# lm System on Nikkei with New Chart

August 15, 2011
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[This article was first published on Timely Portfolio, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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I got a great idea from the zoo-overplot demo to make a very helpful visualization of system entry and exit.  Since the lm-based system presented in Unrequited lm Love is newest, I will use this system, but apply to the Nikkei 225 instead of the Russell 2000.

THIS IS STILL NOT INVESTMENT ADVICE, AND I TAKE NO RESPONSIBILITY FOR THE LOSSES THAT ARE VERY LIKELY IF YOU PURSUE THIS APPROACH.

Here is the new system visualization.

 From TimelyPortfolio
 From TimelyPortfolio
 From TimelyPortfolio
 From TimelyPortfolio
 From TimelyPortfolio

R code (click to download):

`#third version#add another neat chart for visualization#got idea from zoo-overplot demo   #second version#this one actually has an additional mean reverting element#for markets that have moved down so long entry is quickerrequire(PerformanceAnalytics)require(quantmod)   #set this up to get either FRED or Yahoo!Finance#getSymbols("N225",src="FRED")getSymbols("^N225",from="1896-01-01",to=Sys.Date())   N225 <- to.weekly(N225)[,4]N225mean <- runMean(N225,n=30)#index(N225) <- as.Date(index(N225))      width = 10for (i in (width+1):NROW(N225)) {	linmod <- lm(N225[((i-width):i),1]~index(N225[((i-width):i)]))	ifelse(i==width+1,signal <- coredata(linmod\$residuals[length(linmod\$residuals)]),		signal <- rbind(signal,coredata(linmod\$residuals[length(linmod\$residuals)])))	ifelse(i==width+1,signal2 <- coredata(linmod\$coefficients[2]),		signal2 <- rbind(signal2,coredata(linmod\$coefficients[2])))	ifelse(i==width+1,signal3 <- cor(linmod\$fitted.values,N225[((i-width):i),1]),		signal3 <- rbind(signal3,cor(linmod\$fitted.values,N225[((i-width):i),1])))}   signal <- as.xts(signal,order.by=index(N225[(width+1):NROW(N225)]))signal2 <- as.xts(signal2,order.by=index(N225[(width+1):NROW(N225)]))signal3 <- as.xts(signal3,order.by=index(N225[(width+1):NROW(N225)]))signal4 <- ifelse(N225 > N225mean,1,0)   price_ret_signal <- merge(N225,lag(signal,k=1),	lag(signal2,k=1),	lag(signal3,k=1),	lag(signal4,k=1),	lag(ROC(N225,type="discrete",n=15),k=1),	ROC(N225,type="discrete",n=1))	price_ret_signal[,2] <- price_ret_signal[,2]/price_ret_signal[,1]	price_ret_signal[,3] <- price_ret_signal[,3]/price_ret_signal[,1]ret <- ifelse((price_ret_signal[,5] == 1) | (price_ret_signal[,5] == 0  & 	runMean(price_ret_signal[,3],n=50) > 0 & runMean(price_ret_signal[,2],n=10) < 0 ),	1, 0) * price_ret_signal[,7]retCompare <- merge(ret, price_ret_signal[,7])colnames(retCompare) <- c("Linear System", "BuyHold")#jpeg(filename="performance summary.jpg",#	quality=100,width=6.25, height = 8,  units="in",res=96)charts.PerformanceSummary(retCompare,ylog=TRUE,cex.legend=1.2,	colorset=c("black","gray70"),main="N225 System Return Comparison")#dev.off()require(ggplot2)df <- as.data.frame(na.omit(merge(price_ret_signal[,5],price_ret_signal[,7])))colnames(df) <- c("signal_avg","return")#jpeg(filename="boxplot by average.jpg",#	quality=100,width=6.25, height = 8,  units="in",res=96)ggplot(df,aes(x=factor(signal_avg),y=return)) + geom_boxplot()#dev.off()df2 <- as.data.frame(na.omit(merge(ifelse((price_ret_signal[,5] == 0  & 	runMean(price_ret_signal[,3],n=50) > 0 & runSum(price_ret_signal[,2],n=10) < 0 ),	1, 0),price_ret_signal[,7])))colnames(df2) <- c("signal_other","return")#jpeg(filename="boxplot by other signal.jpg",#	quality=100,width=6.25, height = 8,  units="in",res=96)ggplot(df2,aes(x=factor(signal_other),y=return)) + geom_boxplot()#dev.off()df3 <- as.data.frame(na.omit(merge(ifelse((price_ret_signal[,5] == 1) |	(price_ret_signal[,5] == 0  & 	runMean(price_ret_signal[,3],n=50) > 0 & runMean(price_ret_signal[,2],n=10) < 0 ),	1, 0),price_ret_signal[,7])))colnames(df3) <- c("signals_all","return")#jpeg(filename="boxplot by long signal.jpg",#	quality=100,width=6.25, height = 8,  units="in",res=96)ggplot(df3,aes(x=factor(signals_all),y=return)) + geom_boxplot()#dev.off()#jpeg(filename="text plot of return and risk.jpg",	quality=100,width=6.25, height = 6.25,  units="in",res=96)textplot(rbind(table.AnnualizedReturns(retCompare),	table.DownsideRisk(retCompare)[c(1:3,7,11),]))#dev.off()   #eliminate NA at start of return seriesretCompare[is.na(retCompare)] <- 0price_system <- merge(N225,ifelse((price_ret_signal[,5] == 1) |	(price_ret_signal[,5] == 0  & 	runMean(price_ret_signal[,3],n=50) > 0 &	runMean(price_ret_signal[,2],n=10) < 0 ),	NA, 1),coredata(N225)[width+50]*cumprod(retCompare[,1]+1))price_system[,2] <- price_system[,1]*price_system[,2]colnames(price_system) <- c("In","Out","System")   #jpeg(filename="chartSeries with colored entry and exit.jpg",#	quality=100,width=6.25, height = 6.25,  units="in",res=96)chartSeries(price_system\$System,theme="white",log=TRUE,up.col="black",	yrange=c(min(price_system[,c(1,3)]),max(price_system[,c(1,3)])),	TA="addTA(price_system\$In,on=1,col=3);	addTA(price_system\$Out,on=1,col=2)",	name="N225 Linear Model System")#dev.off()`

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