我在Quantstrat上使用交易统计学，并获得了看好这个世界的正面结束股票（起始资产= 1m）。然而，令人费解的是，当我制作表格时累积回报为-1.0。
您如何才能获得正的期末权益和负累积回报？我对结束股权的理解是错误的吗？
library(quantmod)
library(FinancialInstrument)
library(PerformanceAnalytics)
library(foreach)
library(blotter)
library(quantstrat)
options("getSymbols.yahoo.warning"=FALSE)
options("getSymbols.warning4.0"=FALSE)
initDate="1990-01-01"
from ="2009-01-01"
to ="2013-01-01"
symbols = c("SPY")
currency("USD")
getSymbols(symbols, from=from, to=to, adjust=TRUE)
stock(symbols, currency="USD", multiplier=1)
initEq=1000000
strategy.st <- portfolio.st <- account.st <- "mystrat"
rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(name=portfolio.st,
symbols=symbols,
initDate=initDate,
currency='USD')
initAcct(name=account.st,
portfolios=portfolio.st,
initDate=initDate,
currency='USD',
initEq=initEq)
initOrders(portfolio=portfolio.st,
initDate=initDate)
strategy(strategy.st, store=TRUE)
### Add Indicators
nRSI <- 21
buyThresh <- 50
sellThresh <- 50
#Indicator for EMA long medium short
nEMAL<- 200
nEMAM<- 30
nEMAS<- 13
nEMAF<- 5
add.indicator(strategy.st, name="RSI",
arguments=list(price=quote(Cl(mktdata)), n=nRSI),
label="rsi")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAL),
label="EMAL")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAM),
label="EMAM")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAS),
label="EMAS")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAF),
label="EMAF")
upsig <- function(data) {
sig <- data[, "rsi"] >50 & data[, "EMA.EMAM"] > data[, "EMA.EMAL"]
colnames(sig) <- "upSig"
sig
}
downsig <- function(data) {
sig <- data[, "rsi"] <50 & data[, "EMA.EMAM"] < data[, "EMA.EMAL"]
colnames(sig) <- "downSig"
sig
}
### Add Signal- Enter
add.signal(strategy.st, name="upsig",
arguments=list(data = quote(mktdata)),
label = "entersig")
add.signal(strategy.st, name="downsig",
arguments=list(data = quote(mktdata)),
label = "exitsig")
### Add rule - Enter
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="upSig.entersig",
sigval=TRUE,
orderqty=1000,
ordertype='market',
orderside='long',
threshold=NULL),
type='enter',
path.dep=TRUE)
### Add rule- Exit
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="downSig.exitsig",
sigval=TRUE,
orderqty= -1000,
ordertype='market',
orderside='long',
pricemethod='market',
replace=FALSE),
type='exit',
path.dep=TRUE)
start_t<-Sys.time()
out<-try(applyStrategy(strategy=strategy.st,
portfolios=portfolio.st))
updatePortf(portfolio.st)
updateAcct(portfolio.st)
updateEndEq(account.st)
for(symbol in symbols) {
chart.Posn(
Portfolio=portfolio.st,
Symbol=symbol,
log=TRUE)
}
tstats <- tradeStats(portfolio.st)
t(tstats)
rets <- PortfReturns(Account = account.st)
rownames(rets) <- NULL
charts.PerformanceSummary(rets, colorset = bluefocus)
tab.perf <- table.Arbitrary(rets,
metrics=c(
"Return.cumulative",
"Return.annualized",
"SharpeRatio.annualized",
"CalmarRatio"),
metricsNames=c(
"Cumulative Return",
"Annualized Return",
"Annualized Sharpe Ratio",
"Calmar Ratio"))
tab.perf
#Test here
#test <-try(applyIndicators(strategy.st,mktdata=OHLC(AAPL)))
#head(test, n=40)
答案 0 :(得分：2)
首先，你只进入很多多头头寸。然后是很多连续的退出交易！问题是你在很长一段时间内在每个信号条上获得长信号。并且您并没有限制您的策略进入越来越多的多头头寸，每个头寸1000个。您可以使用osMaxPos和addPosLimit来处理限制仓位时的交易量向特定方向开放。
在这里，您可以停止在每个栏上发生如此多的长条目。当rsi在上方和下方超过50时，您希望条目为真。使用sigCrossover。其次，使用addPosLimit来限制允许的总职位数量。看看mktdata下次调试你的策略，检查你没有一行接一个多个输入信号。
您获得-1暨回报，因为您提供了无意义的输入。如此多的购买（你在每个连续的一天购买1k单位，而入口信号是真的，然后连续多天出售）。很明显，这不是预期的。检查getTxns的输出以查看问题。此外，您的最终资产可能是负数，因为您只是将您的投资组合中的现金PnL加到您的初始资本中。即，一旦您的实际资产变为负数，量子计划就不会停止交易。您可以这样想：即使您的损失超过初始权益，quantstrat也只是保持交易，假设您有更多的资金可以交易。
如果您使用合理的参数，您的权益将永远不会在量化策略中出现负值（除非您的策略非常糟糕且一直失去现金，或者您在回溯测试中进行了很长时间的交易，因此破产或更糟的情况具有相当大的概率发生在允许的时间。）
这里有一些调整，即sigCrossover，并使用交易规模300，在您的策略中获得更明智的数字。也使用osMaxPos。它仍然在这里购买最多3个级别的堆叠仓位。
library(quantmod)
library(FinancialInstrument)
library(PerformanceAnalytics)
library(foreach)
library(blotter)
library(quantstrat)
options("getSymbols.yahoo.warning"=FALSE)
