(This article was first published on Timely Portfolio, and kindly contributed to R-bloggers)
DO NOT TRADE THIS SYSTEM. YOU VERY EASILY COULD LOSE LARGE AMOUNTS OF MONEY.
I am not necessarily recommending the system that I presented in Exploring the Market with Hurst, but I thought it would provide a nice platform to illustrate some backtesting with multiple indexes. Do not pass on the incredible opportunity presented by almost unlimited indexes from Yahoo! Finance and the Fed.
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| From TimelyPortfolio |
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| From TimelyPortfolio |
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| From TimelyPortfolio |
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| From TimelyPortfolio |
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| From TimelyPortfolio |
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| From TimelyPortfolio |
require(quantmod)
require(PerformanceAnalytics)
require(FGN) #sort of random mix for additional testing
indexes<-c("STI","KS11","GDAXI","DJUSAU","DJUSFI","RUT","DJUBS")
#iterate through index symbols
for (i in 1:length(indexes)) {
#get symbol
getSymbols(paste("^",indexes[i],sep=""),
from="1900-01-01",to=format(Sys.Date(),"%Y-%m-%d"))
#set monthly index to first day of the month
assign(indexes[i],to.monthly(get(indexes[i]))[,4])
#has to be a cleaner way than this to set the index
assign(indexes[i],as.xts(coredata(get(indexes[i])),
order.by=as.Date(index(get(indexes[i])))))
#get monthly changes
ret<-ROC(get(indexes[i]),n=1,type="discrete")
index(ret) <- as.Date(index(ret))
hurstKmonthly <- apply.rolling(ret, FUN="HurstK", width = 12)
colnames(hurstKmonthly) <- "HurstK.monthly"
index(hurstKmonthly) <- as.Date(index(hurstKmonthly))
serialcorr <- runCor(cbind(coredata(ret)),cbind(index(ret)),n=12)
serialcorr <- as.xts(serialcorr,order.by=index(ret))
autoreg <- runCor(ret,lag(ret,k=1),n=12)
colnames(serialcorr) <- "SerialCorrelation.monthly"
colnames(autoreg) <- "AutoRegression.monthly"
signalUpTrend <- runMean(hurstKmonthly+serialcorr+autoreg,n=6) +
(get(indexes[i])/runMean(get(indexes[i]),n=12)-1)*10
signalUpTrend <- lag(signalUpTrend,k=1)
Created by Pretty R at inside-R.org
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