Cointegrated assets : identification and trading

Abstract

Cointegration is a statistical property possessed by some multivariate time series that is defined by the concepts of stationarity and the order of integration of the series. When each component of a multivariate time series is non-stationary but certain linear combinations of these non-stationary components are stationary, the time series cointegrate. The idea of cointegration is often applied to stock pairs trading as it offers a more sophisticated description of co-movement between the cointegrated stock pairs. The objective of this project is to evaluate the effectiveness of applying cointegration to stock pairs trading. It involves writing a program using R programming language to compare the results from a simple pair trading strategy to that of a cointegrated stock pair trading strategy on 866 financial stocks listed on the Hong Kong Stock Exchange (HKSE). Data used to form stock pairs was taken from 1 September 2014 to 31 August 2015 while data used in the simulation to evaluate the strategies was taken from 1 September 2015 to 30 August 2016. Traders are not limited to their usage of logarithm or raw stock prices. Therefore, this report also seeks to evaluate the effects of using the different price series of the stocks in the various trading strategies that are simulated in the report.