Improved Moving Average R Function

MAImp.r

# Function to implement a version of the improved moving average functionality
# introduced and tested in:
#
# Papailias, Fotis and Thomakos, Dimitrios D.,
# "An Improved Moving Average Technical Trading Rule,
# (September 11, 2011). Available at SSRN: http://ssrn.com/abstract=1926376
#
# Original code written by Kent Russell @ timelyportfolio.com
#
# Cross-checked by Dimitrios Thomakos on 11/29/2011, @ quantf.com
# Cross-checked by Fotis Papailias on 11/30/2011, @quantf.com
#
# NOTE: this function does not perform the exact methodology 
#       of the paper and results in more trades. Is given for
#       public use for research and back-testing purposes with 
# 		no guarrantees whatsoever!!!
#
# Comment by Fotis Papailias: More care must be taken regarding
# the entry prices. 
#
# All rights reserved & copyright by the above authors.
#

# Main function with additional comments & minor changes
# 
# The research uses daily data, but the function can be used
# for any periodicity

MAImp <- function (x, k1=20, k2=0) 
{
	# Cross-checks
	if ((k1 < 0) | (k2 < 0) | ((k1 > k2) & (k2 > 0))) { stop("k1,k2 must be positive and k1 < k2") }
	
	# Select correctly the closing price if OHLC is loaded
	if(NCOL(x) > 1) x <- x[,4]

	# Get shorter moving average; will use this as the only 
	# moving average if not crossover and will assume no
	# crossover if k2 is not defined
	#
	MAshort <- runMean(x,n=k1)
	if( k2!=0 ) { MAlong <- runMean(x,n=k2) }
	else if (k2 == 0)
	{
		# Swap MAshort for MAlong and assign MAshort as x series
		# Do this so we can use the same function later for the 
		# evaluation of trading signals
		MAlong <- MAshort
		MAshort <- x
	}
	
	# Get the standard MA signals
	signal.ma <- ifelse(MAshort > MAlong, 1, 0)
	
	# Get the entry values for the trailing stop defined in the paper;
	# note the difference with the above...
	x.entry <- ifelse((MAshort > MAlong) & (lag(MAshort,k=1) < lag(MAlong,k=1)), 1, 0) * x

	# This little block will fill in the entry x
	#
	#I have still have not found a better way to accomplish
	#takes longer than I would like
	
	# Select the values of modified cross-over signals only
	entry <- x.entry[which(x.entry!=0)]
	
	# Loop over these values to compute the trailing stop-based signals
	for (i in 1:NROW(entry)) 
	{
		ifelse (i < NROW(entry),
			x.entry[paste(index(entry)[i],index(entry)[i+1],sep="::"),] <- entry[i],
			x.entry[paste(index(entry)[i],sep="::"),] <- entry[i])
	}
	
	# Compute and return the modified signal as well as the standard signal
	signal.mod <- ifelse(x >= x.entry, 1, 0) # Fotis: Strange things here....
	#the "strange things" are without changes later in this function
	#is this signal will reenter whenver closing price crosses
	#back above the entry price
	#after converstation with the authors
	#I realized that the system should not reenter until
	#the standard ma or ma crossover exits and enters as a different signal

	###changed here to insure that crossover still intact
	###to try a different version
	###remove comment on next line if you would like to experiment
	###I prefer the results from this next signal
	#signal.mod <- ifelse(x >= x.entry & signal.ma==1 , 1, 0)

	#add additional logic to insure consistency with research paper
	#if exit on improved signal there is no reentry until
	#a new crossover
	simple.entry <- ifelse((MAshort > MAlong) & (lag(MAshort,k=1) < lag(MAlong,k=1)), 1, 0)
	improved.exit <- ifelse(signal.mod==0 & lag(signal.mod,k=1)==1,-1,0)

	simple.date <- simple.entry[which(simple.entry!=0)]
	improved.date <- improved.exit[which(improved.exit!=0)]

	#initialize this adjusted as signal.mod (varition of implementation)
	#signal.mod.adj will be the the paper's implementation
	signal.mod.adj <- signal.mod
	j=1
	for (i in 1:NROW(improved.date)) {
		#need two counters i and j for this to work
		#since the standard ma (simple.date) and the improved(improved.date)
		#are not aligned
		while (index(improved.date)[i]>index(simple.date)[j])
			if(j+1 < NROW(simple.date))
				j=j+1
			else break #exit while loop if we are at the end
		#print(paste(i,j))

		#turn off all reenter 1s since reentry on the improved
		#should only occur when the standard crosses below/exits and
		#standard crosses above/enters

		signal.mod.adj[paste(index(improved.date)[i],index(simple.date)[j],sep="::"),1]=0
		#fill 1 for the first day of simple.date to align signals
		#if we do not do this then improved will always lag by 1
		#which might amount to foresight on choppy entries
		signal.mod.adj[index(simple.date)[j],1]=1
	}
	#since the signal.mod is now my own
	#I will introduce the change I mentioned above
	#to reenter on the improved only when standard simple is still intact
	signal.mod <- ifelse(x >= x.entry & signal.ma==1 , 1, 0)
	signals <- merge(standard=signal.ma,modified=signal.mod,modified.correct=signal.mod.adj)
	colnames(signals) <- c("Simple","Improved-variation","Improved-original")
	#I think returning xts makes it easier to calculate returns
	#the return will be three signals
	#first column will be standard simple moving average or ma crossover
	#second column will be my unintentional variation of the signal
	#third column will be the signal introduced and tested by the paper
	return(signals)
}

##here is a sample of use of the function
#require(quantmod)
#require(PerformanceAnalytics)
#
#getSymbols("^GSPC", from="1896-01-01", to=Sys.Date())
##use 200-day moving average cross
#signals <- MAImp (x=GSPC, k1=200)
#ret <- merge(rep(ROC(GSPC[,4],type="discrete",n=1),3) * lag(signals,k=1),ROC(GSPC[,4],type="discrete",n=1))
#colnames(ret) <- c(colnames(signals),"BuyHold")
#charts.PerformanceSummary(ret,ylog=TRUE)