# Crazy RUT

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**Timely Portfolio**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

I have noticed that the Russell 2000 (RUT) acts very differently from most of the other indexes that I have studied. If we apply the system shown in Shorting Mebane Faber to RUT and then extend it with a simple slope, we notice something very different about RUT behavior. No clear dominant strategy really emerges.

From TimelyPortfolio |

From TimelyPortfolio |

require(quantmod) require(PerformanceAnalytics) getSymbols("^RUT",from="1919-01-01",to=Sys.Date()) RUT <- to.monthly(RUT)[,4] index(RUT) <- as.Date(index(RUT)) #get 10 month rolling average avg10 <- runMean(RUT,n=10) #know I can do this better in R but here is my ugly code #to calculate 6 month slope of 10 month average width=6 for (i in 1:(NROW(avg10)-width)) { #get sp500/crb slope model <- lm(RUT[i:(i+width),1]~index(RUT[i:(i+width)])) ifelse(i==1,avg10slope <- model$coefficients[2], avg10slope <- rbind(avg10slope,model$coefficients[2])) } #get xts so we can use avg10slope <- xts(cbind(avg10slope),order.by=index(avg10)[(width+1):NROW(avg10)]) priceSignals <- na.omit(merge(RUT,avg10,avg10slope)) signalUpUp <- ifelse(priceSignals[,1] > priceSignals[,2] & priceSignals[,3] > 0, 1, 0) signalUpDown <- ifelse(priceSignals[,1] > priceSignals[,2] & priceSignals[,3] < 0, 1, 0) signalDownUp <- ifelse(priceSignals[,1] < priceSignals[,2] & priceSignals[,3] > 0, 1, 0) signalDownDown <- ifelse(priceSignals[,1] < priceSignals[,2] & priceSignals[,3] < 0, 1, 0) retUpUp <- lag(signalUpUp,k=1)* ROC(RUT,type="discrete",n=1) retUpDown <- lag(signalUpDown,k=1)* ROC(RUT,type="discrete",n=1) retDownUp <- lag(signalDownUp, k=1) * ROC(RUT,type="discrete",n=1) retDownDown <- lag(signalDownDown, k=1) * ROC(RUT,type="discrete",n=1) ret <- merge(retUpUp,retUpDown,retDownUp,retDownDown,ROC(RUT,type="discrete",n=1)) colnames(ret) <- c("UpUp","UpDown","DownUp","DownDown","RUT") jpeg(filename="performance summary.jpg",quality=100, width=6.25, height = 6.25, units="in",res=96) charts.PerformanceSummary(ret,ylog=TRUE, colorset=c("cadetblue","darkolivegreen3","goldenrod","purple","gray70","black"), main="RUT 10 Month Moving Average Strategy Comparisons May 1987-Jun 2011") dev.off() jpeg(filename="rolling returns.jpg",quality=100, width=6.25, height = 6.25, units="in",res=96) chart.RollingPerformance(ret,width=36, colorset=c("cadetblue","darkolivegreen3","goldenrod","purple","gray70","black"), main="RUT 10 Month Moving Average Strategy Comparisons 36 Month Rolling Return May 1987-Jun 2011") dev.off()

To

**leave a comment**for the author, please follow the link and comment on their blog:**Timely Portfolio**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.