[R-SIG-Finance] apply
Diego Peroni
diegoperoni at vodafone.it
Sat Jan 28 14:40:16 CET 2017
Hi Joshua,
I've found the same problem (fast memory increse until swap and crash)
using last quantstrat release from GitHub (0.10.0).
I'm running a very simple demo strategy (in attach to this email) based
on ES 2006 x minute data (163MB).
The strategy do just few trades per case to run to the end of
combinations quickly.
It seems to me that at each new case the memory increases because old
data are not dropped from memory.
I didn't had this problem using quantstrat 0.9.1709
My configuration is the following:
- CentOS server (128GB ram, 6 core XEON)
- RStudio Server Version 0.99.484
- R version 3.2.2 (2015-08-14)
- TTR 0.23.1
- quantmod 0.4.7
- blotter 0.9.1741
- PerformanceAnalytics 1.4.3662
I'm sending to you (in private) a link to download the data
(ES_2006.RData) that the strategy uses:
Thanks in advance for your time and let me know if I've missed important
information for you.
Regards
Diego
On 28/01/2017 12:14, Diego Peroni wrote:
> Hi Joshua,
>
> thanks for your answer!
>
> I'm going to download and test last version from GitHub first and I'll
> check if my problem persists...
>
> Diego
>
>
> On 27/01/2017 19:13, Joshua Ulrich wrote:
>> On Fri, Jan 27, 2017 at 12:04 PM, Diego Peroni
>> <diegoperoni at vodafone.it> wrote:
>>> Hi everybody,
>>>
>>> I'm running last quantstrat build from a couple of days on a CentOS
>>> server (128GB ram, 6 core XEON):
>>>
>>> Version: *0.9.1739*| Last change: *2016-04-17 20:25:28+02*| Rev.: *1748
>>>
>> That is not the last quantstrat build. You're using the last commit
>> from R-Forge, but quantstrat moved from R-Forge to GitHub in May 2016.
>> https://github.com/braverock/quantstrat
>>
>>> **Using:
>>>
>>> **library(doMC)
>>> registerDoMC(cores=detectCores())
>>> results = apply.paramset(my.strategy, paramset.label = "OPT",
>>> portfolio=my.strategy, account=my.strategy,
>>> nsamples=0, calc='slave', audit=NULL, verbose=FALSE)
>>> *
>>> *This new release crashes in few minutes with just 500 combinations
>>> because memory allocation ***increases *of each single process very
>>> very
>>> fast.
>>>
>>> **It never happened to me with this simple strategy before quantstrat
>>> upgrade.*
>>> *
>>> Someone can help me?*
>>> *
>> It's going to be very difficult for people to help you with so little
>> information about the strategy.
>>
>> It would also be helpful to know the versions of R and all relevant
>> packages both *before* and after this issue occurred. You think the
>> issue is with quantstrat because you're trying to run a strategy, but
>> quantstrat depends on a lot of other packages and an issue in one of
>> them could be causing this issue.
>>
>>> Thanks*
>>> *Diego
>>> *
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
>>> R-SIG-Finance at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
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>>> -- Also note that this is not the r-help list where general R
>>> questions should go.
>>
>>
>
> _______________________________________________
> R-SIG-Finance at r-project.org mailing list
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-------------- next part --------------
rm(list=ls())
library(quantstrat)
Sys.setenv(TZ="UTC")
Sys.setlocale('LC_TIME', 'C')
options("scipen"=100, "digits"=10)
osMaxPosLongShort = function(data, timestamp, orderqty, ordertype, orderside, portfolio, symbol, ruletype, ...) {
maxpos = osMaxPos(data, timestamp, orderqty, ordertype, orderside, portfolio, symbol, ruletype, ...)
curpos = getPosQty(portfolio, symbol, timestamp)
if (orderside == 'long' & curpos<0)
maxpos = 0
if (orderside == 'short' & curpos>0)
maxpos = 0
return (maxpos)
}
initEq = 10000
symbol = 'ES'
currency('USD')
initDate = startDate = '2006-01-01'
endDate = '2006-12-31'
load('ES_2016.RData') # loading minute data
stock(symbol, currency='USD', multiplier=50, tick_size=0.25)
qs.strategy = 'teststrategy'
rm.strat(qs.strategy)
initPortf(qs.strategy, symbol, initDate = initDate)
initAcct(qs.strategy, portfolios = qs.strategy, initDate = initDate, initEq = initEq)
initOrders(portfolio = qs.strategy, initDate = initDate)
strategy(qs.strategy, store = TRUE)
addPosLimit(portfolio = qs.strategy, symbol = symbol, timestamp = initDate, maxpos = 1, minpos = -1)
add.indicator(qs.strategy, name='RSI',
arguments = list(price=quote(Cl(mktdata)), n=12), label='rsi')
add.signal(qs.strategy, name = "sigThreshold",
arguments = list(column="EMA.rsi", threshold=0.01, relationship="lt", cross=TRUE), label="upTrend")
add.rule(qs.strategy, name='ruleSignal',
arguments = list(sigcol="upTrend", sigval=TRUE,
replace=TRUE,
prefer='open',
orderside='long',
ordertype='market',
orderqty=1,
osFUN='osMaxPosLongShort',
orderset='ocolong'),
timespan='T09:30/T16:00',
type='enter',
label='LE')
add.rule(qs.strategy, name='ruleSignal',
arguments=list(sigcol='upTrend', sigval=TRUE,
prefer='open',
replace=FALSE,
orderside='long',
ordertype='stoptrailing',
threshold=0.005,
tmult=TRUE,
orderqty='all',
orderset='ocolong'
),
type='chain', parent='LE',
label='StopTrailingLong',
enabled=TRUE)
add.distribution(qs.strategy,
paramset.label = 'MACDOPT',
component.type = 'signal',
component.label = 'upTrend',
variable = list(threshold = seq(1, 2, by=.003)),
label = 'threshold.upTrend')
library(doMC)
registerDoMC(cores=detectCores())
results = apply.paramset(qs.strategy, paramset.label = "MACDOPT", portfolio=qs.strategy, account=qs.strategy, nsamples=0, calc='slave', audit=NULL, verbose=TRUE)
r = t(data.frame(do.call(rbind, results$tradeStats)))
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