So i have a Trading Strategy that on average has a Max Drawdown that is greater than 20%. I would like to find a way to optimize maxDrawdown()
. However looking into it, I found good articles showing how to this via DEoptim()
but only showed examples for portfolio optimization. I do not know if it is feasible this way?
#Choose the Adjusted Close of a Symbol
stock <- Ad(TNA)
# I want to create a table with all possible combinations from the ranges below
i = c(3:45)
k = c(3:45)
j = c(3:45)
# stores possible combinations into z
z <- expand.grid(i,k,j)
z <- z[z[,1]<z[,2], ]
colnames(z)<- c("one","two","three")
row.names(z)<- c(paste(z[,1],z[,2],z[,3],sep=","))
# Function that will be used
getStratRet <- function(nFast, nSlow, nSig, stock, stockret) {
x <- MACD((stock), nFast=nFast, nSlow=nSlow, nSig=nSig, maType="EMA")
x <- na.omit(x)
sig <- Lag(ifelse((x$macd <= x$signal),-1, 0)) + Lag(ifelse((x$macd >= x$signal),1, 0))
return(na.omit(stockret * sig))
}
# time elapsed for 3:45 combinations: 479.886 seconds,
system.time(
Returns <- do.call(merge, mapply(FUN = getStratRet, nFast = z[,1], nSlow = z[,2], nSig
= z[,3], MoreArgs = list(stock = stock, stockret = stockret), SIMPLIFY = TRUE))
)
#My strategy returns a matrix of returns
View(Returns[1:10,1:5])
row.names 3,4,3 3,5,3 4,5,3 3,6,3 4,6,3
2011-01-11 -0.0035308990 NA NA NA NA
2011-01-12 0.0090226176 0.0090226176 0.0090226176 NA NA
2011-01-13 -0.0016647249 -0.0016647249 -0.0016647249 -0.0016647249 -0.0016647249
2011-01-14 0.0072214466 0.0072214466 0.0072214466 0.0072214466 0.0072214466
2011-01-18 0.0017353225 0.0017353225 0.0017353225 0.0017353225 0.0017353225
2011-01-19 -0.0098735504 -0.0098735504 -0.0098735504 -0.0098735504 -0.0098735504
2011-01-20 0.0013350023 0.0013350023 0.0013350023 0.0013350023 0.0013350023
2011-01-21 -0.0022517836 -0.0022517836 -0.0022517836 -0.0022517836 -0.0022517836
2011-01-24 -0.0056487939 -0.0056487939 -0.0056487939 -0.0056487939 -0.0056487939
2011-01-25 0.0005796862 0.0005796862 0.0005796862 0.0005796862 0.0005796862
I have created a function to optimize by DEoptim()
called MAXDD
this function calculates maxDrawdown
(from PerformanceAnalytics
) for each return.
# MAX DrawDown
MAXDD <- function(ret) {
ret <- na.omit(ret)
maxdd<- maxDrawdown(ret)
return (maxdd)
}
# MAX DRAWDOWN
system.time(
MaxDraw <- sapply(Returns, FUN = MAXDD)
)
Then I use DEoptim()
for the function that I want to minimize: MAXDD
library(DEoptim)
lower <- c(-0.10, 0) # I think this sets the max drawdown that will be acceptable
upper<- -lower # I think this will set what the maximum return acceptable
res <- DEoptim(MAXDD,lower,upper, control=list(NP=2000, itermax=10))
# I set the iteration to 5, to print them here:
Iteration: 1 bestvalit: -0.000000 bestmemit: 0.051143 0.000000
Iteration: 2 bestvalit: -0.000000 bestmemit: 0.034017 0.000000
Iteration: 3 bestvalit: -0.000000 bestmemit: 0.020190 0.000000
Iteration: 4 bestvalit: -0.000000 bestmemit: 0.028910 0.000000
Iteration: 5 bestvalit: -0.000000 bestmemit: 0.038250 0.000000
This is where i am stuck as I do not know if I am doing this correctly? I do not know how to translate this to use in my objective.