**Timely Portfolio**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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I was intrigued by the CRAN update on a package ttrTests, especially since quantstrat is not built for backtesting system parameters and analyzing system performance as I mentioned in A Quantstrat to Build On Part 6. ttrTests offers a nice start to my ideal setup for system development, testing, and reporting. In upcoming posts, I hope to build some functionality on top of ttrTests to accomplish my objectives.

I proposed a basic counting system in A Quantstrat to Build On Part 6, but randomly assigned a 50 week (250 days or 1 trading year) parameter to the count. With the help of ttrTests and a couple of index series from Yahoo!Finance, let’s see what parameters work best. Then we can aggregate and graph to visualize the results. As always, THIS IS NOT INVESTMENT ADVICE, and I welcome comments and suggestions.

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

From TimelyPortfolio |

#let's define our silly countupdown function

#as a sample of a custom ttr rule

CUD <- function(x,params=50,...) {

#CUD takes the n-period sum of 1 (up days) and -1 (down days)

temp <- ifelse(runSum(ifelse(ROC(x,1,type="discrete") > 0,1,-1),params)>=0,1,0)

#replace NA with 0 at beginning of period

temp[is.na(temp)] <- 0

temp

} require(ttrTests)

require(quantmod)

require(lattice)

require(reshape2)

require(PerformanceAnalytics) #defaults functions is overridden by ggplot2 and plyr if loaded

#and will cause problems if you want to use ttrTests concurrently tckrs <- c("GSPC","RUT","N225","GDAXI","DJUBS") for (i in 1:length(tckrs)) {

getSymbols(paste("^",tckrs[i],sep=""),from="1896-01-01",to=Sys.Date())

test_price <- as.vector(get(tckrs[i])[,4])

#do parameter tests but plot=FALSE

#we will plot later

#if you want plot=TRUE make sure you add dev.new() here

param_results <- paramStats(x=test_price, ttr = CUD, start = 20, nSteps = 30, stepSize = 10,

restrict = FALSE, burn = 0, short = FALSE, condition = NULL,

silent = TRUE, TC = 0.001, loud = TRUE, plot = FALSE, alpha = 0.025,

begin = 1, percent = 1, file = "", benchmark = "hold")

#get excess returns and add to matrix

ifelse(i==1,param_all <- param_results[[1]],

param_all <- cbind(param_all,param_results[[1]]))

#get best parameter and add to matrix

ifelse(i==1,param_best <- param_results[[5]],

param_best <- rbind(param_best,param_results[[5]]))

}

rownames(param_best) <- tckrs

print(param_best) param_all <- cbind(param_results[[8]],param_all)

#fix rownames and colnames for param_all

colnames(param_all) <- c("parameters",tckrs) df <- as.data.frame(param_all)

df.melt <- melt(df,id.vars=1)

colnames(df.melt) <- c("parameters","index","excessreturn")

param_plot <- xyplot(excessreturn~parameters,group=index,data=df.melt,

auto.key=TRUE,type="l",main="Excess Returns by Parameter")

#jpeg(filename="excess return by parameter.jpg",

quality=100,width=6.25, height = 6.25, units="in",res=96)

print(param_plot)

#want to add points for max but unsure how currently

#df.melt[which(df.melt$parameters==param_best[1,] & df.melt$index==rownames(param_best)[1] ),3]

dev.off() #get performance summary for the best parameters

for (i in 1:length(tckrs)) {

dev.new()

#jpeg(filename=paste(tckrs[i],"performance summary.jpg",sep=""),

# quality=100,width=6.25, height = 6.25, units="in",res=96)

ret <- merge(lag(CUD(get(tckrs[i])[,4],

coredata(param_best)[1],k=1))*ROC(get(tckrs[i])[,4],type="discrete", n=1),

ROC(get(tckrs[i])[,4],type="discrete", n=1))

colnames(ret)<-c(paste(tckrs[i]," CUD System",sep=""),tckrs[i])

charts.PerformanceSummary(ret,ylog=TRUE)

#dev.off()

ret[1,]<-0

price_system <- merge(get(tckrs[i])[,4],

lag(CUD(get(tckrs[i])[,4],

coredata(param_best)[1],k=1))*get(tckrs[i])[,4],

cumprod(1+ret[,1])*coredata(get(tckrs[i]))[coredata(param_best)[1],4])

price_system[which(price_system[,2]==0),2] <- NA

colnames(price_system) <- c("Out","In","System") dev.new()

#jpeg(filename=paste(tckrs[i],"entry analysis.jpg",sep=""),

# 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$Out,on=1,col=2);

addTA(price_system$In,on=1,col=3)",

name=paste(tckrs[i]," Linear Model System",sep=""))

#dev.off()

}

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