Back testing for Stock analysis with R - r

Question

I am a newbie of "R" and I want to write a script for back testing my strategy of buy and sell according to the EMA. I write the following code according to some reference from Web. However, the script got an error message in line 72 but I cannot figure out the problem. Anybody can help to solve my problem? Thanks in advance.
library(quantmod)
stock1<-getSymbols("^DJI",src="yahoo",from="2010-01-01",auto.assign=F)
stock1<-na.locf(stock1)
stock1$EMA9<-EMA(Cl(stock1),n=9)
stock1$EMA19<-EMA(Cl(stock1),n=19)
stock1$EMACheck<-ifelse(stock1$EMA9>stock1$EMA19,1,0)
stock1$EMA_CrossOverUp<-ifelse(diff(stock1$EMACheck)==1,1,0)
stock1$EMA_CrossOverDown<-ifelse(diff(stock1$EMACheck)==-1,-1,0)
stock1<-stock1[index(stock1)>="2010-01-01",]
stock1_df<-data.frame(index(stock1),coredata(stock1))
colnames(stock1_df)<-c("Date","Open","High","Low","Close","Volume","Adj","EMA9","EMA19","EMACheck","EMACheck_up","EMACheck_down")
head(stock1_df)
#To calculate the number of crossoverup transactions during the duration from 2010-01-01
sum(stock1_df$EMACheck_up==1 & index(stock1)>="2010-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_up==1 & index(stock1)>="2010-01-01"]
sum(stock1_df$EMACheck_down==-1 & index(stock1)>="2010-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_down==-1 & index(stock1)>="2010-01-01"]
#To generate the transcation according to the strategy
transaction_dates<-function(stock2,Buy,Sell)
{
Date_buy<-c()
Date_sell<-c()
hold<-F
stock2[["Hold"]]<-hold
for(i in 1:nrow(stock2)) {
if(hold == T) {
stock2[["Hold"]][i]<-T
if(stock2[[Sell]][i] == -1) {
#stock2[["Hold"]][i]<-T
hold<-F
}
} else {
if(stock2[[Buy]][i] == 1) {
hold<-T
stock2[["Hold"]][i]<-T
}
}
}
stock2[["Enter"]]<-c(0,ifelse(diff(stock2[["Hold"]])==1,1,0))
stock2[["Exit"]]<-c(ifelse(diff(stock2[["Hold"]])==-1,-1,0),0)
Buy_date <- stock2[["Date"]][stock2[["Enter"]] == 1]
Sell_date <- stock2[["Date"]][stock2[["Exit"]] == -1]
if (length(Sell_date)<length(Buy_date)){
#Sell_date[length(Sell_date)+1]<-tail(stock2[["Date"]],n=2)[1]
Buy_date<-Buy_date[1:length(Buy_date)-1]
}
return(list(DatesBuy=Buy_date,DatesSell=Sell_date))
}
#transaction dates generate:
transactionDates<-transaction_dates(stock1_df,"EMACheck_up","EMACheck_down")
transactionDates
num_transaction1<-length(transactionDates[[1]])
Open_price<-function(df,x) {df[as.integer(rownames(df[df[["Date"]]==x,]))+1,][["Open"]]}
transactions_date<-function(df,x) {df[as.integer(rownames(df[df[["Date"]]==x,]))+1,][["Date"]]}
transactions_generate<-function(df,num_transaction)
{
price_buy<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[1]][x])})
price_sell<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[2]][x])})
Dates_buy<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[1]][x])}))
Dates_sell<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[2]][x])}))
transactions_df<-data.frame(DatesBuy=Dates_buy,DatesSell=Dates_sell,pricesBuy=price_buy,pricesSell=price_sell)
#transactions_df$return<-100*(transactions_df$pricesSell-transactions_df$pricesBuy)/transactions_df$pricesBuy
transactions_df$Stop_loss<-NA
return(transactions_df)
}
transaction_summary<-transactions_generate(stock1_df,num_transaction1)
transaction_summary$Return<-100*(transaction_summary$pricesSell-transaction_summary$pricesBuy)/transaction_summary$pricesBuy
transaction_summary

Answer 1

Your code fails on this line:
transactionDates<-transaction_dates(stock1_df,"EMACheck_up","EMACheck_down")
The reason is that the first 19 records of stock1_df contain NA values in the columns "EMACheck_up" and "EMACheck_down".
head(stock1_df)
EMACheck_up EMACheck_down
1 NA NA
2 NA NA
3 NA NA
4 NA NA
5 NA NA
6 NA NA
You can solve your issue by running na.locf before running the offending line of code.
stock1_df <- na.locf(stock1_df)
transactionDates <-
transaction_dates(stock1_df, "EMACheck_up", "EMACheck_down")
Skipping the first 19 rows (or first month) would also work.
You might want to look into quantstrat if you want to do more in backtesting strategies. But what you have now does the trick.