Comment coder selon S

##########################1

##1




sharperatio<-function(r,rf){
sr<-(mean(r)-mean(rf))/sd(r)
return(sr)
}

##2

covars<-function(x){
M<-t(matrix(colMeans(x),ncol(x), nrow(x)))
return(t(x-M)%*%(x-M)/(nrow(x)-1))
}

covars(X)


##3

portret<-function(w,x){t(w)%*%r}
portsig<-function(w,x){
sqrt(t(w)%*%covars(x)%*%w)
}


##4
install.packages("tseries")
library("tseries")


GetData<-function(x){
get.hist.quote("x",quote="Close", compression="m", start="2000-01-01")
}

##5
Code.R<-{
FC<-read.csv(file=file.choose(), header=TRUE)
MKT<-FC$MKT
SMB<-FC$SMB
ss<-sharperatio(MKT,SMB)
A<-paste("le ratio de sharpe est:",ss, sep="")
print(A)
}


##################2

##1
BMW<-GetData("BMW.DE")
TEL<-GetData("TEF.MC")
LOR<-GetData("OR.PA")
UNI<-GetData("UNA.AS")
UNICRED<-GetData("UCG.MI")
EUROSTOX<-GetData("^STOXX50E")
FCT<-read.csv(file=file.choose(),header=TRUE)
head(FCT)

##2

class(FCT)
FCT<-as.matrix(FCT)

RBMW<-diff(log(BMW))
RTEL<-diff(log(TEL))
RLOR<-diff(log(LOR))
RUNI<-diff(log(UNI))
RUNICRED<-diff(log(UNICRED))
REUSTOX<-diff(log(EUROSTOX))

stocks<-cbind(RBMW,RTEL,RLOR,RUNI,RUNICRED,REUSTOX)
head(stocks)
class(stocks)

stocks<-as.matrix(stocks)

install.packages('zoo')
library('zoo')

stocks<-na.locf(stocks)

##3

install.packages("Quandl")
library("Quandl")


#code quandl
RF<-RF[order(RF[,1]),]
RF[,2]<-RF[,2]/100

prime-actif<-stocks-RF[,2]

capm1<-lm(prime-actif[,2]~prime-actif[,6])
capm2<-lm(prime-actif[,3]~prime-actif[,6])
capm3<-lm(prime-actif[,4]~prime-actif[,6])
capm4<-lm(prime-actif[,5]~prime-actif[,6])
capm5<-lm(prime-actif[,1]~prime-actif[,6])

summary(capm1)
summary(capm1)$r.squared

##4


ff<-lm(prime-actif~FCT)

summary(ff)
FF <- get.hist.quote("FFIDX",quote="Close",start="2001-01-01")
plot(FF)


#Vérifier la classe et le type de données des variables {FF} et {Factors}.
class(stocks)
class(FCT)

#Estimer un modèle de Fama-French à 3 facteurs
FCT <- zoo(FCT,order.by=as.Date(rownames(FCT)))
plot(FCT,type='l')
FCT$MktRf <- FCT$Mkt-FCT$RF #A vérifier si c'est nécessaire!

DF <- FCT #Juste un nom plus court pour ce data frame

summary(reg <- lm(DF$FFund~DF$MktRf+DF$SMB+DF$HML))

##5
CAPM<-as.matric(summary(capm1)$coefficients,summary(capm1)$r.squared
FF<-cbind(summary(fama)$coefficients,summary(fama)$r.squared)

######################3

##1


install.packages("stats")
library("stats")

install.packages("urca")
library("urca")



CAC<-GetData("^FCHI")

DLCAC<-diff(log(CAC))
head(DLCAC)

##2

acf(CAC)
pacf(CAC)

acf(LCAC)
pacf(LCAC)
?ur.df

summary(ur.df(CAC, type ="trend", lags = 1, selectlags = c("Fixed", "AIC", "BIC")))
summary(ur.df(CAC, type ="drift", lags = 1, selectlags = c("Fixed", "AIC", "BIC")))
summary(ur.df(CAC, type ="none", lags = 1, selectlags = c("Fixed", "AIC", "BIC")))

summary(ur.df(CAC))
summary(ur.df(LCAC))


##3
AR<-arima(LCAC,c(1,0,0))
AR
MA<-arima(LCAC,c(0,0,1))
MA
ARMA<-arima(LCAC,c(1,0,1))
ARMA
ARMA22<-arima(LCAC,c(2,0,2))
ARMA12<-arima(LCAC,c(1,0,2))
ARMA21<-arima(LCAC,c(2,0,1))


####################4

##1


rstock1<-na.locf(rstock,na.rm =TRUE,fromLast=TRUE)
head(rstock1)

sup_na<-function(x){
for(j in 1:dim(x)[2]){
for(i in dim(x)[1]:1){
if (is.na(x[i,j])){x[i,j]<-x[i+1,j]}
}
}
return(x)
}

rstock2<-sup_na(rstock)


S<-cov(stocks2)


##2
install.packages("quadprog")
library("quadprog")


Dmat<-S #covariance

dvec<-as.matrix(colMeans(rstock2))##rdt
amat<-rbind(rep(1,5),diag(5))
Amat<-t(amat)##contrainte
bvec<-c(1,rep(0,5))
result<-solve.QP(Dmat,dvec,Amat,bvec,meq=1,factorized=FALSE)

results$solution

portret(results$solution,dvec)

ou
Amat <- rbind(rep(1,N),diag(N))
Amat

bvec <- matrix(c(1, rep(0,N)),4,1)
res <- solve.QP(SIGMA, RET, t(Amat), bvec, meq = 1)

##3

opt <- function(lambda){solve.QP(lambda*SIGMA, RET, t(Amat), bvec, meq = 1)$solution}

lambda <- seq(0.5,20,1)
lambda
L <- length(lambda)
Wopt <- t(sapply(lambda,opt))
Wopt

vol.port <- function(w,s){sqrt((t(w)%*%s)%*%w)}

ret.port <- function(w,r){t(w)%*%r}

RR <- array()
SS <- array()

for (l in seq(L)){
SS[l] <- vol.port(Wopt[l,],SIGMA)
RR[l] <- ret.port(Wopt[l,],RET)
}
RR
SS

plot(SS,RR,type="l")