8,507 research outputs found
Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress
Recently, applying the novel data mining techniques for evaluating enterprise
financial distress has received much research alternation. Support Vector
Machine (SVM) and back propagation neural (BPN) network has been applied
successfully in many areas with excellent generalization results, such as rule
extraction, classification and evaluation. In this paper, a model based on SVM
with Gaussian RBF kernel is proposed here for enterprise financial distress
evaluation. BPN network is considered one of the simplest and are most general
methods used for supervised training of multilayered neural network. The
comparative results show that through the difference between the performance
measures is marginal; SVM gives higher precision and lower error rates.Comment: 13 pages, 1 figur
RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE
In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets. The risk analysis and asset allocation are the key technology of banking and risk management. The aim of this paper, build a loan portfolio optimization model based on risk analysis. Loan portfolio rate of return by using Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank. In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm. This paper solves the highly difficult problem by matrix operation method. Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space. It is easy calculation in proposed method
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