Custom Indicator and apply.paramset problem
You didn't tell the list what error you see when you try running your code. You should probably use doParallel on Windows, and not load snow and parallel both. The socket cluster code in the parallel package came from snow, and they share the same function names, so you could have namespace collisions with both loaded. Your most likely problem is that you did not export your custom function to the cluster workers using .exports in the apply.paramsets call or clusterExport before calling apply.paramsets. Regards, Brian
On 02/25/2017 02:11 PM, Atakan Okan wrote:
Hi again,
As a followup to my custom indicator question:
Although I have successfully implemented it based on your suggestions and ran it via applyStrategy; optimizing parameters of a strategy with the same custom indicator via apply.paramset does not seem to work on Windows using the package doSNOW, despite the fact that I have run apply.paramset on a different strategy with parallelization with doSNOW but without any custom indicators.
Any help is appreciated, thank you :)
Atakan Okan
The reproducible code:
library(quantmod)
library(quantstrat)
library(TTR)
Sys.setenv(TZ = "UTC")
.strategy <- new.env()
.blotter <- new.env()
#Data
getSymbols("AAPL")
#Stock
symbol.name = "AAPL"
tick.size = 0.01
currency('USD')
stock(symbol.name, currency="USD", multiplier=1,tick_size= tick.size)
initialEquity = 100000
port.acct.currency <- "USD"
strategy.st <- 'Custom_Prob'
rm.strat(strategy.st)
initDate = as.character(as.Date(index(AAPL[1])-1))
initPortf(strategy.st, symbol.name, initDate=initDate, currency =
port.acct.currency)
initAcct(strategy.st, portfolios=strategy.st,
initDate=initDate,
initEq=initialEquity, currency = port.acct.currency)
initOrders(portfolio=strategy.st,initDate=initDate)
strategy(strategy.st,store=TRUE)
summary(getStrategy(strategy.st))
#MACD W1 indicator
MACD_W1 <- function(mktdata=quote(mktdata),
nFast = 12,
nSlow = 26,
nSig = 9)
{
y <- eval(parse(text = symbol.name))
y <- to.weekly(y)
y <- Cl(y)
y <- MACD(y,
nFast = nFast,
nSlow = nSlow,
nSig = nSig,
maType = "EMA")
y <- cbind(mktdata, y[paste(first(index(mktdata)),
last(index(mktdata)),
sep = "/")])
if (anyNA(y[,1])){
y <- y[-which(is.na(y[,1])),]
}
y <- na.locf(y)
y <- y[,c((ncol(y)-1),ncol(y))]
y
}
add.indicator(strategy.st,
name = "MACD",
arguments = list(x=Cl(AAPL)),
label='macd')
add.indicator(strategy.st,
name = "MACD_W1",
arguments = list(mktdata=quote(mktdata)))
add.signal(strategy.st,name="sigCrossover",
arguments = list(columns=c("macd.macd","signal.macd"),relationship="gt"),
label="macd.gt.signal")
add.signal(strategy.st,name="sigCrossover",
arguments = list(columns=c("macd.macd","signal.macd"),relationship="lt"),
label="macd.lt.signal")
add.signal(strategy.st, name="sigFormula",
arguments=list(columns=c("macd.MACD_W1.ind", "signal.MACD_W1.ind"),
formula="(macd.MACD_W1.ind > signal.MACD_W1.ind)",
cross=FALSE),
label="LongCond.W1")
add.signal(strategy.st, name="sigFormula",
arguments=list(columns=c("macd.macd", "signal.macd","LongCond.W1"),
formula="(macd.gt.signal == 1) & (LongCond.W1 == 1)",
cross=FALSE),
label="macd.gt.signal.w1")
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="macd.gt.signal.w1",
sigval=TRUE,
prefer="Open",
orderqty= 100,
ordertype='market',
orderside='long',
orderset='ocolong',
TxnFees = 0),
type='enter',
label='longenter',
enabled=TRUE
)
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="macd.lt.signal",
sigval=TRUE,
prefer="Open",
orderqty='all',
ordertype='market',
orderside='long',
orderset='ocolong',
TxnFees = 0),
type='exit',
label='longexit',
enabled=TRUE
)
macdFastMARange <- seq(2,12,by=5)
macdSlowMARange <- seq(12,24,by=6)
macdSignalRange <- seq(5,15,by=5)
paramset.label.name <- "macd_opt"
add.distribution(strategy.st,
paramset.label = paramset.label.name,
component.type = 'indicator',
component.label = "macd",
variable = list( nFast = macdFastMARange ),
label = "macdFastMARANGE")
add.distribution(strategy.st,
paramset.label = paramset.label.name,
component.type = 'indicator',
component.label = "macd",
variable = list( nSlow = macdSlowMARange ),
label = "macdSlowMARANGE")
add.distribution(strategy.st,
paramset.label = paramset.label.name,
component.type = 'indicator',
component.label = "macd",
variable = list( nSig = macdSignalRange ),
label = "macdSignalRANGE")
add.distribution.constraint(strategy.st,
paramset.label = paramset.label.name,
distribution.label.1 = 'macdFastMARANGE',
distribution.label.2 = 'macdSlowMARANGE',
operator = '<',
label = 'FastMA<SlowMA')
#Single Core - Works
#applyStrategy(strategy=strategy.st,portfolios=strategy.st, verbose=TRUE)
#updatePortf(strategy.st)
#updateAcct(strategy.st)
#updateEndEq(strategy.st)
#DoSNOW Parallel on Windows - Does Not Work
library(doSNOW)
library(parallel)
paramsetenv <- new.env()
cl <- snow::makeCluster(detectCores(), type = "SOCK")
registerDoSNOW(cl)
results <- apply.paramset(strategy.st,
paramset.label=paramset.label.name,
portfolio=strategy.st,
account=strategy.st,
nsamples=0,
verbose = TRUE,
audit=paramsetenv,
calc = "slave")
snow::stopCluster(cl)
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