R:Quantstrat如何在投资组合中进行完全股权交易？

我仍然在和盖伊·约林的《量子战略》打交道。在这个例子中，他在间谍公司10天的并购交易中买入1000股。既然我们定义了初始股权，那么是否有可能总是购买整个投资组合，而不仅仅是900股？”“所有”都不适用于入口，只适用于出口

if (!exists('.blotter')) .blotter <- new.env()
if (!exists('.strategy')) .strategy <- new.env()
if (!exists('.instrument')) .instrument <- new.env()
currency("USD")
stock("SPY",currency="USD",multiplier=1)
ls(envir=FinancialInstrument:::.instrument)


initDate <- '1997-12-31'
startDate <- '1998-01-01'
endDate <- '2013-07-31'
initEq <- 1e6
Sys.setenv(TZ="UTC")
getSymbols('SPY', from=startDate, to=endDate, adjust=T)
SPY=to.monthly(SPY, indexAt='endof')
SPY$SMA10m <- SMA(Cl(SPY), 10)

# inz portfolio, account
qs.strategy <- "qsFaber"
rm.strat(qs.strategy) # remove strategy etc. if this is a re-run
initPortf(qs.strategy,'SPY', initDate=initDate)
initAcct(qs.strategy,portfolios=qs.strategy, initDate=initDate, initEq=initEq)


initOrders(portfolio=qs.strategy,initDate=initDate)
# instantiate a new strategy object
strategy(qs.strategy,store=TRUE)
add.indicator(strategy = qs.strategy, name = "SMA",
              arguments = list(x = quote(Cl(mktdata)), n=10), label="SMA10")
add.signal(qs.strategy,name="sigCrossover",
           arguments = list(columns=c("Close","SMA10"),relationship="gt"),
           label="Cl.gt.SMA")
add.signal(qs.strategy,name="sigCrossover",
           arguments = list(columns=c("Close","SMA10"),relationship="lt"),
           label="Cl.lt.SMA")

add.rule(qs.strategy, name='ruleSignal',
         arguments = list(sigcol="Cl.gt.SMA", sigval=TRUE, orderqty=900,
                          ordertype='market', orderside='long', pricemethod='market'),
         type='enter', path.dep=TRUE)
add.rule(qs.strategy, name='ruleSignal',
         arguments = list(sigcol="Cl.lt.SMA", sigval=TRUE, orderqty='all',
                          ordertype='market', orderside='long', pricemethod='market'),
         type='exit', path.dep=TRUE)


out <- applyStrategy(strategy=qs.strategy , portfolios=qs.strategy)
updatePortf(qs.strategy)
updateAcct(qs.strategy)
updateEndEq(qs.strategy)

myTheme<-chart_theme()
myTheme$col$dn.col<-'lightblue'
myTheme$col$dn.border <- 'lightgray'
myTheme$col$up.border <- 'lightgray'
# plot performance
chart.Posn(qs.strategy, Symbol = 'SPY', Dates = '1998::',theme=myTheme)
plot(add_SMA(n=10,col=4, on=1, lwd=2))

---

如果（！exists（'.blotter'））.blotter您不能对条目使用
orderqty=“all”
，因为
“all”
指的是当前位置大小（即，当您想退出整个位置时）

可以购买等于总可用投资组合权益的金额，但必须定义自定义订单大小调整函数。该功能必须对书进行标记（使用
updateport f
），以确定可用权益的金额。
我知道这个问题很久以前就发布了，但请查看软件包“IKTrading”和订单调整功能“osMaxDollar”；使用此订单调整功能时，可以设置每笔交易的美元价值和总头寸

