# [R] Trading Strategy and Bootstrap

Joshua Ulrich josh.m.ulrich at gmail.com
Wed Dec 16 02:27:27 CET 2015

```On Thu, Dec 10, 2015 at 4:30 PM, Schiele, Erik
<Erik.Schiele at bnymellon.com> wrote:
> 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?
>
People will be more likely to respond and help if you provide a more
specific problem statement than, "with no luck".  What's wrong with
your current solution?  What other things have you tried and why
weren't they sufficient?

Also, please do not cross-post.  It's inconsiderate to those who don't
follow both lists: they won't know whether someone has provided a
satisfactory answer on the list/forum they don't follow.

> 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)
>
>    # 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)
>
> Erik Schiele
> Vice President
> Money Markets Trading, Originations and Sales
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