GARCH.rar_The Family_garch

#garchSim（）和garchFit（） #omega - the constant coefficient of the variance equation, by default 1e-6; #alpha - the value or vector of autoregressive coefficients, by default 0.1, specifying a model of order 1; #beta - the value or vector of variance coefficients, by default 0.8, specifying a model of order 1; #The optional values for the linear part are: #mu - the intercept value, by default 0 (it implies that the mean = mu/(1-sum(ar))); #ar - the autoregressive ARMA coefficients, by default 0; #ma - the moving average ARMA coefficients, by default 0. getwd() source("Igarch.R") source("GarchM.R") mm=Igarch(x$log.return,include.mean=F,volcnt=F) sresi=x$log.return/mm$volatility pacf(sresi) pacf(sresi**2) mm1=garchM(x$log.return,type=2) mm=garchM(sp5,type=2) #------------------------------------------------------------------------# library(rugarch) ?rugarch ?ugarchspec ?ugarchfit #-------------------------------------------------------------------------# myspec=ugarchspec(variance.model = list(model = "fGARCH", garchOrder = c(1,1), submodel = "GARCH", external.regressors = NULL, variance.targeting =FALSE), mean.model = list(armaOrder = c(2,2), include.mean = TRUE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "ged") myfit=ugarchfit(myspec,data=x$log.return,solver="solnp") myfit res=residuals(myfit) sigma=sigma(myfit) fit=fitted(myfit) sres=residuals(myfit,standardize=T)#or sres=res/sigma for(ii in 1:15) print(Box.test(sres**2,ii,"Ljung")) ArchTest(sres) pred3=ugarchforecast(myfit,n.ahead=100) plot(fitted(pred3),type="l") plot(myfit) #------------------------------------------------------------------------# myspec=ugarchspec(variance.model = list(model = "iGARCH", garchOrder = c(1,1), submodel = NULL, external.regressors = NULL, variance.targeting = 0), mean.model = list(armaOrder = c(3,3), include.mean =FALSE , archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "ged") myfit1=ugarchfit(myspec,data=x$log.return,solver="solnp") myfit1 sres1=residuals(myfit1,standardize=T) for(ii in 1:30) print(Box.test(sres1,ii,"Ljung")) #-------------------------------------------------------------------------# myspec=ugarchspec(variance.model = list(model = "fGARCH", garchOrder = c(1,1), submodel = "GARCH", external.regressors = NULL, variance.targeting =0), mean.model = list(armaOrder = c(3,3), include.mean =TRUE , archm = TRUE, archpow = 2, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "ged") ##archm Whether to include ARCH volatility in the mean regression. ##archpow Indicates whether to use st.deviation (1) or variance (2) in the ARCH in mean regression. myfit2=ugarchfit(myspec,data=x$log.return,solver="solnp") myfit2 sres2=residuals(myfit2,standardize=T) for(ii in 1:30) print(Box.test(sres2,ii,"Ljung")) #-------------------------------------------------------------------------# myspec=ugarchspec(variance.model = list(model = "eGARCH", garchOrder = c(1,1), submodel = NULL, external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder = c(0,0), include.mean = TRUE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "ged") myfit3=ugarchfit(myspec,data=x$log.return,solver="solnp") myfit3 sres3=residuals(myfit3,standardize=T) for(ii in 1:30) print(Box.test(sres3,ii,"Ljung")) ##LOG(GARCH) = -0.1623325008 + 0.1310836286*ABS(RESID(-1)/@SQRT(GARCH(-1))) - 0.0001938796244*RESID(-1)/@SQRT(GARCH(-1)) + 0.9920272489*LOG(GARCH(-1)) ##R中默认的egarch模型的形式是什么？？？ #--------------------------------------------------------------------------# myspec=ugarchspec(variance.model = list(model = "fGARCH", garchOrder = c(1,1), submodel = "TGARCH", external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder = c(3,3), include.mean = TRUE, archm =FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "std") myfit4=ugarchfit(myspec,data=x$log.return,solver="solnp") myfit4 sres4=residuals(myfit4,standardize=T) for(ii in 1:30) print(Box.test(sres4,ii,"Ljung"))