concept drift, this paper attempts to put forward a new method for dynamic financial distress prediction modeling based on slip time window and multiple support vector machines (SVMs). A new algorithm is designed to dynamically select the proper time window to handle concept drift, and then a dynamic classifier selection method is used to build a combined model...
In order to analyze the basic characteristics of cash-flow of the enterprise, this paper establishes the cash flow system dynamic model of the listed companies using system dynamics method and uses the model to carry out the dynamic simulation and control the real-time cash flow data of the enterprise, besides, designs different modes consisting of different parameters to simulate the enterprise's...
In China, men study the market risk of open-end funds less than the close-end funds. In fact, the risk of open-end funds of China is significantly high. So, in order to make sure the stability and validity, using the methods of structure MONTE CARLO and Normal-GARCH, the author makes a Comparative research empirically of the Market Risk of the open-end funds of china basing on the model of VaR and...
The recent studies on financial distress are mostly confined to static econometric or statistical methods based on cross-sectional financial data ,and it is ignored that the variation of companies' financial status is a dynamic process. In order to show the change of companies in financial position, this study constructed the financial distress prediction model based on panel logit. On the selection...
This paper use Microsoft SQL Server 2005 data mining tools and three methods of neural networks, decision trees and logistic regression to establish the financial crisis early-warning model of listed companies. The conclusion is that the three kinds of methods have good results and the prediction accuracy rate are 80% or more. The accuracy of the decision tree algorithm model is higher than others.
Based on a lot of related literatures, the authors suggest a Financial Distress Prediction System incorporated the Expected Default Frequency (EDF) into Logit regression model. The empirical findings suggest that the EDF calculated by KMV model is significantly associated with the probability of default in both 3rd and 4th quarters prior to the financial crisis of sample firms. Thus, an incorporation...
In this paper, we propose a new estimation method for the parameters of a multivariate Markov chain model. In the new method, we calculate the correlations of the sequences first and establish multivariate Markov chain models for those positively correlated sequences. The parameters are estimated by minimizing the error of prediction. We apply the method to demand predictions for a soft-drink company...
This paper applies DEA model to a sample of 58 power plate listed companies in the securities market in China in 2008, with a view to identifying the financial risk companies and non-financial risk companies, instead of using ST in the past. Then, after comparing logit regression model and neural network LVQ in predicting the company financial risks, the conclusion was drawn that neural network LVQ...
Financial distress is the most synthetic form of business crisis and financial distress prediction (FDP) has been a widely and continually studied topic in the field of corporate finance. This paper attempts to put forward OR-CBR in K-nearest neighbors model, which can be the implementation of corresponding algorithm.
This paper compares the early-warning model of financial crisis home and abroad, using multiple logistic regression method to build an early warning model for enterprise financial crisis in e-commerce environment. Test results show that the model can accurately estimate the samples, and help control the samples. The accuracy rate of discriminate analysis of the model shows that the model has a good...
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,...
Credit risk management has become a fundamental and crucial work for commercial banks. This paper studies the credit risk measurement of listed corporations by using various types of credit risk models, and analyzes their applicability in China. This paper also makes an empirical analysis to the Chinese listed corporations’ credit risk on the basis of the KMV model. Finally, several proposals on how...
Companies in financial distress make the creditors, shareholders, employees, investors and other participants of the related firms suffer great losses. In order to prevent the companies run into bankruptcy, financial distress prediction has been a useful tool for distinguishing companies in financial distress from those healthy. Statistical methods and artificial intelligence techniques have been...
In the case of full circulation of stocks, the ratio "the total market value of stocks/total debt" introduced in financial crisis early warning model can improve the warning mechanism. Through setting up the early warning mechanism and improving data processing, the consequence of operating the early warning mechanism would forecast better the degree and probability of a financial crisis...
Prediction models provide investors preliminary information before bankruptcy. Prediction models based on classification technique distinguish a listed company between healthiness and bankruptcy in the most literature, but little attention has been paid to do the further discussion on the sequential analysis of classifications. To supplement this insufficiency, a mixture model of Support Vector Machine...
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