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R Backtesting and Optimization: Quantstrat
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R Backtesting and Optimization: Quantstrat

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R Backtesting and Optimization: Quantstrat

Found Quantstrat package for R backtesting and optimization:

https://r-forge.r-project.org/scm/viewvc.php/pkg/quantstrat/?root=blotter

https://r-forge.r-project.org/projects/blotter/

Mailing list:

https://stat.ethz.ch/mailman/listinfo/r-sig-finance

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Related:

FOSS Trading

Timely Portfolio

Mike

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Quick Summary
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FOSS Trading: quantstrat is slow

Josh is saying that the newest release of quantstrat (0.7.11) released this week is seeing performance improvements of 64x (a 32 hour job now finishing in under 30 minutes).

Mike

Due to time constraints, please do not PM me if your question can be resolved or answered on the forum.

Need help?
1) Stop changing things. No new indicators, charts, or methods. Be consistent with what is in front of you first.
2) Start a journal and post to it daily with the trades you made to show your strengths and weaknesses.
3) Set goals for yourself to reach daily. Make them about how you trade, not how much money you make.
4) Accept responsibility for your actions. Stop looking elsewhere to explain away poor performance.
5) Where to start as a trader? Watch this webinar and read this thread for hundreds of questions and answers.
6)
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Attached: 4 detailed presentations on quantstrat.

Source: Presentations - home

Attached Thumbnails
R Backtesting and Optimization: Quantstrat-quantstrat-i.pdf   R Backtesting and Optimization: Quantstrat-quantstrat-ii.pdf   R Backtesting and Optimization: Quantstrat-quantstrat-iii.pdf   R Backtesting and Optimization: Quantstrat-quantstrat-iv.pdf  
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I have used quantstrat for the first time today.

As an illustration, I have posted below a 400-line R code, which is self-supporting.

It tests an always-in EMA cross-over strategy (actually, EMA has been replaced by Ehlers' super smoother).
There is no stop.
And no optimization: periods have been arbitrarily chosen as 20 and 40.

Initial capital: $100,000
Commission: $6 per contract, round trip
2 contracts
Entry at the open the next day

Instrument is CL. I have enclosed a csv file. Just download it somewhere on your computer, and copy/paste the location at the very beginning of the code, in the line which begins with "quotes.file".

When you run the code, there is nothing to do, except press "Enter" when invited.

The code will produce 4 arrays of data and 5 charts (screenshots below).

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Nicolas

 
Code
# by Nicolas11 @ futures.io (formerly BMT)
# July 27th, 2014

library(lattice)
library(quantstrat)

quotes.file <- "D:\\MultiCharts_Data\\CL#CB_for_strategy_testing.csv"

#
# 1. Instrument: read csv file into xts object
#

data <- read.csv(quotes.file, head=TRUE)
quotes0 <- cbind(data$Open,
                data$High,
                data$Low,
                data$Close,
                data$Volume)
colnames(quotes0) <- c("Open", "High", "Low", "Close", "Volume")
dates <- as.Date(data$Date)
CL <- xts(x=quotes0, order.by=dates)

#
# 2. Support Functions
#

pause <- function() {
  cat ("Press [enter] to continue")
  line <- readline()
}

superSmoother <- function(x0, period) {
  x <- as.numeric(x0)
  res <- numeric(length(x))
  a <- exp(-1.414*pi/period)
  b <- 2*a*cos(1.414*pi/period)
  c2 <- b
  c3 <- -a*a
  c1 <- 1-c2-c3
  res[1] <- x[1]
  res[2] <- x[2]
  for (i in 2:(length(x)-1)) {
    res[i+1] <- (x[i+1]+x[i])*c1/2 + c2*res[i] + c3*res[i-1]
  }
  res
}

#
# 3. Initializations
#

# Currency:
currency("USD")

# Instrument:
big.point.value <- 1000
stock("CL", currency="USD", multiplier=big.point.value)
# Note: for this demo, CL is considered as a stock

# Strategy, portfolio and account names:
qs.strategy <- "Super.Smoother.on.CL"
qs.portfolio <- "Futures"
qs.account <- "My.account"

# Remove previous strategy, portfolio and account:
suppressWarnings(rm(list = c(paste("account", qs.account, sep='.'), paste("portfolio", qs.portfolio, sep='.')), pos=.blotter))
suppressWarnings(rm(list = c(qs.strategy, paste("order_book", qs.portfolio, sep='.')), pos=.strategy))
rm.strat(qs.strategy) # remove strategy etc. if this is a re-run

