Beating the random walk

library(TTR)

quotes  <- getStooqData("sc.f",static_cookie=TRUE)
prices  <- quotes[,"Close"]
Nquotes <- nrow(quotes)
changes <- log(prices[-1]/prices[-Nquotes])

rw <- changes

n <- 25
trade <- rep(0,length(rw))

for(i in (n+1):(length(rw)-1)) {

    m  <- ifelse(i>n ,mean(rw[(i-n):i]), mean(rw[1:i]) )

  if ( ifelse(tail(cumsum(rw[(i-n):i]),1)>0, rw[i] < m, rw[i] > m) )

    trade[i] <- log(prices[i+2]/prices[i+1]) else
    trade[i] <- log(prices[i+1]/prices[i+2])

}

eq_curve <- cumsum(trade)

par(mfrow=c(2,1))
plot(rw,type='l',main='daily log changes',ylab="%")
matplot(cbind(eq_curve,cumsum(changes)),type="l",main="cumulative log return",ylab="%")
legend("topleft",legend=c("strategy","asset"),text.col=c("Black","Red"))
abline(h=0,col="Red",lty="dotted")

tail(eq_curve,1)
prices[Nquotes]/prices[1]-1