The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
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.
Lately, many notorious financial distress and bankruptcy events occurred in the world economic. As we known, bankruptcy of Lehman Brothers Holdings Inc. (LEH) is the largest bankruptcy filing in U.S. history in 2008. These events have serious impacted on the socio-economic and investment in public wealth. Due to solve this dilemma, this research collected 68 listed companies as the raw data from Taiwan...
In the predicting financial distress, we know that irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper use rough sets as a preprocessor of SVR to select a subset of input variables and employ the particle swarm optimization algorithm (PSOA) to optimize...
In the analysis of predicting financial distress based on support vector regression (SVR), irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper used rough sets as a preprocessor of SVR to select a subset of input variables and employed the immune clone...
In this paper, we applied culture particle swarm optimization algorithm (CPSO) to optimize the parameters of SVM. Utilizing the colony aptitude of particle swarm and the ability of conserving the evolving knowledge of the culture algorithm, this CPSO algorithm constructed the population space based on particle swarm and the knowledge space. The two spaces evolved independently, at the same time, the...
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...
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 genetic algorithm (CGA) to optimize the parameters of SVM. Through embedding GA into the cultural algorithm...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.