# Portfolio:
initDate <- '2011-07-25'
initPortf(qs.portfolio, 'CL', initDate=initDate, currency='USD')

# Account:
initEq <- 100000
initAcct(qs.account, portfolios=qs.portfolio, initDate=initDate, currency='USD', initEq=initEq)

# Orders:
initOrders(portfolio=qs.portfolio, initDate=initDate)

# Strategy:
strategy(qs.strategy, store=TRUE)

#
# 4. Functions indicating buy, sell short, sell and buy to cover
#

nb.bars.with.no.trade <- 15

buy.function <- function(x, fastPeriod=20, slowPeriod=40) {
  N <- nrow(x)
  
  fast.super.smoother <- superSmoother(x, fastPeriod)
  slow.super.smoother <- superSmoother(x, slowPeriod)
  
  buy.signals <- numeric(N)
  buy.signals[1:nb.bars.with.no.trade]<- 0
  for (i in (nb.bars.with.no.trade+1):N) {
    if ( ( fast.super.smoother[i] > slow.super.smoother[i] )
         && ( fast.super.smoother[i-1] <= slow.super.smoother[i-1] )
         && index(x)[i] < "2014-07-03" # trick to avoid an open trade at the end
         ) {
      buy.signals[i] <- 1
    } else {
      buy.signals[i] <- 0
    }
  }
  
  xts(x=buy.signals, order.by=index(x))
}

sell.function <- function(x, fastPeriod=20, slowPeriod=40) {
  N <- nrow(x)
  
  fast.super.smoother <- superSmoother(x, fastPeriod)
  slow.super.smoother <- superSmoother(x, slowPeriod)
  
  sell.signals <- numeric(N)
  sell.signals[1:nb.bars.with.no.trade]<- 0
  for (i in (nb.bars.with.no.trade+1):N) {
    if ( ( fast.super.smoother[i] < slow.super.smoother[i] )
         && ( fast.super.smoother[i-1] >= slow.super.smoother[i-1] ) ) {
      sell.signals[i] <- 1
    } else {
      sell.signals[i] <- 0
    }
  }
  
  xts(x=sell.signals, order.by=index(x))
}

sellshort.function <- function(x, fastPeriod=20, slowPeriod=40) {
  N <- nrow(x)
  
  fast.super.smoother <- superSmoother(x, fastPeriod)
  slow.super.smoother <- superSmoother(x, slowPeriod)
  
  sellshort.signals <- numeric(N)
  sellshort.signals[1:nb.bars.with.no.trade]<- 0
  for (i in (nb.bars.with.no.trade+1):N) {
    if ( ( fast.super.smoother[i] < slow.super.smoother[i] )
         && ( fast.super.smoother[i-1] >= slow.super.smoother[i-1] )
         && index(x)[i] < "2014-07-03"# trick to avoid an open trade at the end
         ) {
      sellshort.signals[i] <- 1
    } else {
      sellshort.signals[i] <- 0
    }
  }
  
  xts(x=sellshort.signals, order.by=index(x))
}

buyToCover.function <- function(x, fastPeriod=20, slowPeriod=40) {
  N <- nrow(x)
  
  fast.super.smoother <- superSmoother(x, fastPeriod)
  slow.super.smoother <- superSmoother(x, slowPeriod)
  
  buyToCover.signals <- numeric(N)
  buyToCover.signals[1:nb.bars.with.no.trade]<- 0
  for (i in (nb.bars.with.no.trade+1):N) {
    if ( ( fast.super.smoother[i] > slow.super.smoother[i] )
         && ( fast.super.smoother[i-1] <= slow.super.smoother[i-1] ) ) {
      buyToCover.signals[i] <- 1
    } else {
      buyToCover.signals[i] <- 0
    }
  }
  
  xts(x=buyToCover.signals, order.by=index(x))
}

#
# 5. Indicators for buy, sell short, sell and buy to cover
#

add.indicator(strategy = qs.strategy,
              name = "buy.function",
              arguments = list(x = quote(Cl(mktdata)[,1]), fastPeriod=20, slowPeriod=40),
              label="Buy")

add.indicator(strategy = qs.strategy,
              name = "sell.function",
              arguments = list(x = quote(Cl(mktdata)[,1]), fastPeriod=20, slowPeriod=40),
              label="Sell")

add.indicator(strategy = qs.strategy,
              name = "sellshort.function",
              arguments = list(x = quote(Cl(mktdata)[,1]), fastPeriod=20, slowPeriod=40),
              label="SellShort")

add.indicator(strategy = qs.strategy,
              name = "buyToCover.function",
              arguments = list(x = quote(Cl(mktdata)[,1]), fastPeriod=20, slowPeriod=40),
              label="BuyToCover")

