PairTrading-package: Classical pair trading methods based on cointegration...
In PairTrading: classical pair trading based on cointegration in finance

Description Details Author(s) References Examples

This package gives classical trading strategy called "Pair trading". You can easily specify pairs for trading and do back-testing. Analysis are based on the idea of Cointegration that is a statistical feature of time series proposed by Engle and Granger.

Package:	PairTrading
Type:	Package
Version:	1.1
Date:	2012-03-24
License:	BSD
LazyLoad:	yes

Shinichi Takayanagi, Kohta Ishikawa Maintainer: Shinichi Takayanagi<shinichi.takayanagi@gmail.com>, Kohta Ishikawa<quantumcorgi@gmail.com>

Engle, Robert F. and C.W.J. Granger, 1987, Co-integration and error correction: Representation, estimation, and testing, Econometrica 55, 251-276. Granger, C.W.J., 1986, Developments in the study of cointegrated economic variables, Oxford Bulletin of Economics and Statistics 48, 213-228.

#load library
library(PairTrading)

#load sample stock price data
data(stock.price)

#select 2 stocks
price.pair <- stock.price[,1:2]["2008-12-31::"]

#Estimate parameters & plot spread
reg <- EstimateParameters(price.pair, method = lm)
str(reg)
plot(reg$spread)

#check stationarity
IsStationary(reg$spread, 0.1)

#estimate parameters for back test
params <- EstimateParametersHistorically(price.pair, period = 180)

#create & plot trading signals
signal <- Simple(params$spread, 0.05)
barplot(signal,col="blue",space = 0, border = "blue",xaxt="n",yaxt="n",xlab="",ylab="")
par(new=TRUE)
plot(params$spread)

#performance
return.pairtrading <- Return(price.pair, lag(signal), lag(params$hedge.ratio))
if(!all(is.na(return.pairtrading))){
  plot(100 * cumprod(1 + return.pairtrading))
}