Abstract
A new approach is proposed to identify trading opportunities in the equity market by using the
information contained in the bivariate dependence structure of two equities. The relationships
between the equity pairs are modelled with bivariate copulas and the fitted copula structures are
utilised to identify the trading opportunities. Two trading strategies are considered that take
advantage of the relative mispricing between a pair of correlated stocks and involve taking a
position on the stocks when they diverge from their historical relationship. The position is then
reversed when the two stocks revert to their historical relationship. Only stock-pairs with relatively
high correlations are considered. The dependence structures of the chosen stock-pairs very often
exhibited both upper- and lower-tail dependence, which implies that copulas with the correct
characteristics should be more effective than the more traditional approaches typically applied. To
identify trading opportunities, the conditional copula functions are used to derive confidence
intervals for the two stocks. It is shown that the number of trading opportunities is highly dependent
on the confidence level and it is argued that the chosen confidence level should take the strength of
the dependence between the two stocks into account. The back-test results of the pairs-trading
strategy are disappointing in that even though the strategy leads to profits in most cases, the profits
are largely consumed by the trading costs. The second trading strategy entails using single stock
futures and it is shown to have more potential as a statistical arbitrage approach to construct a
portfolio.