kernel regression context, we derive the limit distribution of the SIMEX estimate. With the regression spline technique, two … different methods of estimations are used. The first method is the SIMEX algorithm which attempts to estimate the bias, and …

Vector Machines (SVM) for financial data. The financial series are fitted into a family of Asymmetric Power ARCH (APARCH … inefficient when the data distribution shows departure from normality, so the current paper utilizes the nonparametric-based SVM … method and shows that it is more efficient than the QML under the skewed Student's t-distributed error. As the SVM is a …

credit risk assessment models based on support vector machine (SVM) technique and BP neural network respectly. Results: (1 …) The SCF credit risk assessment model based on SVM is of good generalization ability and robustness, which is more … applying the SVM model, which can alleviate credit rationing on SMEs. Conclusions: (1)The SCF credit risk assessment index …

Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of … accuracy the SVM has a lower model risk than the Logit on average and displays a more robust performance. This result holds …

banks in order to measure their client's degree of risk, and for firms to operate successfully. The SVM with evolutionary … and probit models as benchmark On overall, GA-SVM is outperforms compared to the benchmark models in both training and …