FX and Stop Loss

	#*****************************************************************
	# Load historical data
	#****************************************************************** 
	library(SIT)
	load.packages('quantmod')	
	
	data <- new.env()
	data$USDCAD = read.xts('data/USDCAD.csv', format='%m/%d/%y %H:%M', index.class = c("POSIXlt", "POSIXt"))
		#plota(data$USDCAD, type='l')
	bt.prep(data, align='remove.na')
	
if (FALSE) {
	tickers = spl('USDCAD')
	data <- new.env()
	getSymbols.fxhistoricaldata(tickers, 'hour', data, 
		download=F, name.has.type = FALSE)
	bt.prep(data, align='remove.na', dates='1990::')
}	

	#*****************************************************************
	# Code Strategies
	#****************************************************************** 	
	prices = data$prices  


	models = list()

	dates = '2001::'
	#*****************************************************************
	# Code Strategies: Buy and Hold
	#****************************************************************** 	
	data$weight[] = NA
	  	data$weight[] = 1
	models$Buy.Hold = bt.run.share(data, dates=dates, silent=T, clean.signal=T)

	#*****************************************************************
	# Code Strategies: Long
	#****************************************************************** 	
	#Calculate the indicators we need for our strategy
	CCI20 = CCI(prices,20)
	RSI3 = RSI(prices,3)
	DEMA10 = DEMA(prices,n = 10, v = 1, wilder = FALSE)
	DEMA10c = prices - DEMA10
		DEMA10c = DEMA10c/.0001

	buy.signal = ifelse(RSI3 < 30 & CCI20 > -290 & CCI20 < -100 & DEMA10c > -40 & DEMA10c < -20,1,NA)

	#Set our long entry conditions found by our algorithms and optimized by us in the last post	
	data$weight[] = NA
	  	data$weight[] = buy.signal
	models$Long = bt.run.share(data, dates=dates, trade.summary = TRUE, silent=T, clean.signal=T)
	
	#*****************************************************************
	# Code Strategies: Short
	#****************************************************************** 	

	sell.signal<-ifelse(DEMA10c > 10 & DEMA10c < 40 & CCI20 > 185 & CCI20 < 325 & RSI3 > 50, -1 ,NA)

	data$weight[] = NA
	  	data$weight[] = sell.signal
	models$Short = bt.run.share(data, dates=dates, trade.summary = TRUE, silent=T, clean.signal=T)

long.short.strategy<-iif(RSI3 < 30 & CCI20 > -290 & CCI20 < -100 & DEMA10c > -40 & DEMA10c < -20,1,iif(DEMA10c > 10 & DEMA10c < 40 & CCI20 > 185 & CCI20 < 325 & RSI3 > 50, -1 ,NA))

	data$weight[] = NA
	  	data$weight[] = long.short.strategy
	models$Long.Short = bt.run.share(data, dates=dates, trade.summary = TRUE, silent=T, clean.signal=T)
					

	#*****************************************************************
	# Create Reprot
	#****************************************************************** 	
	#Isolate the dates from our validation set (The data not used to train the model or create the rules, our out-of-sample test)
	dates = '2014-02-26::2014-09-22'

	bt.stop.strategy.plot(data, models$Long.Short, dates = dates, layout=T, main = 'Long Short Strategy', plotX = F)

	strategy.performance.snapshoot(models, T)