montecarlo

monte carlo simulation: incredibly useful forecasting tool to predict outcomes of events with many random variables


N<-500
mc_matrix<-matrix(nrow=252*4,ncol=N)
mc_matrix[1,1]<-as.numeric(AMZN$AMZN.Adjusted[length(AMZN$AMZN.Adjusted),])

for(j in 1:ncol(mc_matrix)){
  mc_matrix[1,j]<-as.numeric(AMZN$AMZN.Adjusted[length(AMZN$AMZN.Adjusted),])
for(i in 2:nrow(mc_matrix)){
  mc_matrix[i,j]<-mc_matrix[i-1,j]*exp(rnorm(1,mu,sig))
}
}

name<-str_c("Sim ",seq(1,500))
name<-c("Day",name)

final_mat<-cbind(1:(252*4),mc_matrix)
final_mat<-as.tibble(final_mat)
colnames(final_mat)<-name

dim(final_mat) #1008 501

final_mat%>%gather("Simulation","Price",2:501)%>%ggplot(aes(x=Day,y=Price,Group=Simulation))+geom_line(alpha=0.2)+labs(title="Amazon Stock (AMZN): 500 Monte Carlo Simulations for 4 Years")+theme_bw()

#is it likely? Check the confidence interval