[R-SIG-Finance] Problems with quantstrat and my own code

[Brian G. Peterson]

OK, first, to your question:

There is no book that will teach you modeling in R.  Strategy modeling is
a very complex and often proprietary task.  There are many books that
purport to teach strategy modeling.  All the ones I own are pretty bad. 
None of them use R.  Some of them are useful as a compilation of common
widely known strategy parameters, indicators, signals, and rules.  

There's a reason that successful quantitative strategists are well
compensated: what we do is hard, and involves art, science, math, and a
little bit of luck.  'quantstrat', and the rest of the toolchain, represent
tools that you can use to make you more productive as you create
strategies.

Second, to your problems.

1> quantstrat

That's a *Warning*, not an *Error*, and is coming out of xts somewhere,
probably in subsetting, since we do so much of that.  Because it is a
Warning, and not an Error, I haven't taken the time to figure out where it
is and either code around it or suppress it.

2> your code

I'm not going to debug your ad-hoc strategy code for you, sorry.  Every
time I set out to write an ad-hoc backtest of a strategy, I screw
*something* up. We wrote a framework to concentrate the bugs in one place,
so that we could eliminate them one at a time, and spend more time actually
modeling strategies. Another way of putting that would be that we we wrote
the framework so that we could have a different kind of discussion with the
user of our open source code.  That discussion would look something like
this:  

"I ran the quantstrat demo('faber') code on instrument 'TYC' and
instrument 'XLY', pdf's of chart.Posn() attached. 
I believe the demo code for market orders is creating incorrect results 
here <insert detailed description> by <insert your hypothesis of what is
wrong>. Could someone please check this and let me know?  I'd be happy to
help patch the code.  Thanks." 

Since I think that's probably more or less what you meant, I'll take a
look at the faber demo on TYC and XLY when I get to the office, and look
for any obvious problems with the trades and P&L.  If you've found
something specific that might raise concerns (all the data is available
either  in the output of applyStrategy or in the portfolio to double-check
the indicators, signals, and rules), please share.

Regards,

  - Brian


On Tue, 14 Dec 2010 00:53:33 -0600, Aaditya Nanduri
<aaditya.nanduri at gmail.com> wrote:
> Hello All,
> 
> I have 2 problems and 1 question today.
> 
> QUESTION : Are there any book that teach modelling in R? Hopefully an
> introductory book. I would like to learn how to build/backtest
strategies,
> so if there are any introductory books, please share.
> 
> PROBLEMS:
> 1) Quantstrat
> 
> I tried to use the Faber demo but changed all the symbols to just "TYC"
> and I get the following errors:
>    .
>    .
>    .
>  # Process the indicators and generate trades
>> start_t<-Sys.time()
>> out<-try(applyStrategy(strategy=stratFaber , portfolios='faber'))
> *Warning message:*
> *In max(i) : no non-missing arguments to max; returning -Inf*
>> end_t<-Sys.time()
>    .
>    .
>    .
> *Warning messages:*
> *1: In max(i) : no non-missing arguments to max; returning -Inf*
> *2: In max(i) : no non-missing arguments to max; returning -Inf*
> 
> I have no idea what they mean...
> 
> 2) My code:
> 
> 
> I know this code is wrong but I dont know where the error is. To me, it
> seems right. But when I ran "XLY" through the faber demo and the code I
> wrote, the end results couldnt be further from each other.
> I also know that my code is highly inefficient so if there are any
helpful
> hints that you would like to throw my way, I am open to everything.
> 
>
------------------------------------------------CODE-----------------------------------
> library(quantmod)
> 
> # Get Data
> getSymbols("TYC", from = "1998-01-01", to = Sys.Date())
> 
> # Convert from daily to monthly
> x <- get(TYC)
> x <- to.monthly(XLY, indexAt = 'lastof', drop.time= TRUE)
> indexFormat(x) <- '%Y-%m-%d'
> colnames(x) <- gsub("x", "XLY", colnames(x))
> assign("XLY", x)
> 
> price <- as.numeric(Cl(XLY))
> # Build indicators
> sma10 <- SMA(price, n=10)
> 
> for(i in 1:length(price)){ buy[i] <- NA; sell[i] <- NA }
> # Buy signal
> buy[which(price > sma10)] <- 1
> buy[which(is.na(buy))] <- 0
> 
> # Sell signal
> sell[which(price < sma10)] <- -1
> sell[which(is.na(sell))] <- 0
> 
> signal <- buy + sell
> signal[which(is.na(signal))] <- 0
> 
> x <- NA
> 
> for(i in 1:length(signal)){
>  # Start with buying not selling
> if(signal[i-1] == 0 && signal[i] == -1) {
> signal[i] = 0
> }
> }
> 
> for(i in 1:length(signal)){
> 
> if(signal[i-1] == 0 && signal[i] == 1) {
> x[i] <- 1
> }
> if(signal[i-1] == -1 && signal[i] == 1) {
> x[i] <- 1
> }
> if(signal[i-1] == 1 && signal[i] == -1) {
> x[i] <- -1
> }
> }
> 
> x[which(is.na(x))] <- 0
> 
> money <- 100000 -> initEq
> stock <- 0
> numinP <- 0
> 
> for(i in 1:length(x)){
>  if(x[i] == 1) {
> p <- price[i]
> b <- floor(money/p)
> numinP <- numinP + b
> money <- money - p*b
> stock <- p*b
>  }
> if(x[i] == -1) {
> p <- price[i]
> money <- money + p*numinP
> stock <- 0
> numinP <- 0
> }
> }
> 
> total <- money + stock
> print(paste("The initial equity:",initEq))
> print(paste("After 10 years of trading using TAA:",total))
> 
> 
> I appreciate all your help
> 
> -- 
> Aaditya Nanduri
> aaditya.nanduri at gmail.com
> 
> 	[[alternative HTML version deleted]]
> 
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-- 
Brian G. Peterson
http://braverock.com/brian/
Ph: 773-459-4973
IM: bgpbraverock