Dependency between Stock Movements Using the Clayton Copula Method (Ghana Stock Exchange)

This study examines the dependence structure of Ghana's financial market using copula methods and the correlation method. Modeling multivariate probability distributions can be difficult if the marginal probability density functions of the random variables of the components differ. Most microeconomic modeling situations have marginal distributions that cannot be easily combined into joint distributions. Since there are few or no joint parametric distributions based on the margins of different families, the copula method provides a simple and general approach to building joint distributions in these situations. Financial markets are concerned with whether prices of different assets exhibit dependence. For these reasons, copulas have become very important as a technique for modeling these non-constant correlations. This has been a great blessing for financial engineering because it is possible to flexibly model these nonlinear relationships. Copula is a suitable tool for modeling dependence between random variables with any marginal distributions. This is why the copula method will be used to study how the various selected stocks move together. How can the Copula method be used on a stock exchange market? This report introduces the idea of a copula, consisting of correlation and dependence, completes the basic mathematics behind its composition and the applications in financial engineering, in particular the structure of dependency in the Ghanaian financial market (promotions). This report examines the linear and non-linear dependency (structure) between the stocks selected on the Ghanaian stock market using the Joe Clayton Copula.