r语言 - 在 Quantstrat 中优化时，运行 add.distribution 和 apply.paramset 后 - r - What step is necessary to get an output after running add.distribution and apply.paramset when optimizing in Quantstrat? 小贝子编程网

我一直在按照以下教程学习如何在quantstrat中测试不同的变量。

https://timtrice.github.io/backtesting-strategies/parameter-optimization.html

有关优化的教程部分位于此链接的第 7 部分中，但它取决于前面的部分。

在我输入apply.paramset后，R不返回任何内容。

如果我输入tradeStats(portfolio.st,'SPY')，它会返回这个;

[1] Portfolio          Symbol             Num.Txns           Num.Trades        
[5] Total.Net.Profit   Avg.Trade.PL       Med.Trade.PL       Std.Err.Trade.PL  
[9] Largest.Winner     Largest.Loser      Gross.Profits      Gross.Losses      
[13] Std.Dev.Trade.PL   Percent.Positive   Percent.Negative   Profit.Factor     
[17] Avg.Win.Trade      Med.Win.Trade      Avg.Losing.Trade   Med.Losing.Trade  
[21] Avg.Daily.PL       Med.Daily.PL       Std.Dev.Daily.PL   Std.Err.Daily.PL  
[25] Ann.Sharpe         Max.Drawdown       Profit.To.Max.Draw Avg.WinLoss.Ratio 
[29] Med.WinLoss.Ratio  Max.Equity         Min.Equity         End.Equity        
<0 rows> (or 0-length row.names)

此数据帧采用我期望的格式，但它没有值。我希望得到的是向我显示慢速和快速 SMA 值的每个组合的值。

我尝试运行apply.strategy，但这给了我相同的结果。

我的理解是，apply.paramset的功能与apply.strategy相似。

我尝试在有和没有这个部分的情况下运行它，它给出了相同的结果。

library(parallel)
if( Sys.info()['sysname'] == "Windows") {
library(doParallel)
registerDoParallel(cores=detectCores())
} else {
library(doMC)
registerDoMC(cores=detectCores())
}

直接取自本教程的代码如下所示。

我在这里缺少什么吗？我浏览了本教程的第 12 部分，并且可以轻松查看第 5 部分的结果，其中不包括发行版。但是，我没有看到任何关于优化后查看结果的内容。

#Tutorial 第 5 部分

library(quantstrat)
library(blotter)
Sys.setenv(TZ = "UTC")
currency('USD')
init_date <- "2007-12-31"
start_date <- "2008-01-01"
end_date <- "2009-12-31"
init_equity <- 1e4 # $10,000
adjustment <- TRUE

