So I am just doing EMA50 cross strategy in quantstrat, it works fine, but I was hoping to change the time frame from daily to weekly.
I tried storing stock() function as to.weekly(SPY) but they wouldn't let me do that. I want to try this for the multiple numbers of stocks later, so it has to be applied within the portfolio.
library(quantstrat)
rm(list=ls(.blotter), envir=.blotter)
strategy.st<-"firststrat"
portfolio.st<-"firststrat"
account.st<-"firststrat"
rm.strat(strategy.st)
#assignsymbol
getSymbols("SPY",auto.assign=TRUE,adjust=TRUE)
initdate<-"2009-01-01"
from<-"2010-01-01"
to<-"2016-11-01"
Sys.setenv(TZ="UTC")
currency("USD")
stock("SPY",currency="USD",multiplier=1)
tradesize<-10000
inieq<-100000
rm.strat(portfolio.st)
initPortf(portfolio.st,symbols="SPY",initDate=initdate,currency='USD')
initAcct(account.st,portfolios = portfolio.st,initDate = initdate,initEq = inieq,currency="USD")
initOrders(portfolio = portfolio.st,initDate = initdate)
strategy(strategy.st,store=TRUE)
add.indicator(strategy = strategy.st,name="EMA",arguments=list(x=quote(Cl(mktdata)),n=50),label="EMA50")
#if closing price goes over moving average 50 and TSi fference is less then 0.15, then long
#short when closing price touches below original closing price by x(depends on atr? previous lows?)
add.signal(strategy.st,name="sigCrossover",
arguments = list(columns=c("Close","EMA50"),
relationship="gt"),
label="crossentry"
)
add.signal(strategy.st,name="sigCrossover",
arguments = list(columns=c("Close","EMA50"),
relationship="lt"),
label="crossexit"
)
add.rule(strategy.st,name="ruleSignal",
arguments=list(sigcol = "crossentry",
sigval=TRUE,
orderqty=100,
ordertype="market",
orderside="long",
replace=FALSE,
prefer="Open",
path.dep=TRUE
),
type="enter"
)
add.rule(strategy.st,name="ruleSignal",
arguments=list(sigcol = "crossexit",
sigval=TRUE,
orderqty="all",
ordertype="market",
orderside="long",
replace=FALSE,
prefer="Open",
path.dep=TRUE
),
type="exit"
)
out <- applyStrategy(strategy = strategy.st, portfolios = portfolio.st)
....
[1] "2016-01-04 00:00:00 SPY -100 @ 197.432029165538"
[1] "2016-02-23 00:00:00 SPY 100 @ 191.041013032617"
[1] "2016-02-24 00:00:00 SPY -100 @ 187.72241891553"
[1] "2016-02-26 00:00:00 SPY 100 @ 193.571820974787"
[1] "2016-03-01 00:00:00 SPY -100 @ 192.035603073637"
.... Any way I can change it to weekly?
You're on the right track. If you do SPY <- to.weekly(SPY) before running applyStrategy, then you'll run the strategy on weekly bars. Remember that quantstrat uses the names of the symbols to find the data, regardless of what frequency that underlying data is stored at (whether it be daily or weekly in the object named SPY in your case).
Here is a more general automated approach for you, since you want to do this for a portfolio of securities. To improve readability, I'm just showing the sections of the code in your question that you need to modify to run with >= 2 securities:
symbols <- c("SPY", "XLE")
getSymbols(symbols,auto.assign=TRUE,adjust=TRUE)
# Change to weekly frequency, using the same names for the symbols in the global environment (which is where you have assigned them in your getSymbols call)
lapply(symbols, function(x) assign(x = x, value = to.weekly(get(x, envir = globalenv()), name = x), envir = globalenv()))
initdate<-"2009-01-01"
from<-"2010-01-01"
to<-"2016-11-01"
Sys.setenv(TZ="UTC")
currency("USD")
# Use your symbols to construct the correct instrument types for your strategy. You are running on stocks only, so simply pass in the vector named `symbols` to stock:
stock(symbols,currency="USD",multiplier=1)
tradesize<-10000
inieq<-100000
rm.strat(portfolio.st)
# When initializing your portfolios, pass in the symbols you want the strategy to run on (the vector named `symbols` here):
initPortf(portfolio.st,symbols=symbols,initDate=initdate,currency='USD')
# ... run the rest of your original code
After applyStrategy has successfully run, you can check mktdata is of the format you wanted (weekly) for the most recent symbol run (the XLE ETF in the symbols vector in this example). You should see something like this:
mktdata["2016-04/2016-05"]
# XLE.Open XLE.High XLE.Low XLE.Close XLE.Volume XLE.Adjusted EMA.EMA50 crossentry crossexit
# 2016-04-01 61.08612 61.83661 59.70363 60.29613 70527800 60.29613 64.16397 NA NA
# 2016-04-08 60.18750 61.92548 59.19014 61.58974 81670700 61.58973 64.06302 NA NA
# 2016-04-15 62.08348 63.73259 61.33299 62.74510 94225700 62.74510 64.01134 NA NA
# 2016-04-22 61.45149 66.44819 61.30337 66.20132 94215100 66.20131 64.09722 1 NA
# 2016-04-29 65.97419 67.95905 64.96695 66.65556 92445000 66.65556 64.19754 NA NA
# 2016-05-06 66.53706 66.81356 63.69309 64.45345 76727000 64.45345 64.20758 NA NA
# 2016-05-13 64.08809 65.90507 62.70560 64.17696 65436100 64.17696 64.20638 NA 1
# 2016-05-20 65.01632 66.07294 63.68321 65.33233 79205200 65.33233 64.25053 1 NA
# 2016-05-27 64.94720 67.07030 64.72008 66.29019 55806400 66.29018 64.33052 NA NA