options("getSymbols.warning4.0"=FALSE)
initDate="1990-01-01"
from ="2009-01-01"
to ="2013-01-01"
symbols = c("SPY")
currency("USD")
getSymbols(symbols, from=from, to=to, adjust=TRUE)
stock(symbols, currency="USD", multiplier=1)
initEq=1000000
strategy.st <- portfolio.st <- account.st <- "mystrat"
rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(name=portfolio.st,
symbols=symbols,
initDate=initDate,
currency='USD')
initAcct(name=account.st,
portfolios=portfolio.st,
initDate=initDate,
currency='USD',
initEq=initEq)
initOrders(portfolio=portfolio.st,
initDate=initDate)
strategy(strategy.st, store=TRUE)
### Add Indicators
nRSI <- 21
buyThresh <- 50
sellThresh <- 50
#Indicator for EMA long medium short
nEMAL<- 200
nEMAM<- 30
nEMAS<- 13
nEMAF<- 5
tradeSize <- 100
for (sym in symbols) {
addPosLimit(portfolio.st, sym, start(get(sym)), maxpos = 300, longlevels = 3)
}
add.indicator(strategy.st, name="RSI",
arguments=list(price=quote(Cl(mktdata)), n=nRSI),
label="rsi")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAL),
label="EMAL")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAM),
label="EMAM")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAS),
label="EMAS")
add.indicator(strategy.st, name="EMA",
arguments=list(x=quote(Cl(mktdata)), n=nEMAF),
label="EMAF")
# important to set cross = TRUE in sigThreshold
add.signal(strategy.st, name = "sigThreshold",
arguments = list(column = "rsi", threshold = 50, relationship = "gt", cross = TRUE),
label = "rsiUp")
add.signal(strategy.st, name = "sigThreshold",
arguments = list(column = "rsi", threshold = 50, relationship = "lt", cross = TRUE),
label = "rsiDn")
upsig <- function(data) {
sig <- data[, "rsiUp"] & data[, "EMA.EMAM"] > data[, "EMA.EMAL"]
colnames(sig) <- "upSig"
sig
}
downsig <- function(data) {
sig <- data[, "rsiDn"] & data[, "EMA.EMAM"] < data[, "EMA.EMAL"]
colnames(sig) <- "downSig"
sig
}
### Add Signal- Enter
add.signal(strategy.st, name="upsig",
arguments=list(data = quote(mktdata)),
label = "entersig")
add.signal(strategy.st, name="downsig",
arguments=list(data = quote(mktdata)),
label = "exitsig")
### Add rule - Enter
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="upSig.entersig",
sigval=TRUE,
orderqty=100,
ordertype='market',
orderside='long',
threshold=NULL,
osFUN = osMaxPos), # <- need this to cap trade levels to at most 3
type='enter',
path.dep=TRUE)
### Add rule- Exit
add.rule(strategy.st,
name='ruleSignal',
arguments = list(sigcol="downSig.exitsig",
sigval=TRUE,
orderqty= -100,
ordertype='market',
orderside='long',
pricemethod='market',
replace=FALSE),
type='exit',
path.dep=TRUE)
start_t<-Sys.time()
out<-try(applyStrategy(strategy=strategy.st,
portfolios=portfolio.st))
updatePortf(portfolio.st)
updateAcct(portfolio.st)
updateEndEq(account.st)
for(symbol in symbols) {
chart.Posn(
Portfolio=portfolio.st,
Symbol=symbol,
log=TRUE)
}
tstats <- tradeStats(portfolio.st)
t(tstats)
rets <- PortfReturns(Account = account.st)
rownames(rets) <- NULL
charts.PerformanceSummary(rets, colorset = bluefocus)
tab.perf <- table.Arbitrary(rets,
metrics=c(
"Return.cumulative",
"Return.annualized",
"SharpeRatio.annualized",
"CalmarRatio"),
metricsNames=c(
"Cumulative Return",
"Annualized Return",
"Annualized Sharpe Ratio",
"Calmar Ratio"))
tab.perf
tail(.blotter$account.mystrat$summary)
# Additions Withdrawals Realized.PL Unrealized.PL Interest Gross.Trading.PL Txn.Fees Net.Trading.PL Advisory.Fees Net.Performance End.Eq
# 2012-12-20 19:00:00 0 0 0 -392.4 0 -392.4006 0 -392.4006 0 -392.4006 1012255
# 2012-12-23 19:00:00 0 0 0 -132.0 0 -131.9961 0 -131.9961 0 -131.9961 1012123
# 2012-12-25 19:00:00 0 0 0 -180.0 0 -180.0018 0 -180.0018 0 -180.0018 1011943
# 2012-12-26 19:00:00 0 0 0 -57.0 0 -57.0006 0 -57.0006 0 -57.0006 1011886
# 2012-12-27 19:00:00 0 0 0 -459.0 0 -458.9997 0 -458.9997 0 -458.9997 1011427
# 2012-12-30 19:00:00 0 0 0 714.0 0 714.0015 0 714.0015 0 714.0015 1012141