#
# 6. Signals for buy, sell short, sell and buy to cover
#

add.signal(qs.strategy,
           name="sigFormula",
           arguments = list(formula="X1.Buy == 1"),
           label="Buy",
           cross=FALSE)

add.signal(qs.strategy,
           name="sigFormula",
           arguments = list(formula="X1.SellShort == 1"),
           label="SellShort",
           cross=FALSE)

add.signal(qs.strategy,
           name="sigFormula",
           arguments = list(formula="X1.BuyToCover == 1"),
           label="BuyToCover",
           cross=FALSE)

add.signal(qs.strategy,
           name="sigFormula",
           arguments = list(formula="X1.Sell == 1"),
           label="Sell",
           cross=FALSE)

# 
# 7. Rules for buy, sell short, sell and buy to cover
# 

nb.contracts <- 2
round.trip.commission.for.one.contract <- 6
round.trip.commission.for.total.contracts <- round.trip.commission.for.one.contract * nb.contracts

add.rule(qs.strategy,
         name='ruleSignal',
         arguments = list(sigcol="Sell", 
                          sigval=TRUE,
                          orderqty='all',
                          ordertype='market',
                          orderside='long',
                          pricemethod='market',
                          TxnFees=-round.trip.commission.for.total.contracts,
                          prefer='Open',
                          replace=TRUE),
         type='exit',
         path.dep=TRUE,
         label="LongExit")

add.rule(qs.strategy,
         name='ruleSignal',
         arguments = list(sigcol="BuyToCover", 
                          sigval=TRUE,
                          orderqty='all',
                          ordertype='market',
                          orderside='short',
                          pricemethod='market',
                          TxnFees=-round.trip.commission.for.total.contracts,
                          prefer='Open',
                          replace=TRUE),
         type='exit',
         path.dep=TRUE,
         label="ShortExit")

add.rule(qs.strategy,
         name='ruleSignal',
         arguments = list(sigcol="Buy",
                          sigval=TRUE,
                          orderqty=nb.contracts,
                          ordertype='market',
                          orderside='long',
                          pricemethod='market',
                          TxnFees=0,
                          prefer='Open',
                          replace=FALSE),
         type='enter',
         path.dep=TRUE,
         label="LongEntry")

add.rule(qs.strategy,
         name='ruleSignal',
         arguments = list(sigcol="SellShort",
                          sigval=TRUE,
                          orderqty=-nb.contracts,
                          ordertype='market',
                          orderside='short',
                          pricemethod='market',
                          TxnFees=-0,
                          prefer='Open',
                          replace=FALSE),
         type='enter',
         path.dep=TRUE,
         label="ShortEntry")

#
# 8. Apply Strategy to Porfolio
#

applyStrategy(strategy = qs.strategy,
              portfolios = qs.portfolio)

updatePortf(qs.portfolio, Symbols='CL', Dates=paste('::',as.Date(Sys.time()),sep=''))
updateAcct(qs.account)
updateEndEq(qs.account)

#
# 9. View Order book
# 

View(getOrderBook(qs.portfolio)[[qs.portfolio]]$CL)

#
# 10. Plot strategy execution
# 

layout(matrix(1:1))

myTheme<-chart_theme()
myTheme$col$dn.col<-'lightgray'
myTheme$col$dn.border <- 'lightgray'
myTheme$col$up.border <- 'lightgray'

chart.Posn(qs.portfolio,
           Symbol = 'CL',
           Dates = '20131001::',
           theme= myTheme)
 
plot(add_TA(xts(superSmoother(CL$Close, 20), order.by=dates),
           col='black',
           lty=3, 
           legend=NULL,
           on=1))
plot(add_TA(xts(superSmoother(CL$Close, 40), order.by=dates),
            col='black',
            lty=1, 
            legend=NULL,
            on=1))

#
# 11. View trade statistics
#

View(t(tradeStats(qs.portfolio, 'CL')))

#
# 12. View transactions
#

View(getTxns(Portfolio=qs.portfolio, Symbol="CL"))

#
# 13. View statistics per trade
#

View(perTradeStats(qs.portfolio))

# 
# 14. Chart MAE / MFE
#
  
pause()

chart.ME(Portfolio=qs.portfolio, Symbol='CL', type='MAE', scale='percent')

pause()

chart.ME(Portfolio=qs.portfolio, Symbol='CL', type='MFE', scale='percent')

#
# 15. Plot account
#

pause()

layout(matrix(1:1))
a <- getAccount(paste("account", qs.account, sep="."))
plot_obj <- xyplot(a$summary,type="h", col=4)
print(plot_obj)

