#BSɂvbgIvVi
dd1<-(log(1000/K)+(r+sigma^2/2))/sigma
dd2<-dd1-sigma
poc<-(-K*exp(-r)*pnorm(dd2)+1000*pnorm(dd1))*1000
count<-rep(0,100)
Y<-matrix(rep(1,1300),100,13)
S<-matrix(rep(1,1300),100,13)
mu<-0.1/12
sigma<-0.2/sqrt(12)
for (i in 1:100){
Y[i,1]<-0@#l
S[i,1]<-1@#l
for (j in 1:12){
Y[i,j+1]<-mu+sigma*rnorm(1)
S[i,j+1]<-exp(Y[i,j+1])
}
}
for(i in 1:100){
kabuka<-S[i,]
SS<-kabuka*1000
K<-1000
r<-0.05
sigma<-0.4
t<-seq(0,1,by=1/12)
d1<-(log(SS/K)+(1-t)*(r+sigma^2/2))/sigma/sqrt(1-t)
d2<-d1-sigma*sqrt(1-t) 
delta<-pnorm(d1)
kabusu<-(delta-c(0,delta[-13]))*1000
cost<-kabusu*SS
ruiseki<-cumsum(cost)
kinri<-ruiseki*r/12
kinri[13]<-0
data.frame(SS,delta,kabusu,cost,ruiseki,kinri)
count[i]<-ruiseki[13]-(sign(SS[13]-1000)+1)/2*SS[13]*1000-poc
}
summary(count)
sd(count)
hist(count)

