Resolving the forecasting problems of overshoot and volatility clustering using ANFIS coupling nonlinear heteroscedasticity with quantum tuning
type: Item
instance of: scholarly article
title: Resolving the forecasting problems of overshoot and volatility clustering using ANFIS coupling nonlinear heteroscedasticity with quantum tuning
author: Bao Rong Chang
published in: Fuzzy Sets and Systems
publication date: 2009-08-28T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 5599511
zbMATH Keywords: time-series prediction
zbMATH Keywords: ANFIS/NGARCH composite model
zbMATH Keywords: quantum minimization
zbMATH Keywords: quantum amplitude amplification
zbMATH Keywords: volatility clustering
zbMATH Keywords: nonlinear heteroscedasticity
describes a project that uses: ANFIS
MaRDI profile type: Publication
full work available at URL: j.fss.2008.04.003
OpenAlex ID: W1992846411
cites work: Generalized autoregressive conditional heteroscedasticity
cites work: Q3364404
cites work: Q4862306
cites work: Q4819589
cites work: Applying nonlinear generalized autoregressive conditional heteroscedasticity to compensate ANFIS outputs tuned by adaptive support vector regression
cites work: Control problems of grey systems
cites work: Rapid solution of problems by quantum computation
cites work: The solution of dynamic linear rational expectations models
cites work: Q4226179
cites work: Q4228473
cites work: Q4840212
cites work: On a measure of lack of fit in time series models
cites work: Q2706552
cites work: Q4692920
cites work: Q4289663
DOI: 10.1016/J.FSS.2008.04.003
description: scientific article; zbMATH DE number 5599511