用 R 对股票市场进行回测
Back testing for Stock Market with R
我是 R 的新用户,想使用 R 来回测我的策略。我尝试结合在 web.xml 中找到的一些脚本。但是,它没有按照我的想法工作。我的问题是无法根据我的策略设计日期生成交易日期。
library(quantmod)
library(lubridate)
stock1<-getSymbols("AAPL",src="yahoo",from="2016-01-01",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$EMACheck)==-1,-1,0)
stock1<-stock1[index(stock1)>="2016-01-01",]
stock1_df<-data.frame(index(stock1),coredata(stock1))
colnames(stock1_df)<-c("Date","Open","High","Low","Close","Volume","Adj","EMA9","EMA19","EMACheck","EMACheck_up","EMACheck_down")
#To calculate the number of crossoverup transactions during the duration from 2016-01-01
sum(stock1_df$EMACheck_up==1 & index(stock1)>="2016-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_up==1 & index(stock1)>="2016-01-01"]
sum(stock1_df$EMACheck_down==-1 & index(stock1)>="2016-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_down==-1 & index(stock1)>="2016-01-01"]
#To generate the transcation according to the strategy
transaction_dates<-function(stock2,Buy,Sell)
{
Date_buy<-c()
Date_sell<-c()
hold<-F
stock2[["Hold"]]<-hold
for(i in 1:nrow(stock2)) {
if(hold == T) {
stock2[["Hold"]][i]<-T
if(stock2[[Sell]][i] == -1) {
#stock2[["Hold"]][i]<-T
hold<-F
}
} else {
if(stock2[[Buy]][i] == 1) {
hold<-T
stock2[["Hold"]][i]<-T
}
}
}
stock2[["Enter"]]<-c(0,ifelse(diff(stock2[["Hold"]])==1,1,0))
stock2[["Exit"]]<-c(ifelse(diff(stock2[["Hold"]])==-1,-1,0),0)
Buy_date <- stock2[["Date"]][stock2[["Enter"]] == 1]
Sell_date <- stock2[["Date"]][stock2[["Exit"]] == -1]
if (length(Sell_date)<length(Buy_date)){
#Sell_date[length(Sell_date)+1]<-tail(stock2[["Date"]],n=2)[1]
Buy_date<-Buy_date[1:length(Buy_date)-1]
}
return(list(DatesBuy=Buy_date,DatesSell=Sell_date))
}
#transaction dates generate:
stock1_df <- na.locf(stock1_df)
transactionDates<-transaction_dates(stock1_df,"EMACheck_up","EMACheck_down")
transactionDates
num_transaction1<-length(transactionDates[[1]])
Open_price<-function(df,x) {df[as.integer(rownames(df[df[["Date"]]==x,]))+1,][["Open"]]}
transactions_date<-function(df,x) {df[as.integer(rownames(df[df[["Date"]]==x,]))+1,][["Date"]]}
transactions_generate<-function(df,num_transaction)
{
price_buy<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[1]][x])})
price_sell<-sapply(1:num_transaction,function(x) {Open_price(df,transactionDates[[2]][x])})
Dates_buy<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[1]][x])}))
Dates_sell<-as.Date(sapply(1:num_transaction,function(x) {transactions_date(df,transactionDates[[2]][x])}))
transactions_df<-data.frame(DatesBuy=Dates_buy,DatesSell=Dates_sell,pricesBuy=price_buy,pricesSell=price_sell)
#transactions_df$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
sum(transaction_summary$Return,na.rm=T)
嗨,我是 R 的新用户,想使用 R 来回测我的策略。我尝试结合在 web.xml 中找到的一些脚本。但是,它没有按照我的想法工作。我的问题是无法根据我的策略设计日期生成交易日期。
problem as this image
你的代码太复杂了。
问题出在函数Open_price和transactions_date查找使用行名查找记录编号然后取下一个。但随后不再查找行名,而是将其用作索引。那里出错了。
如果您查看第一次约会的以下结果,returns 40。
as.integer(rownames(stock1_df[stock1_df[["Date"]] == "2016-03-01", ]))
[1] 40
