r语言 - 使用定量分析优化信号参数会导致错误:尝试选择少于一个元素

Question

我在quantstrat中实现了一个简单的只做多布林策略（下面的可重现示例）。代码运行正常，但现在我想优化 sigThreshold 值（即 0.3 和 0.7）。apply.paramset函数运行在定义的参数范围内，但最终显示错误

error calling combine function:
<simpleError in fun(result.1, result.2, 

。

result.137, result.138): attempt to select less than one element>

我不知道

如何解释。我很乐意接受任何建议。请在下面找到代码：

require(quantstrat)
require(foreach)
require(doParallel)
startDate <- '2010-01-01'  
endDate <-  '2015-01-01'   
symbols = c('XLF')
Sys.setenv(TZ='UTC')       

getSymbols(symbols, 
           src='yahoo', 
           index.class=c('POSIXt','POSIXct'),
           from=startDate, to=endDate, 
           adjust=TRUE)

initDate <- startDate
initEq <- 1000000
currency('USD')
stock(symbols, currency='USD',multiplier=1)

rm.strat('bbands') 
initPortf(name='bbands', symbols, initDate=initDate)
initAcct(name='bbands', portfolios='bbands',
         initDate=initDate, initEq=initEq)
initOrders(portfolio='bbands', initDate=initDate)

strategy.st <- 'bbands'
account.st <- 'my.account'
portfolio.st <- 'bollinger'
strategy(strategy.st, store=TRUE)

# add indicators
add.indicator(strategy.st, name = 'BBands',
              arguments = list(HLC = quote(Cl(mktdata)), 
                               maType='SMA', 
                               n=40, 
                               sd=2), 
              label='BBands')

#add signals
add.signal(strategy.st, name='sigThreshold',
           arguments=list(column='pctB', 
                          threshold = 1.0, 
                          relationship='gt', 
                          cross=TRUE),
           label='Cl.gt.UpperBand')
add.signal(strategy.st, name='sigThreshold',
           arguments=list(column ='pctB', 
                          threshold = 0, 
                          relationship='lt', 
                          cross=TRUE),
           label='Cl.lt.LowerBand')
add.signal(strategy.st, name='sigThreshold',
           arguments=list(column ='pctB', 
                          threshold = 0.7, 
                          relationship='gte', 
                          cross = TRUE),
           label='Cl.gte.0.7')
add.signal(strategy.st, name='sigThreshold',
           arguments=list(column ='pctB', 
                          threshold = 0.3, 
                          relationship='lte', 
                          cross = TRUE),
           label='Cl.lt.0.3')

#add rules
add.rule(strategy.st, name='ruleSignal',
         arguments=list(sigcol='Cl.gt.UpperBand',
                        TxnFees = -5,
                        sigval=TRUE, 
                        orderqty= 'all',
                        ordertype='market', 
                        orderside=NULL),
         type='exit')
add.rule(strategy.st, name='ruleSignal',
         arguments=list(sigcol='Cl.lt.LowerBand',
                        TxnFees = -5,
                        sigval=TRUE, 
                        orderqty= 500, 
                        ordertype='market', 
                        orderside=NULL, 
                        osFUN=osMaxPos),
         type='enter')
add.rule(strategy.st, name='ruleSignal',
         arguments=list(sigcol='Cl.gte.0.7',
                        TxnFees = -5,
                        sigval=TRUE, 
                        orderqty= 500,
                        ordertype='market', 
                        orderside=NULL, 
                        osFUN=osMaxPos),
         type='enter')
add.rule(strategy.st, name='ruleSignal',
         arguments=list(sigcol='Cl.lt.0.3',
                        TxnFees = -5,
                        sigval=TRUE, 
                        orderqty='all',
                        ordertype='market', 
                        orderside=NULL),
         type='exit')
# add positon limit
addPosLimit('bbands', 'XLF', timestamp=initDate, maxpos=500, minpos=0)

SD = 2
N = 40
out <- applyStrategy('bbands',
  portfolios='bbands',parameters=list(sd=SD,n=N))

updatePortf('bbands')
updateAcct('bbands')
updateEndEq('bbands')

现在，这就是整个问题的内容

# start optimization here
.upper.range.distribution = seq(0.4, 0.9, by = 0.05)
.lower.range.distribution = seq(0, 0.7, by = 0.05)
add.distribution(strategy.st,
                 paramset.label = 'sigThreshold',
                 component.type = 'signal',
                 component.label = 'Cl.lt.0.3',
                 variable = list(threshold = .lower.range.distribution),
                 label = 'LOWER'
)

add.distribution(strategy.st,
                 paramset.label = 'sigThreshold',
                 component.type = 'signal',
                 component.label = 'Cl.gte.0.7',
                 variable = list(threshold = .upper.range.distribution),
                 label = 'UPPER'
)

add.distribution.constraint(strategy.st,
                            paramset.label = 'sigThreshold',
                            distribution.label.1 = 'LOWER',
                            distribution.label.2 = 'UPPER',
                            operator = '<',
                            label = 'RANGE'
)

rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(portfolio.st, symbols='XLF', initDate=initDate, currency='USD')
initAcct(account.st, portfolios=portfolio.st,
         initDate=initDate, currency='USD')
initOrders(portfolio.st, initDate=initDate)

apply.paramset(strategy.st, paramset.label='sigThreshold',
               portfolio.st=portfolio.st, account.st=account.st, nsamples=0)

Answer 1

您需要在调用apply.paramset之前将头寸限制添加到您的投资组合中。您可能希望将apply.paramset的输出分配给某些内容。 这对我来说是使用最新版本的吸墨仪和定量器。

addPosLimit(portfolio.st, 'XLF', timestamp=initDate, maxpos=500, minpos=0)
ap <- apply.paramset(strategy.st, paramset.label='sigThreshold',
    portfolio.st=portfolio.st, account.st=account.st, nsamples=0)