Narrow search
Showing 1 - 10 of 10
Cover Image
Estimation of default probabilities with Support Vector Machines
Chen, Shiyi; Härdle, Wolfgang Karl; Moro, Rouslan A. - 2006
propose the so called Support Vector Machine (SVM) to estimate default probabilities of German firms. Our analysis is based on … classifying ability of SVM appears to be superior over a wide range of the SVM parameters. Based on the nonparametric Nadaraya …-Watson estimator, the expected returns predicted by the SVM for regression have a significant positive linear relationship with the …
Persistent link: https://www.econbiz.de/10010274122
Cover Image
Support vector regression based GARCH model with application to forecasting volatility of financial returns
Chen, Shiyi; Jeong, Kiho; Härdle, Wolfgang Karl - 2008
In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...
Persistent link: https://www.econbiz.de/10010274143
Cover Image
Recurrent support vector regression for a nonlinear ARMA model with applications to forecasting financial returns
Chen, Shiyi; Jeong, Kiho; Härdle, Wolfgang Karl - 2008
Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns Abstract: Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data...
Persistent link: https://www.econbiz.de/10010274149
Cover Image
Support vector regression based GARCH model with application to forecasting volatility of financial returns
Chen, Shiyi (contributor); Jeong, Kiho (contributor);  … - 2008
In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...
Persistent link: https://www.econbiz.de/10003636113
Cover Image
Recurrent support vector regression for a nonlinear ARMA model with applications to forecasting financial returns
Chen, Shiyi (contributor); Jeong, Kiho (contributor);  … - 2008
Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns Abstract: Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data...
Persistent link: https://www.econbiz.de/10003770766
Cover Image
Estimation of default probabilities with Support Vector Machines
Chen, Shiyi (contributor); Härdle, Wolfgang (contributor);  … - 2006
propose the so called Support Vector Machine (SVM) to estimate default probabilities of German firms. Our analysis is based on … classifying ability of SVM appears to be superior over a wide range of the SVM parameters. Based on the nonparametric Nadaraya …-Watson estimator, the expected returns predicted by the SVM for regression have a significant positive linear relationship with the …
Persistent link: https://www.econbiz.de/10003402291
Cover Image
Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns
Chen, Shiyi - 2016
Motivated by recurrent neural networks, this paper proposes a recurrent support vector regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR based ARMA model is compared with five...
Persistent link: https://www.econbiz.de/10012997751
Cover Image
Estimation of Default Probabilities with Support Vector Machines
Chen, Shiyi - 2017
propose the so called Support Vector Machine (SVM) to estimate default probabilities of German firms. Our analysis is based on … inventories. Based on the performance measures, the SVM tool can predict a firms default risk and identify the insolvent firm more … classifying ability of SVM appears to be superior over a wide range of the SVM parameters. Based on the nonparametric Nadaraya …
Persistent link: https://www.econbiz.de/10012966238
Cover Image
Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns
Chen, Shiyi - 2017
In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a...
Persistent link: https://www.econbiz.de/10012966267
Cover Image
Estimation of Default Probabilities with Support Vector Machines
Chen, Shiyi; Härdle, Wolfgang; Moro, Rouslan - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2006
propose the so called Support Vector Machine (SVM) to estimate default probabilities of German firms. Our analysis is based on … inventories. Based on the performance measures, the SVM tool can predict a firms default risk and identify the insolvent firm more … classifying ability of SVM appears to be superior over a wide range of the SVM parameters. Based on the nonparametric Nadaraya …
Persistent link: https://www.econbiz.de/10005677958