# Commands that generated the results of Section 2.5 of
# "The Portfolio Probe User's Manual"
#
# These commands demonstrate testing a trading strategy
# using random portfolios
#
# This depends on functions listed in 'pprobe_functions01.R'
# The data are created in 'pprobe_R_data01.txt'
#
# The functions that create the graphs are in 'pprobe_graphFun01.R'
# If you want hardcopies of the graphs, then you need to start a
# graphics device (like 'pdf') and do 'dev.off()' after the graphs
# are created.




# things to CHANGE, possibly

PP_LOC <- ".." 





# initial setup

if(!exists("us.pricemat")) attach(paste(PP_LOC, "us.pricemat.rda", sep="/"))
if(!exists("us.macdmat")) attach(paste(PP_LOC, "us.macdmat.rda", sep="/"))



# These optimizations do not involve a variance (for simplicity)
# Real optimizations almost certainly will, see the file
# 'pprobe_R_varCache.txt' for a method of dealing with 
# large variance matrices


# generate set of starting portfolios
rp.20.w10.2008 <- random.portfolio(20, us.pricemat[502,], gross.value=1e7, 
	long.only=TRUE, max.weight=.1, port.size=20)

# do evaluation of the strategy
evalst.20.w10.t200.2008 <- pp.evalstrat(100, rp.20.w10.2008, 
	us.pricemat[-1:-502,], us.macdmat, frac.turnover=2/252, 
	max.weight=.1, port.size=20, verbose=2, 
	do.warn=c(utility.switch=FALSE, novariance=FALSE))


# do plots

P.evst1Q(NULL)
P.evst2Q(NULL)
P.evst4Q(NULL)