Hi,
I have been experimenting with different custom transaction fee models for
different assets and I realized that apply.paramset and applyStrategy yields
different results when a custom transaction fee function is used.
The reproducible example is below, and even though apply.paramset yields a
NetPnL result of 21779 with the custom transaction fee model, applyStrategy
yields 21509, which makes me believe that apply.paramset somehow is not
incorporating the fees. The comparison of NetPnL results were made with the
parameter combination of FastSMA=5, SlowSMA=50 and Stoploss=0.005.
Any help is appreciated, thanks.
Atakan Okan
Code:
library(lattice);library(foreach);library(doSNOW);library(ggplot2)library(gridExtra);library(reshape);library(beepr);library(quantstrat)
library(doSNOW)Sys.setenv(TZ="UTC")
.strategy<- new.env();.blotter<- new.env()
currency('USD')
stock("AAPL", currency="USD", multiplier=1,tick_size= 0.01)
getSymbols('AAPL',src = 'yahoo', from="2014-01-01", to="2015-05-31")AAPL <-
adjustOHLC(AAPL)
strategy.st <- paste("AAPL","MACD_D1",sep = "_")rm.strat(strategy.st)
initialEquity = 100000
initDate = "2013-12-30" initPortf(strategy.st, "AAPL",
initDate=initDate, currency = "USD")initAcct(strategy.st,
portfolios=strategy.st, initDate=initDate, initEq=initialEquity, currency =
"USD")initOrders(portfolio=strategy.st,initDate=initDate)
strategy(strategy.st,store=TRUE)
customFees <- function (TxnQty, ...) { return(abs(TxnQty) * -0.01)}txn.model
<- "customFees"
positionSizeLong = 1000 positionSizeShort = -1000
paramset.label.name <- "SMA_OPT"FastSMARange <- seq(5,21,by=8)SlowSMARange <-
seq(10,50,by=20)StopLossDistanceRange <- seq(0.0025,0.005,by=0.0025)
add.indicator(strategy.st,
name = "SMA",
arguments = list(x=Cl(eval(parse(text = "AAPL")))
,n=5 #fastsma of best combination by NetPnL ),
label='fastsma')
add.indicator(strategy.st,
name = "SMA",
arguments = list(x=Cl(eval(parse(text = "AAPL")))
,n=50 #slowsma of best combination by NetPnL ),
label='slowsma')
add.signal(strategy.st, name="sigCrossover", arguments =
list(columns=c("fastsma","slowsma"),relationship="gt"),
label="fastsma.gt.slowsma")
add.signal(strategy.st, name="sigCrossover", arguments =
list(columns=c("fastsma","slowsma"),relationship="lt"),
label="fastsma.lt.slowsma")
add.rule(strategy.st, name='ruleSignal', arguments =
list(sigcol="fastsma.gt.slowsma", sigval=TRUE,
prefer="Open", orderqty=
positionSizeLong, #osFUN="osAllInLong",
ordertype='market', orderside='long',
orderset='ocolong', TxnFees =
txn.model), type='enter', label='longenter',
enabled=FALSE #timespan = xxxx, #store=TRUE
#storefun=FALSE )
# Long Exit
Rule-------------------------------------------------------------------add.rule(strategy.st,
name='ruleSignal', arguments =
list(sigcol="fastsma.lt.slowsma", sigval=TRUE,
prefer="Open", orderqty='all',
ordertype='market',
orderside='long', orderset='ocolong',
TxnFees = txn.model), type='exit', label='longexit',
enabled=FALSE #timespan = xxxx, #store=TRUE)
# Long StopLoss
Rule---------------------------------------------------------------------------add.rule(strategy.st,name='ruleSignal',
arguments = list( sigcol="fastsma.lt.slowsma", sigval=TRUE,
replace=FALSE, orderside='long',
ordertype='stoplimit',
tmult=TRUE, threshold=quote( longStopLossDistance ),
orderqty='all',
orderset='ocolong', TxnFees = txn.model),
type='chain', parent="longenter", label='StopLossLong',
enabled=FALSE)
# Short Entry
Rule--------------------------------------------------------------------add.rule(strategy.st,
name='ruleSignal', arguments =
list(sigcol="fastsma.lt.slowsma", sigval=TRUE,
prefer="Open",
orderqty=positionSizeShort, #osFUN="osAllInShort",
