library(stats)
library(tseries)
library(fSeries)
library(moments)
library(Rcmdr)
library(fGarch)


# entrada de dados
ibv<-indices$IBV
petro<-indices$PETROBRAS
banespa<-indices$BANESPA
cemig<-indices$CEMIG

# grafico das series
par(mfrow=c(4,1))
ts.plot(ibv)
ts.plot(petro)
ts.plot(banespa)
ts.plot(cemig)

# calculo dos log retornos

ribv<-diff(log(ibv),lag=1,differences=1)
rpetro<-diff(log(petro),lag=1,differences=1) 
rbanespa<-diff(log(banespa),lag=1,differences=1)
rcemig<-diff(log(cemig),lag=1,differences=1)

# graficos séries-log retornos

par(mfrow=c(4,2))
ts.plot(ibv)
ts.plot(ribv)
ts.plot(petro)
ts.plot(rpetro)
ts.plot(banespa)
ts.plot(rbanespa)
ts.plot(cemig)
ts.plot(rcemig)


# calculo das fac da série e do retorno
                                     
par(mfrow=c(4,2))
acf(ibv)
acf(ribv)
acf(petro)
acf(rpetro)
acf(banespa)
acf(rbanespa)
acf(cemig)
acf(rcemig)


#calculo das fac e facp dos log retornos

par(mfrow=c(4,2))
acf(ribv)
pacf(ribv)
acf(rpetro)
pacf(rpetro)
acf(rbanespa)
pacf(rbanespa)
acf(rcemig)
pacf(rcemig)

# ler conjunto de dados ibv (  dados de 1999 a 2008)

IBV<-IBV$Preço
rIBV<-diff(log(IBV),lag=1,differences=1)
par(mfrow=c(2,3))
ts.plot(ibv)
ts.plot(ribv)
acf(ribv)
ts.plot(IBV)
ts.plot(rIBV)
acf(rIBV)

# calculo da curtose e da`assimetria
skewness(ribv)
kurtosis(ribv)
skewness(rIBV)
kurtosis(rIBV)

skewness(ribv)
kurtosis(rpetro)
skewness(rpetro)
kurtosis(rbanespa)
skewness(rbanespa)


#ajuste de um modelo arma  usando o pacote   tseries

rpetromod<- arma(rpetro,order=c(9,0),include.intercept= TRUE)
summary(rpetromod)
rpetromod2<-arma(rpetro,lag=list(ar=c(1,3,6,9),ma=NULL))
summary(rpetromod2)
rpetromod2<-arma(rpetro,lag=list(ar=c(1,3,6,9),ma=NULL))
rpetromod3<-arma(rpetro,lag=list(ar=c(1,3,9),ma=NULL),include.intercept= FALSE)
summary(rpetromod3)
par(mfrow=c(2,1))
acf(residuals(rpetromod3)^2, na.action=na.remove)
pacf(residuals(rpetromod3)^2, na.action=na.remove)



# ajuste de um modelo usando o pacote  Stats  (não faz modelo reduzido)

rpetromod6<-arima(rpetro, order = c(9,0,0),include.mean = FALSE)
summary(rpetromod6)
coeficientes<-rpetromod6$coef
coeficientes
residuos<-rpetromod6$residuals
par(mfrow=c(2,1))
acf(residuos)
pacf(residuos)

tsdiag(rpetromod6)


  # ajuste de um modelo ARCH aos dados da Petrobras e Cemig
  
?garchFit
rpetromod1<- garchFit(~arma(10,0)+garch(1,1), rpetro,cond.dist = c("dnorm"),include.mean = TRUE)
summary(rpetromod1)
               
rcemigmod1<- garchFit(~arma(0,1)+garch(1,1), rcemig,cond.dist = c("dnorm"),include.mean = TRUE)
summary(rcemigmod1)                     
res <- rcemigmod1@residuals
desvpad <- rcemig@sigma.t
respad <- res/desvpad

rcemigmod2<- garchFit(~arma(0,1)+garch(1,1), rcemig,cond.dist = c("dnorm"),include.mean = FALSE)
par(mfrow=c(3,1))
ts.plot(respad)
acf(respad)
pacf(respad)

rcemigmod3<- garchFit(~arma(6,0)+garch(1,1), rcemig,cond.dist = c("dnorm"),include.mean = FALSE)
summary(rcemigmod3)

par(mfrow=c(3,1))
ts.plot(respad^2)
acf(respad^2)
pacf(respad^2)

qq.plot(respad)
skewness(respad)
kurtosis(respad)
hist(respad,prob=T,ylim=c(0,0.45),breaks=20)
x<-seq(-6,6,0.01)
lines(x,dnorm(x,mean=mean(respad),sd=sd(respad)),col=2)

fitg2<-garchFit(formula = ~arma(10,0)+ garch(1,1), leverage=TRUE,
    data = lribv, cond.dist = "dstd",include.mean = TRUE, standardize=T)

res <- fitg2@residuals
desvpad <- fitg2@sigma.t
respad <- res/desvpad

par(mfrow=c(3,1))
ts.plot(respad)
acf(respad)
pacf(respad)

par(mfrow=c(3,1))
ts.plot(respad^2)
acf(respad^2)
pacf(respad^2)

qq.plot(respad)
skewness(respad)
kurtosis(respad)
hist(respad,prob=T,ylim=c(0,0.45),breaks=20)
x<-seq(-6,6,0.01)
lines(x,dnorm(x,mean=mean(respad),sd=sd(respad)),col=2)

   
   rpetromod3<-arma(rpetro,lag=list(ar=c(1,3,9),ma=NULL),include.intercept= FALSE)
summary(rpetromod3)
par(mfrow=c(2,1))
acf(residuals(rpetromod3)^2, na.action=na.remove)
pacf(residuals(rpetromod3)^2, na.action=na.remove)

pacf(rpetro^2)




qq.plot(respad)
skewness(respad)
kurtosis(respad)
hist(respad,prob=T,ylim=c(0,0.45),breaks=20)
x<-seq(-6,6,0.01)
lines(x,dnorm(x,mean=mean(respad),sd=sd(respad)),col=2)

fitg2<-garchFit(formula = ~arma(10,0)+ garch(1,1), leverage=TRUE,
    data = lribv, cond.dist = "dstd",include.mean = TRUE, standardize=T)

res <- fitg2@residuals
desvpad <- fitg2@sigma.t
respad <- res/desvpad

par(mfrow=c(3,1))
ts.plot(respad)
acf(respad)
pacf(respad)

par(mfrow=c(3,1))
ts.plot(respad^2)
acf(respad^2)
pacf(respad^2)

qq.plot(respad)
skewness(respad)
kurtosis(respad)
hist(respad,prob=T,ylim=c(0,0.45),breaks=20)
x<-seq(-6,6,0.01)
lines(x,dnorm(x,mean=mean(respad),sd=sd(respad)),col=2)