ggplot() geom_point() 散布図

月間変動係数 vs. Composite Leading Indicator 5 months delta.
##  codes begin

w <- (apply.monthly(SP5[,4],sd)/apply.monthly(SP5[,4],mean))["1970::2018"]
d <- na.omit(diff(cli_xts$oecd,5))["1970::2018"]
func <- function(x){
  if(x > 0.1){return("upper")}
  if(x > 0){return("uppermiddle")}
  if(x > -0.1){return("lowermiddle")}
  if(x < -0.1){return("lower")}
}
df <- data.frame(sd=as.vector(w),delta=as.vector(d),sign=as.vector(apply(diff(cli_xts$oecd)["1970::2018"],1,func)))
#           sd    delta sign
# 1 0.02741634 -0.80305    m
# 2 0.01305567 -0.83870    m
# 3 0.01308169 -0.86574    m
# 4 0.03515768 -0.87581    m
# 5 0.04406664 -0.85544    m
# 6 0.02212387 -0.79926    m
p <- ggplot(df, aes(x=delta,y=sd,color=sign))
p <- p + geom_point(alpha=0.5)
# p <- p + geom_smooth(method = "lm")
plot(p)

## codes end

月間騰落率 vs. Composite Leading Indicator 5 months delta.
## codes begin

w <- (to.monthly(SP5)[,4]/to.monthly(SP5)[,1])["1970::2018"]
w <- w-1
# w <- (apply.monthly(SP5[,4],sd)/apply.monthly(SP5[,4],mean))["1970::2018"]
d <- na.omit(diff(cli_xts$oecd,5))["1970::2018"]
func <- function(x){
  if(x > 0.1){return("upper")}
  if(x > 0){return("uppermiddle")}
  if(x > -0.1){return("lowermiddle")}
  if(x < -0.1){return("lower")}
}
df <- data.frame(monthlyreturn=as.vector(w),delta=as.vector(d),sign=as.vector(apply(diff(cli_xts$oecd)["1970::2018"],1,func)))
p <- ggplot(df, aes(x=delta,y=monthlyreturn,color=sign))
p <- p + geom_point(alpha=0.5)
# p <- p + geom_smooth(method = "lm")
plot(p)

## codes end