所以它要查找的下一条记录是 41。但是 stock_df[41, ] 与行名 41 不同。行名的一个问题是,如果您从 data.frame 行名不变。要获得正确的索引号,您应该使用 which
。如果您查看 stock1_df,您会发现它 return 是 21,我们需要记录 22
which(stock1_df[["Date"]] == "2016-03-01")
[1] 21
我将 Open_price 和 transactions_date 函数更改为使用 which
函数。现在这将 return 正确的结果。
Open_price <- function(df, x) {
df[which(df[["Date"]] == x) + 1, ][["Open"]]
}
transactions_date <- function(df, x) {
df[which(df[["Date"]] == x) + 1, ][["Date"]]
}
head(transaction_summary)
DatesBuy DatesSell pricesBuy pricesSell Stop_loss Return
1 2016-03-02 2016-04-25 100.51 105.00 NA 4.467215
2 2016-05-27 2016-06-20 99.44 96.00 NA -3.459374
3 2016-07-13 2016-09-12 97.41 102.65 NA 5.379322
4 2016-09-15 2016-11-02 113.86 111.40 NA -2.160547
5 2016-12-12 2017-06-13 113.29 147.16 NA 29.896728
6 2017-07-17 2017-09-19 148.82 159.51 NA 7.183166
一点建议,尽量在代码中使用空格。这使它更具可读性。看这个 style guide 的例子。您的整个代码被重写为仅使用 stock1,而无需在代码中途将其变成 data.frame。但是现在代码完成了它需要做的事情。
我是 R 的新用户,想使用 R 来回测我的策略。我尝试结合在 web.xml 中找到的一些脚本。但是,它没有按照我的想法工作。我的问题是无法根据我的策略设计日期生成交易日期。
library(quantmod)
library(lubridate)
stock1<-getSymbols("AAPL",src="yahoo",from="2016-01-01",auto.assign=F)
stock1<-na.locf(stock1)
stock1$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)>="2016-01-01",]
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")
#To calculate the number of crossoverup transactions during the duration from 2016-01-01
sum(stock1_df$EMACheck_up==1 & index(stock1)>="2016-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_up==1 & index(stock1)>="2016-01-01"]
sum(stock1_df$EMACheck_down==-1 & index(stock1)>="2016-01-01",na.rm=T)
stock1_df$Date[stock1_df$EMACheck_down==-1 & index(stock1)>="2016-01-01"]
#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,"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$pricesBuy
transaction_summary
sum(transaction_summary$Return,na.rm=T)
嗨,我是 R 的新用户,想使用 R 来回测我的策略。我尝试结合在 web.xml 中找到的一些脚本。但是,它没有按照我的想法工作。我的问题是无法根据我的策略设计日期生成交易日期。
problem as this image
你的代码太复杂了。
问题出在函数Open_price和transactions_date查找使用行名查找记录编号然后取下一个。但随后不再查找行名,而是将其用作索引。那里出错了。
如果您查看第一次约会的以下结果,returns 40。
as.integer(rownames(stock1_df[stock1_df[["Date"]] == "2016-03-01", ]))
[1] 40
所以它要查找的下一条记录是 41。但是 stock_df[41, ] 与行名 41 不同。行名的一个问题是,如果您从 data.frame 行名不变。要获得正确的索引号,您应该使用 which
。如果您查看 stock1_df,您会发现它 return 是 21,我们需要记录 22
which(stock1_df[["Date"]] == "2016-03-01")
[1] 21
我将 Open_price 和 transactions_date 函数更改为使用 which
函数。现在这将 return 正确的结果。
Open_price <- function(df, x) {
df[which(df[["Date"]] == x) + 1, ][["Open"]]
}
transactions_date <- function(df, x) {
df[which(df[["Date"]] == x) + 1, ][["Date"]]
}
head(transaction_summary)
DatesBuy DatesSell pricesBuy pricesSell Stop_loss Return
1 2016-03-02 2016-04-25 100.51 105.00 NA 4.467215
2 2016-05-27 2016-06-20 99.44 96.00 NA -3.459374
3 2016-07-13 2016-09-12 97.41 102.65 NA 5.379322
4 2016-09-15 2016-11-02 113.86 111.40 NA -2.160547
5 2016-12-12 2017-06-13 113.29 147.16 NA 29.896728
6 2017-07-17 2017-09-19 148.82 159.51 NA 7.183166
一点建议,尽量在代码中使用空格。这使它更具可读性。看这个 style guide 的例子。您的整个代码被重写为仅使用 stock1,而无需在代码中途将其变成 data.frame。但是现在代码完成了它需要做的事情。