basic_symbols <- function() {
symbols <- c(
"IWM", # iShares Russell 2000 Index ETF
"QQQ", # PowerShares QQQ TRust, Series 1 ETF
"SPY" # SPDR S&P 500 ETF Trust
)
}
symbols <- basic_symbols()
getSymbols(Symbols = symbols, 
src = "yahoo", 
index.class = "POSIXct",
from = start_date, 
to = end_date, 
adjust = adjustment)
stock(symbols, 
currency = "USD", 
multiplier = 1)
portfolio.st <- "Port.Luxor"
account.st <- "Acct.Luxor"
strategy.st <- "Strat.Luxor"
rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(name = portfolio.st,
symbols = symbols,
initDate = init_date)
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date,
initEq = init_equity)
initOrders(portfolio = portfolio.st,
symbols = symbols,
initDate = init_date)
strategy(strategy.st, store = TRUE)
add.indicator(strategy = strategy.st,
name = "SMA",
arguments = list(x = quote(Cl(mktdata)), 
n = 10),
label = "nFast")
add.indicator(strategy = strategy.st, 
name = "SMA", 
arguments = list(x = quote(Cl(mktdata)), 
n = 30), 
label = "nSlow")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "gte"),
label = "long")
add.signal(strategy = strategy.st,
name="sigCrossover",
arguments = list(columns = c("nFast", "nSlow"),
relationship = "lt"),
label = "short")
add.rule(strategy = strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "long",
sigval = TRUE,
orderqty = 100,
ordertype = "stoplimit",
orderside = "long", 
threshold = 0.0005,
prefer = "High", 
TxnFees = -10, 
replace = FALSE),
type = "enter",
label = "EnterLONG")
add.rule(strategy.st,
name = "ruleSignal",
arguments = list(sigcol = "short",
sigval = TRUE,
orderqty = -100,
ordertype = "stoplimit",
threshold = -0.005, 
orderside = "short", 
replace = FALSE, 
TxnFees = -10, 
prefer = "Low"),
type = "enter",
label = "EnterSHORT")
add.rule(strategy.st, 
name = "ruleSignal", 
arguments = list(sigcol = "short", 
sigval = TRUE, 
orderside = "long", 
ordertype = "market", 
orderqty = "all", 
TxnFees = -10, 
replace = TRUE), 
type = "exit", 
label = "Exit2SHORT")
add.rule(strategy.st, 
name = "ruleSignal", 
arguments = list(sigcol = "long", 
sigval = TRUE, 
orderside = "short", 
ordertype = "market", 
orderqty = "all", 
TxnFees = -10, 
replace = TRUE), 
type = "exit", 
label = "Exit2LONG")
cwd <- getwd()
setwd("C:\Users\NEW USER\Desktop\RYO\R Working Directory")
results_file <- paste("results", strategy.st, "RData", sep = ".")
if( file.exists(results_file) ) {
load(results_file)
} else {
results <- applyStrategy(strategy.st, portfolios = portfolio.st)
updatePortf(portfolio.st)
updateAcct(account.st)
updateEndEq(account.st)
if(checkBlotterUpdate(portfolio.st, account.st, verbose = TRUE)) {
save(list = "results", file = results_file)
save.strategy(strategy.st)
}
}
setwd(cwd)
#Tutorial, Part 7
.fastSMA <- (1:30)
.slowSMA <- (20:80)
.nsamples <- 5
portfolio.st <- "Port.Luxor.MA.Opt"
account.st <- "Acct.Luxor.MA.Opt"
strategy.st <- "Strat.Luxor.MA.Opt"
rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(name = portfolio.st,
symbols = symbols,
initDate = init_date)
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date,
initEq = init_equity)
initOrders(portfolio = portfolio.st,
symbols = symbols,
initDate = init_date)
strategy(strategy.st, store = TRUE)
rm.strat(portfolio.st)
rm.strat(account.st)
initPortf(name = portfolio.st,
symbols = symbols,
initDate = init_date)
initAcct(name = account.st,
portfolios = portfolio.st,
initDate = init_date)
initOrders(portfolio = portfolio.st,
initDate = init_date)
add.distribution(strategy.st,
paramset.label = "SMA",
component.type = "indicator",
component.label = "nFast",
variable = list(n = .fastSMA),
label = "nFAST")
add.distribution(strategy.st,
paramset.label = "SMA",
component.type = "indicator",
component.label = "nSlow",
variable = list(n = .slowSMA),
label = "nSLOW")
add.distribution.constraint(strategy.st,
paramset.label = "SMA",
distribution.label.1 = "nFAST",
distribution.label.2 = "nSLOW",
operator = "<",
label = "SMA.Constraint")
library(parallel)
if( Sys.info()['sysname'] == "Windows") {
library(doParallel)
registerDoParallel(cores=detectCores())
} else {
library(doMC)
registerDoMC(cores=detectCores())
}
cwd <- getwd()
setwd("C:\Users\NEW USER\Desktop\RYO\R Working Directory")
results_file <- paste("results", strategy.st, "RData", sep = ".")
if( file.exists(results_file) ) {
load(results_file)
} else {
results <- apply.paramset(strategy.st,
paramset.label = "SMA",
portfolio.st = portfolio.st,
account.st = account.st, 
nsamples = .nsamples)
if(checkBlotterUpdate(portfolio.st, account.st, verbose = TRUE)) {
save(list = "results", file = results_file)
save.strategy(strategy.st)
}
}
setwd(cwd)
applyStrategy(strategy.st, portfolios = portfolio.st)
checkBlotterUpdate(portfolio.st, account.st, verbose = TRUE)
updatePortf(portfolio.st)
updateAcct(account.st)
updateAcct(account.st)

嗨@mineralpoint这本书相对于最新版本的quantstrat来说已经很旧了，而且该脚本中的代码顺序不正确。您需要在使用applyStrategy运行原始策略后运行参数优化，并且有一些代码删除 portfolio.st 这就是tradeStats(portfolio.st,'SPY')为空的原因。我能建议的最好的事情是查看 https://github.com/braverock/quantstrat/tree/master/demo 存储库的演示范围。

r语言 - 在 Quantstrat 中优化时，运行 add.distribution 和 apply.paramset 后

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