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Financial decisions are difficult because of complex unpredictable factors but play critical role in financial activities. In this paper, we investigate the decision making problems and applied methods by considering different categories of financial ratios as input to the CGA-LSSVM model, which with we present a framework for the financial decision support system.
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,...
Neural networks (NNs) have been widely used to predict financial distress because of their excellent performances of treating non-linear data with self-learning capability. However, the shortcoming of NNs is also significant due to a ldquoblack boxrdquo syndrome. Moreover, in many situations NNs more or less suffer from the slow convergence and occasionally involve in a local optimal solution, which...
Neural networks (NNs) have been widely used to predict financial distress because of their excellent performances of treating non-linear data with self-learning capability. However, common neural networks often suffer from long convergent processes and occasionally involve in a local optimal solution that more or less limited their applications in practice. To overcome the drawbacks of neural networks,...
In the analysis of predicting financial distress based on support vector machine (SVM), the two parameters of SVM, c and sigma, which its value have important effect on the predicting accuracy, must be predetermined carefully. In order to solve this problem, this paper proposed a new culture particle swarm optimization algorithm (CPSO) to optimize the parameters of SVM. Utilizing the colony aptitude...
Recent outbreak of corporate financial crises worldwide has brought attention to the need for a new international financial architecture which rests on crisis prediction and crisis management. Financial data have been widely used by researchers to predict financial crisis, but few studies exploit the use of non-financial indicators in corporate governance to construct financial crisis prediction model...
This paper puts forwards a classifier hybridizing rough sets (RSs) and wavelet support vector machine (WSVM). Rough sets method is used as a preprocessor to select the subset of input variables. Then a method that generates wavelet kernel function of the SVM is proposed based on the theory of wavelet frame and the condition of the SVM kernel function. The Mexican Hat wavelet is selected to construct...
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