Which Pairs of Stocks should we Trade? Selection of Pairs for Statistical Arbitrage and Pairs Trading in Karachi Stock Exchange

Laila Taskeen Qazi, Atta Ur Rahman ., Saleem Gul


Pairs Trading refers to a statistical arbitrage approach
devised to take advantage from short term fluctuations simultaneously
depicted by two stocks from long run equilibrium position. In this study
a technique has been designed for the selection of pairs for pairs
trading strategy. Engle-Granger 2-step Cointegration approach has been
applied for identifying the trading pairs. The data employed in this
study comprised of daily stock prices of Commercial Banks and Financial
Services Sector. Restricted pairs have been formed out of highly liquid
log share price series of 22 Commercial Banks and 19 Financial Services
companies listed on Karachi Stock Exchange. Sample time period extended
from November 2, 2009 to June 28, 2013 having total 911 observations for
each share prices series incorporated in the study. Out of 231 pairs of
commercial banks 25 were found cointegrated whereas 40 cointegrated
pairs were identified among 156 pairs formed in Financial Services
Sector. Furthermore a Cointegration relationship was estimated by
regressing one stock price series on another, whereas the order of
regression is accessed through Granger Causality Test. The mean
reverting residual of Cointegration regression is modeled through the
Vector Error Correction Model in order to assess the speed of adjustment
coefficient for the statistical arbitrage opportunity. The findings of
the study depict that the cointegrated stocks can be combined linearly
in a long/short portfolio having stationary dynamics. Although for the
given strategy profitability has not been assessed in this study yet the
VECM results for residual series show significant deviations around the
mean which identify the statistical arbitrage opportunity and ensure
profitability of the pairs trading strategy. JEL classifications: C32,
C53, G17 Keywords: Pairs Trading, Statistical Arbitrage, Engle-Granger
2-step Cointegration Approach, VECM.

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DOI: https://doi.org/10.30541/v54i3pp.215-244


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