#
# 16. Plot Equity Curve
#

pause()

layout(matrix(1:1))
equity <- a$summary$End.Eq
plot(equity,main="Equity Curve")

#
# 17. Plot returns
#

# pause()

# layout(matrix(1:1))
# ret <- Return.calculate(equity, method="log")
# charts.PerformanceSummary(ret, colorset = bluefocus, main="Strategy Performance", na.rm=TRUE)

Attached Files
Register to download File Type: csv CL#CB_for_strategy_testing.csv (36.8 KB, 53 views)

Last edited by Nicolas11; July 27th, 2014 at 04:41 PM.
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  #6 (permalink)
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Big Mike's Avatar
 
Posts: 46,240 since Jun 2009
Thanks: 29,353 given, 83,234 received

Nicely done.

BTW, here is a quick and dirty function to speed up uploading plots from R to futures.io (formerly BMT). I think you are familiar with it but noticed you are using old school uploads.

 
Code
function(plot=gg.xts, width=1200, height=900, ...){
  suppressMessages(require(RCurl))
  uri <- "https://www.bmcharts.com/vvhgss.php?auth=2"
  fn <- tempfile(fileext=".png")
  png(fn, width=width, height=height, ...)
  plot(plot)
  dev.off()
  result <- postForm(uri, file = fileUpload(filename = fn, contentType="image/png"), .opts = list(ssl.verifypeer = FALSE, timeout = 10, useragent = "RCurl", verbose = FALSE))
  unlink(fn)
  return(paste0("[img]",result,"[/img]"))
}
Mike

Due to time constraints, please do not PM me if your question can be resolved or answered on the forum.

Need help?
1) Stop changing things. No new indicators, charts, or methods. Be consistent with what is in front of you first.
2) Start a journal and post to it daily with the trades you made to show your strengths and weaknesses.
3) Set goals for yourself to reach daily. Make them about how you trade, not how much money you make.
4) Accept responsibility for your actions. Stop looking elsewhere to explain away poor performance.
5) Where to start as a trader? Watch this webinar and read this thread for hundreds of questions and answers.
6)
Help using the forum? Watch this video to learn general tips on using the site.

If you want
to support our community, become an Elite Member.

Reply With Quote
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  #7 (permalink)
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Nicolas11's Avatar
 
Posts: 1,070 since Aug 2011
Thanks: 2,232 given, 1,729 received

You unmasked me, Mike!
I am old-school.

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  #8 (permalink)
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Hi Nicolas,

nice example. I don't want to come across like a smart-arse; Anyway, parts of your code can be shortened and optimized through vectorization, e.g.,

data loading:
 
Code
#
# 1. Instrument: read csv file into xts object
#

data <- read.csv(quotes.file, head=TRUE, stringsAsFactors=FALSE)
CL <- xts(x=data[, -1], order.by=as.Date(data$Date))
buy and sell functions, first make sure superSmoother returns an xts object:
 
Code
superSmoother <- function(x0, period) {
  x <- as.vector(x0)
  res <- length(x)
  a <- exp(-1.414*pi/period)
  b <- 2*a*cos(1.414*pi/period)
  c2 <- b
  c3 <- -a*a
  c1 <- 1-c2-c3
  res[1 : 2] <- x[1 : 2]
  for (i in 2:(length(x)-1)) {
    res[i+1] <- (x[i+1]+x[i])*c1/2 + c2*res[i] + c3*res[i-1]
  }
  res <- xts(res, order.by=index(x0))
  return(res)
}
then vectorize the code, i.e.,
 
Code
buy.function <- function(x, fastPeriod=20, slowPeriod=40) {
  fast.super.smoother <- superSmoother(x, fastPeriod)
  slow.super.smoother <- superSmoother(x, slowPeriod)
  
  buy.signals <- fast.super.smoother > slow.super.smoother &
    lag(fast.super.smoother) <= lag(slow.super.smoother)
  buy.signals["2014-07-03::"] <- 0
  buy.signals[1 : nb.bars.with.no.trade] <- 0
  return(buy.signals)
}

The 6. Signals functions are not strictly necessary. You can directly use the resulting [0, 1] indicators for the rules in paragraph 7. Unfortunately, I don't have time right now to go through the entire code and post a complete solution but I hope my examples above help.

-S

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  #9 (permalink)
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Quick follow-up. The quantstrat examples are a good source to get started.

 
Code
require(quantstrat)
# show all demo's
demo(package="quantstrat")
# run the faber example
demo(faber)
SVN source: https://r-forge.r-project.org/scm/viewvc.php/pkg/quantstrat/demo/?root=blotter

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Thanks a lot, @skrallan

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