Hi,
I'm beginning to fool around in R for trading strategy purposes. To keep it
simple, I have only played with stock data at this point.
I have created a simple trend following strategy (in blue). Given my
statistical background, I am attempting to bootstrap the results and table the
same parameters highlighted below with no luck (in green). Any ideas on what I
could do differently?
Really Appreciate your help!!! Thanks
library(quantmod)
library(PerformanceAnalytics)
b <- get(getSymbols('SPY'))["2011::"]
s <- get(getSymbols('GLD'))["2011::"]
b$sma1 <- SMA(Cl(s) , 1)
s$sma50 <- SMA(Cl(s) , 50)
s$position <- ifelse(Cl(s) > s$sma50 , 1 , -1)
myReturn <- lag(s$position) * dailyReturn(s)
table.Drawdowns(s$position, top = 5, digits = 1)
table.Stats(s$position, ci = 0.95, digits = 2)
table.SpecificRisk(s$position, b$sma1, Rf = 0, digits = 2)
table.Correlation(s$position, b$sma1)
charts.PerformanceSummary(cbind(dailyReturn(s),myReturn))
N = 100 # Number of simulations
Loop = mat.or.vec(N,2,1,1,1)
for (i in 1:N){
# sample with replacement from return distribution of index
s.new = (sample(s, length(s), replace = T, prob = NULL))
# demeaning returns
s.new = s.new-mean(s)
# new price series starting at same value as original series
prices.new = xts(prices[[1]]*exp(cumsum(s.new)))
# define strategies
# mean reversion
s$sma50.new = SMA(Cl(s.new) , 50)
# Create buy/sell signals
# mean reversion
s$position.new <- ifelse(Cl(s) > s$sma50.new , 1 , -1)
# replace missing values with zeros
s$position.new[is.na(s$position.new)] = 0
Loop[i,1] = if (mean(s$position.new) > mean(s$sma50.new)) {1}else{0}
}
#Loop
# plots simulated series
returns.new = cbind(s$sma50.new, cumsum(s$sma50.new))
chart.CumReturns(returns.new,s$sma50.new,geometric=F)
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