【发布时间】：2016-03-22 21:51:08
【问题描述】：
我正在尝试测试一些涉及数字货币的交易策略。其中一种策略涉及 MACD 交叉，但我想优化 nSlow 和 nFast 参数。
这是一个可重现的示例（运行）：
library(httr)
library(plyr)
library(quantstrat)
library(PerformanceAnalytics)
library(IKTrading) # install_github("IlyaKipnis/IKTrading")
poloniex.ohlc.30m <- content(GET("https://poloniex.com/public?command=returnChartData¤cyPair=BTC_ETH&start=1439010600&end=9999999999&period=1800")) # https://poloniex.com/support/api/
ETHBTC.30m <- ldply(poloniex.ohlc.30m, data.frame) # Convert OHLCV to data.frame
ETHBTC.30m$date <- as.POSIXct(ETHBTC.30m$date, origin = "1970-01-01")
# Create 'xts' object:
ethbtc.30m.xts <- xts(ETHBTC.30m[, 2:8], order.by = ETHBTC.30m$date) # is.OHLCV(ETHBTC.30m)
# Rebuild empty environments if RStudio's "Clear All" has been used:
if (!exists('.instrument')) .instrument <- new.env()
if (!exists('.blotter')) .blotter <- new.env()
if (!exists('.strategy')) .strategy <- new.env()
## Optional: Subset timeframe
ETHBTC <- ethbtc.30m.xts[,c("open", "high", "low", "close", "volume")]["2016-02-01::"]
## Define instruments
currency(c('BTC', 'ETH')) # ls_currencies()
exchange_rate('ETHBTC', currency = 'BTC', counter_currency = 'ETH', tick_size = 0.00001)
initDate = '2016-02-01'
initBTC <- 100
initETH <- 0
portfolio.name <- "crypto"
account.name <- "poloniex"
strategy.name <- "accumulator"
symbols <- "ETHBTC"
## To rerun
rm.strat(portfolio.name)
rm.strat(account.name)
rm.strat(strategy.name)
## Initialize Portfolio, Account, and Orderbook
initPortf(name = portfolio.name, symbols = symbols, initPosQty = 0, initDate = initDate, currency = "BTC") # getPortfolio(portfolio.name)
initAcct(name = account.name, portfolios = portfolio.name, initDate = initDate, initEq = 0, currency = "BTC") # getAccount(account.name)
initOrders(portfolio = portfolio.name, symbols = symbols, initDate = initDate) # getOrderBook(portfolio.name)
strategy(strategy.name, store = TRUE) # summary(getStrategy(strategy.name))
## Indicators
# Parameters
.nFast = 60 # 90
.nSlow = 130
.nSig = 45 # 75
add.indicator(strategy.name, name = "MACD", arguments = list(x=quote(Cl(mktdata))), label=NULL)
## Signals
# See Also: applySignals add.indicator link{add.rule} sigComparison sigCrossover sigFormula sigPeak sigThreshold
# MACD
add.signal(strategy.name, "sigCrossover",
arguments = list(columns = c("macd.MACD.ind", "signal.MACD.ind"), relationship = "gt"),
label = 'longEntry')
add.signal(strategy.name, "sigCrossover",
arguments = list(columns = c("signal.MACD.ind", "macd.MACD.ind"), relationship = "gt"),
label = 'signal.gt.macd')
add.signal(strategy.name, "sigThreshold",
arguments = list(column = "macd.MACD.ind", threshold = 0, relationship = "gte"),
label = 'macd.gte.threshold')
add.signal(strategy.name, "sigAND",
arguments=list(columns=c('signal.gt.macd', 'macd.gte.threshold'), cross=FALSE),
label="longExit")
# Order sizing
osFixedDollar <- function(timestamp, orderqty, portfolio, symbol, ruletype, ...)
{
ClosePrice <- as.numeric(Cl(mktdata[timestamp,]))
orderqty <- round(tradeSize/ClosePrice,-2)
return(orderqty)
}
tradeSize <- initBTC/2
## Rules
# Entry
add.rule(strategy.name,name='ruleSignal',
arguments = list(sigcol="longEntry",
sigval=TRUE,
orderqty=1000,
ordertype='market',
orderside='long',
osFUN='osFixedDollar'),
type='enter',
label='EnterLONG',
storefun=FALSE)
# Exit
add.rule(strategy.name,name='ruleSignal',
arguments = list(sigcol="longExit",
sigval=TRUE,
orderqty='all',
ordertype='market',
orderside='long',
osFUN='osFixedDollar'),
type='exit',
label='ExitLONG',
storefun=FALSE)
## Run it
applyStrategy(strategy.name,
portfolios=portfolio.name,
parameters=list(nFast = .nFast, nSlow = .nSlow, nSig = .nSig, maType = 'EMA'),
verbose=TRUE)
updatePortf(Portfolio=portfolio.name,Dates=paste('::',as.Date(Sys.time()),sep=''))
updateAcct(account.name)
updateEndEq(account.name)
## Evaluate
t(tradeStats(portfolio.name))
getTxns(portfolio.name, Symbol = 'ETHBTC')
perTradeStats(portfolio.name, "ETHBTC")
chart.Posn(Portfolio=portfolio.name,Symbol=symbols, type = "line", log.scale = T)
plot(add_Vo())
plot(add_MACD(fast=.nFast, slow=.nSlow, signal=.nSig,maType="EMA")) # nFast = 60, nSlow = 180, nSig = 40, maType = 'EMA'
上面运行得非常好。但是，我想将 nFast 和 nSlow 参数更改为 MACD() 函数：
## Parameter distribution testing
add.distribution(strategy.name,
paramset.label = 'optEMA',
component.type = 'indicator',
component.label = 'nFast',
variable = list(nFast = 60:80),
label = 'NFAST')
add.distribution(strategy.name,
paramset.label = 'optEMA',
component.type = 'indicator',
component.label = 'nSlow',
variable = list(nFast = 180:200),
label = 'NSLOW')
library(doMC)
registerDoMC(cores=detectCores())
results <- apply.paramset(strategy.name, paramset.label = "optEMA", portfolio=portfolio.name, account=account.name, nsamples=0)
这给了我以下错误，我不确定如何调试：
error calling combine function:
<simpleError in fun(result.1, result.2, result.3, result.4, result.5, result.6, ... attempt to select less than one element>
我做错了什么？ FWIW，我使用的是 Ubuntu 12.04/14.04。任何帮助深表感谢。谢谢！！
【问题讨论】：
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请不要cross post。或者，至少，告诉人们您正在交叉发帖，这样他们就不会浪费时间回答在他们不关注的论坛上已经回答的问题。
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@JoshuaUlrich 对此感到抱歉。以后我会记下来的。
标签： r quantmod quantstrat domc blotter