ordertype='market',
orderside='short', orderset='ocoshort',
TxnFees = txn.model), type='enter',
label='shortenter', enabled=FALSE #timespan = xxxx,
#store=TRUE #storefun=FALSE )
# Short Exit
Rule---------------------------------------------------------------------add.rule(strategy.st,
name='ruleSignal', arguments =
list(sigcol="fastsma.gt.slowsma", sigval=TRUE,
prefer="Open", orderqty='all',
ordertype='market',
orderside='short', orderset='ocoshort',
TxnFees = txn.model), type='exit', label='shortexit',
enabled=FALSE #timespan = xxxx, #store=TRUE)
# Short Stop Loss
Rule-----------------------------------------------------------------add.rule(strategy.st,name='ruleSignal',
arguments = list( sigcol="fastsma.gt.slowsma", sigval=TRUE,
replace=FALSE, orderside='short',
ordertype='stoplimit',
tmult=TRUE, threshold=quote( shortStopLossDistance ),
orderqty='all',
orderset='ocoshort', TxnFees = txn.model),
type='chain', parent="shortenter", label='StopLossShort',
enabled=FALSE)
#Indicator
Optimization-------------------------------------------------------------add.distribution(strategy.st,
paramset.label = paramset.label.name,
component.type = 'indicator', component.label = "fastsma",
variable = list( n = FastSMARange ),
label = "FastSMARANGE")
add.distribution(strategy.st, paramset.label =
paramset.label.name, component.type = 'indicator',
component.label = "slowsma", variable = list( n =
SlowSMARange ), label = "SlowSMARANGE")
add.distribution.constraint(strategy.st,
paramset.label = 'SMA_OPT', distribution.label.1 =
'FastSMARANGE', distribution.label.2 =
'SlowSMARANGE', operator = '<',
label = 'FastSMA<SlowSMA')
#SL/Trail-SL/TP
Optimization-----------------------------------------------------------------
#Long Stoploss Optimizationadd.distribution(strategy.st,
paramset.label = paramset.label.name, component.type = "chain",
component.label = "StopLossLong", variable =
list( threshold = StopLossDistanceRange ), label =
"StopLossLONG")
#Short Stoploss Optimizationadd.distribution(strategy.st,
paramset.label = paramset.label.name, component.type = "chain",
component.label = "StopLossShort", variable =
list( threshold = StopLossDistanceRange ), label =
"StopLossSHORT")
#Long&Short Stoploss Distance
Constraintadd.distribution.constraint(strategy.st,
paramset.label = paramset.label.name,
distribution.label.1 = "StopLossLONG",
distribution.label.2 = "StopLossSHORT", operator =
"==", label = "StoplossEquality")
enable.rule(strategy.st,type="enter",label="longenter", enable = TRUE)
enable.rule(strategy.st,type="exit",label="longexit", enable =
TRUE)enable.rule(strategy.st,type="enter",label="shortenter", enable = TRUE)
enable.rule(strategy.st,type="exit",label="shortexit", enable =
TRUE)enable.rule(strategy.st,type="chain",label="StopLossLong", enable =
TRUE)enable.rule(strategy.st,type="chain",label="StopLossShort", enable = TRUE)
summary(getStrategy(strategy.st))
#First run apply.paramset()paramsetenv<-new.env()cl <- snow::makeCluster(4,
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)snow::stopCluster(cl)results.df <-
data.frame(results$tradeStats)
#Second run applyStrategy()longStopLossDistance <- 0.005 #SL
of best combination by NetPnLshortStopLossDistance <- 0.005
#SL of best combination by NetPnL
applyStrategy( strategy=strategy.st , portfolios=strategy.st
,verbose=TRUE)updatePortf(strategy.st)updateAcct(strategy.st)updateEndEq(strategy.st)
results.df.2 <- data.frame(tradeStats(strategy.st))
#Check NetPnL resulting from apply.paramset vs
applyStrategyresults.df$Net.Trading.PL[12] == results.df.2$Net.Trading.PL
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