I face the following simple trading strategy:
Buy: when the price of a stock is above the upper Bollinger band.
Sell: when the price of a stock is below the lower Bollinger band.
Hold: A buy signal has appeared, so we hold the stock until one re-allocation day a sell signal appears.
We only consider weekly re-allocation Dates using GSee's startpoints function.
require(quantmod)
# load stock data
tickers <- c("IBM")
myEnv <- new.env()
getSymbols(tickers, from ="2012-01-03", to="2014-12-01", env=myEnv)
close.prices <- do.call(merge, eapply(myEnv, Cl))
close.prices <- close.prices[,pmatch(tickers,colnames(close.prices))]
colnames(close.prices) <- c("IBM")
# now apply the simple trading strategy
m <- merge(close.prices, BBands(close.prices, n=20, maType="SMA"))
m$sig[with(m, IBM > up) & index(m) %in% index(m)[startpoints(m, on="weeks")]] <- 1
m$sig[with(m, IBM < dn) & index(m) %in% index(m)[startpoints(m, on="weeks")]] <- 0
m$sig[1] <- 0
m <- na.locf(m)
sig <- m$sig
So far so good! Now, I there are more Price series I want to extract signals from:
tickers <- c("IBM","AAPL")
getSymbols(tickers, from="2012-01-01", to="2013-12-01")
close.prices <- do.call(merge, lapply(tickers, function(x) Cl(get(x))))
colnames(close.prices) <- c("IBM","APPLE")´
I want to apply the above trading strategy to this portfolio of assets without defining a matrix (here 'm') for each individual asset. I am used to think in loops but there surely is a much more elegant method that avoids looping.
The result should look something like this:
> sig[100:110]
IBM APPLE
2012-05-24 1 0
2012-05-25 1 0
2012-05-29 1 0
2012-05-30 1 0
2012-05-31 1 0
2012-06-01 1 0
2012-06-04 0 0
2012-06-05 0 0
2012-06-06 0 0