这里有一个玩具示例，可以实现您想要的

您需要引入订单大小调整功能

查看函数
ruleSignal
（例如
formals（ruleSignal）
和
？ruleSignal
）的参数

您将看到有一个参数
osFUN
，您可以在该参数中编写自定义函数来确定订单大小

您可以在
add.rule
中修改适当的参数，以引入订单大小调整（分录交易）

osFUN\u all\u eq Thx为您解答。你有一个如何做到这一点的例子的链接吗？@MichiZH:没有，但是有没有任何提示我如何获得我可以在这些规则中使用的当前股本？我的意思是，这样一个定制订单规模功能需要访问当前的权益…@MichiZH:我已经告诉过你了。使用
updatePorf
标记这本书。很抱歉，我对R还是新手，尤其是quantstrat、quantmod等。学习曲线非常陡峭。很抱歉，我第一次不理解，仍然不知道如何实现它。
osFUN_all_eq <- function (data, timestamp, orderqty, ordertype, orderside, equity, portfolio, symbol, ruletype, ..., initEq) {
    datePos <- format(timestamp,"%Y-%m-%d")

    updatePortf(Portfolio = portfolio, Symbol = symbol, Dates = paste0(start(data), "/", datePos))

    trading_pl <- sum(.getPortfolio(portfolio)$summary$Net.Trading.PL)
    # The total equity in the strategy for this symbol (and this symbol only in isolation always, as this is how quantstrat by default works with applyStrategy)
    equity <- initEq + trading_pl
    ClosePrice <- getPrice(data, prefer = "Close")[datePos]
    UnitSize <- as.numeric(trunc(equity / ClosePrice))
    UnitSize <- osMaxPos(data, timestamp, UnitSize, ordertype, orderside, portfolio, symbol, ruletype, digits=0)
    UnitSize
}





library(quantstrat)

currency("USD")
stock("SPY",currency="USD",multiplier=1)


initDate <- '1997-12-31'
startDate <- '1998-01-01'
endDate <- '2013-07-31'
initEq <- 1e6
Sys.setenv(TZ="UTC")
getSymbols('SPY', from=startDate, to=endDate, adjust=T)
SPY=to.monthly(SPY, indexAt='endof')
SPY$SMA10m <- SMA(Cl(SPY), 10)


qs.strategy <- "qsFaber"
rm.strat(qs.strategy) # remove strategy etc. if this is a re-run
initPortf(qs.strategy,'SPY', initDate=initDate)
initAcct(qs.strategy,portfolios=qs.strategy, initDate=initDate, initEq=initEq)


initOrders(portfolio=qs.strategy,initDate=initDate)
# instantiate a new strategy object
strategy(qs.strategy,store=TRUE)


# Specify the max quantity you could hold in the SPY instrument.  Here we simply assume 1e5 units. You could reduce this number to limit the exposure
max_qty_traded <- 1e5
addPosLimit(qs.strategy, "SPY", timestamp = startDate, maxpos = max_qty_traded)

add.indicator(strategy = qs.strategy, name = "SMA",
              arguments = list(x = quote(Cl(mktdata)), n=10), label="SMA10")
add.signal(qs.strategy,name="sigCrossover",
           arguments = list(columns=c("Close","SMA10"),relationship="gt"),
           label="Cl.gt.SMA")
add.signal(qs.strategy,name="sigCrossover",
           arguments = list(columns=c("Close","SMA10"),relationship="lt"),
           label="Cl.lt.SMA")

add.rule(qs.strategy, name='ruleSignal',
         arguments = list(sigcol="Cl.gt.SMA",
                          sigval=TRUE,
                          orderqty = 1, # the acutal orderqty size becomes redundant when supplying a function to the argument `osFUN`
                          osFUN = osFUN_all_eq,
                          ordertype='market', orderside='long', pricemethod='market'),
         type='enter', path.dep=TRUE)


add.rule(qs.strategy, name='ruleSignal',
         arguments = list(sigcol="Cl.lt.SMA",
                          sigval=TRUE,
                          orderqty='all', # flatten all open long positions
                          ordertype='market',
                          orderside='long',
                          pricemethod='market'),
                          type='exit',
         path.dep=TRUE)


# supply initEq parameter and its value, which pass through to `osFUN`
out <- applyStrategy(strategy=qs.strategy , portfolios=qs.strategy, initEq=initEq)
updatePortf(qs.strategy)
updateAcct(qs.strategy)
updateEndEq(qs.strategy)

myTheme<-chart_theme()
myTheme$col$dn.col<-'lightblue'
myTheme$col$dn.border <- 'lightgray'
myTheme$col$up.border <- 'lightgray'
# plot performance
chart.Posn(qs.strategy, Symbol = 'SPY', Dates = '1998::',theme=myTheme)
plot(add_SMA(n=10,col=4, on=1, lwd=2))