apply.paramset returns zero

[JohnLee987]

Hi, I am replicating the reply given by FXQuantTrader in https://stackoverflow.com/questions/48595452/parameter-optimization-with-custom-indicators-quantstrat regarding using apply.paramset. I noticed that currently the final results i.e. resultsopt$tradeStats are all zero. Given the reply has been posted almost 3.5 years ago, has there been any update causing this? I am posting the code below in case needed. FYI, I also tried to use doParallel and registerDoParallel before running apply.paramset (as replied in another open issue here) with no success.

library(quantstrat)
.blotter <<- new.env()
.strategy <<- new.env()  

Sys.setenv(TZ = "UTC")

currency(c('USD'))

symbols <- "AAPL"
getSymbols(symbols)

stock(symbols, currency = "USD")


AAPL <- AAPL["2016/"]

init_date <- "2017-01-07"
start_date <- "2018-01-31"
end_date <- "2018-01-31"
init_equity <- 1e8 # $100,000,000
adjustment <- FALSE


portfolio.st <- "Luxor.Opt"  
account.st <- "Luxor.Opt"
strategy.st <- "Luxor.Opt"

rm.strat(name = portfolio.st)   

initPortf(name = portfolio.st, 
          symbols = symbols)

initAcct(name = account.st,
         portfolios = portfolio.st,
         initEq = init_equity)

initOrders(portfolio = portfolio.st,
           symbols = symbols)

strategy(strategy.st, store = TRUE) 


fastMA_custom2 = 12

slowMA_custom2 = 26

signalMA_custom2 = 9
maType="EMA"
MAforest = 3

forest <- function(x, fastMA_custom, slowMA_custom, signalMA_custom){
  step1 <- EMA(x,fastMA_custom)
  step2 <- EMA(x,slowMA_custom)
  step3 <- step1-step2
  step4 <- EMA(step3,signalMA_custom)
  step5 <- step3-step4
  return(step5)
}

smaforest <- function(x){
  step1 <- EMA(x,fastMA_custom2)
  step2 <- EMA(x,slowMA_custom2)
  step3 <- step1-step2
  step4 <- EMA(step3,signalMA_custom2)
  step5 <- step3-step4
  step6 <- EMA(step5,MAforest)
  return(step6)
}

add.indicator(strategy = strategy.st,
              name ="forest",
              arguments = list(x=quote(Cl(mktdata)),
                               fastMA_custom = 12,
                               slowMA_custom = 26,
                               signalMA_custom = 9
              ),
              label="forest")

add.indicator(strategy=strategy.st,
              name ="smaforest",
              arguments = list(x=quote(Cl(mktdata))),
              label="smaforest")


add.signal(strategy = strategy.st,
           name="sigCrossover",
           arguments = list(columns = c("forest", "smaforest"),
                            relationship = "gte"),
           label = "long")

add.signal(strategy = strategy.st,
           name="sigCrossover",
           arguments = list(columns = c("forest", "smaforest"),
                            relationship = "lte"),
           label = "short")

add.rule(strategy.st,
         name = "ruleSignal",
         arguments = list(sigcol = "long",
                          sigval = TRUE,
                          orderqty = 100000,
                          ordertype = "market",
                          orderside = "long", 
                          TxnFees = -1, 
                          replace = FALSE),
         type = "enter",
         label = "EnterLONG")

add.rule(strategy.st,
         name = "ruleSignal",
         arguments = list(sigcol = "short",
                          sigval = TRUE,
                          orderqty = -100000,
                          ordertype = "market",
                          orderside = "short", 
                          replace = FALSE, 
                          TxnFees = -1
         ),
         type = "enter",
         label = "EnterSHORT")

add.rule(strategy.st, 
         name = "ruleSignal", 
         arguments = list(sigcol = "short", 
                          sigval = TRUE, 
                          orderside = "long", 
                          ordertype = "market", 
                          orderqty = "all", 
                          TxnFees = -1, 
                          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 = -1, 
                          replace = TRUE), 
         type = "exit", 
         label = "Exit2LONG")

addPosLimit(portfolio.st, symbols[], timestamp=init_date, maxpos=500, minpos=0)

# applyStrategy(strategy.st, portfolio.st)
# 
# updatePortf(portfolio.st)
# tradeStats(portfolio.st, symbols)

add.distribution(strategy.st,
                 paramset.label = "forestopt",  #The label we will use when we want to run this optimisation in paramset
                 component.type = "indicator", # The custom function is of indicator type (not other alternatives including signal or rule)
                 component.label = "forest", #this is the name of your custom function
                 variable = list(fastMA_custom = seq(8, 12, by = 2)),
                 label = "myForestOptLabel") #choose whatever you want



resultsopt <- apply.paramset(strategy.st,
                             paramset.label = "forestopt",
                             portfolio.st = portfolio.st,
                             account.st = account.st, 
                             nsamples = 0)

# Check, results are equal in the case where fastMA_custom = 12 compared to when running `applyStrategy`:

resultsopt$tradeStats

myForestOptLabel         Portfolio Symbol Num.Txns Num.Trades Total.Net.Profit Avg.Trade.PL Med.Trade.PL Largest.Winner
1                8 Luxor.Opt.train.1      0        0          0                0            0            0              0
2               10 Luxor.Opt.train.2      0        0          0                0            0            0              0
3               12 Luxor.Opt.train.3      0        0          0                0            0            0              0
  Largest.Loser Gross.Profits Gross.Losses Std.Dev.Trade.PL Std.Err.Trade.PL Percent.Positive Percent.Negative Profit.Factor
1             0             0            0                0                0                0                0             0
2             0             0            0                0                0                0                0             0
3             0             0            0                0                0                0                0             0
  Avg.Win.Trade Med.Win.Trade Avg.Losing.Trade Med.Losing.Trade Avg.Daily.PL Med.Daily.PL Std.Dev.Daily.PL Std.Err.Daily.PL
1             0             0                0                0            0            0                0                0
2             0             0                0                0            0            0                0                0
3             0             0                0                0            0            0                0                0
  Ann.Sharpe Max.Drawdown Profit.To.Max.Draw Avg.WinLoss.Ratio Med.WinLoss.Ratio Max.Equity Min.Equity End.Equity
1          0            0                  0                 0                 0          0          0          0
2          0            0                  0                 0                 0          0          0          0
3          0            0                  0                 0                 0          0          0          0

[jaymon0703]

Hi @JohnLee987 did you resolve this yourself? Sorry i had not taken a look yet.