Ниже приведен мой скрипт для проекта бэк-тестирования.Я написал, чтобы протестировать возврат 2 SMA для стратегии покупки / продажи.Теперь я хочу автоматизировать ввод значений x и y и сгенерировать таблицу для другого результата.С изменением значения X с (1:30), а также с изменением значения Y с (1:30) и выводом в файл данных, похожий на файл Excel, который соответствует столбцу от 1 до 30. Я пробовал разные способы, но до сих пор не могу сделать окончательный вариантфрейм данных в R
library(quantmod)
library(lubridate)
library(xlsx)
stock0<-getSymbols("^HSI",src="yahoo",from="1988-01-01",auto.assign=F)
stock0 <- to.weekly(stock0)
x<-1
y<-30
stock1<-na.locf(stock0)
stock1$SMA1<-SMA(Cl(stock1),n=x)
stock1$SMA30<-SMA(Cl(stock1),n=y)
stock1$SMACheck<-ifelse(stock1$SMA1>stock1$SMA30,1,0)
stock1$SMA_CrossOverUp<-ifelse(diff(stock1$SMACheck)==1,1,0)
stock1$SMA_CrossOverDown<-ifelse(diff(stock1$SMACheck)==-1,-1,0)
stock1<-stock1[index(stock1)>="1998-01-01",]
stock1_df<-data.frame(index(stock1),coredata(stock1))
colnames(stock1_df)<-c("Date","Open","High","Low","Close","Volume","Adj","SMA1","SMA30","SMACheck","SMACheck_up","SMACheck_down")
sum(stock1_df$SMACheck_up==1 & index(stock1)>="2010-01-01",na.rm=T)
stock1_df$Date[stock1_df$SMACheck_up==1 & index(stock1)>="2010-01-01"]
sum(stock1_df$SMACheck_down==-1 & index(stock1)>="2010-01-01",na.rm=T)
stock1_df$Date[stock1_df$SMACheck_down==-1 & index(stock1)>="2010-01-01"]
#To generate the transcation according to the strategy
transaction_dates<-function(stock2,Buy,Sell)
{
Date_buy<-c()
Date_sell<-c()
hold<-F
stock2[["Hold"]]<-hold
for(i in 1:nrow(stock2)) {
if(hold == T) {
stock2[["Hold"]][i]<-T
if(stock2[[Sell]][i] == -1) {
#stock2[["Hold"]][i]<-T
hold<-F
}
} else {
if(stock2[[Buy]][i] == 1) {
hold<-T
stock2[["Hold"]][i]<-T
}
}
}
stock2[["Enter"]]<-c(0,ifelse(diff(stock2[["Hold"]])==1,1,0))
stock2[["Exit"]]<-c(ifelse(diff(stock2[["Hold"]])==-1,-1,0),0)
Buy_date <- stock2[["Date"]][stock2[["Enter"]] == 1]
Sell_date <- stock2[["Date"]][stock2[["Exit"]] == -1]
if (length(Sell_date)<length(Buy_date)){
#Sell_date[length(Sell_date)+1]<-tail(stock2[["Date"]],n=2)[1]
Buy_date<-Buy_date[1:length(Buy_date)-1]
}
return(list(DatesBuy=Buy_date,DatesSell=Sell_date))
}
#transaction dates generate:
stock1_df <- na.locf(stock1_df)
transactionDates<-transaction_dates(stock1_df,"SMACheck_up","SMACheck_down")
num_transaction1<-length(transactionDates[[1]])
Open_price<-function(df,x) {
df[which(df[["Date"]]==x)+1,][["Open"]]
}
transactions_date<-function(df,x) {
df[which(df[["Date"]]==x)+1,][["Date"]]
}
transactions_generate<-function(df,num_transaction)
{
price_buy<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[1]][x])})
price_sell<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[2]][x])})
Dates_buy<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[1]][x])}))
Dates_sell<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[2]][x])}))
transactions_df<-data.frame(DatesBuy=Dates_buy,DatesSell=Dates_sell,pricesBuy=price_buy,pricesSell=price_sell)
#transactions_df$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
result<-sum(transaction_summary$Return,na.rm=T)
result