Summary, Conclusion and Recommendations
There is no doubt that this paper has been able to adequately address the objectives it set out to achieve. It started by introducing the subject of study and identifying the problem it set out to tackle. While reviewing extant literature frameworks on the subject of multivariate dependent variables, the paper introduced the various methods and formula adaptations that can be employed to unify financial performance data for the purpose of relational research analysis. From the literature review and the earlier discussions of the results of research data analysis, it is evident that financial performance research utilizing multivariate dependent variable has very little space to maneuver with the existing econometric methods of multivariate data analysis. Financial and accounting information are made up of already processed and validated economic data and values which require careful and exact practical treatment which the abstract assumptions of most econometric measurements and analysis may not adequately handle, resulting in the need to adopt a more practical and less abstraction assumptions and methods to manipulate them. The use of geometric means to unify multivariate dependent variables into a single variable is considered the best way to effectively execute a financial performance relational research because, according to Transaction Processing Performance Council (2011), the geometric mean presents a single figure of merit which respects the intrinsic differences across all dimensions of the data distribution (UNDP, 2011).
In view of the aforementioned findings, this paper recommends that more attention be paid to the peculiar nature of financial performance research and the important role that such researches ought to play in the economy of every nation when deciding on the method and tool of analysis to adopt. It will not be out of place if we have a statistical analysis type that takes the peculiar interest of accounting and finance into consideration. If chemistry can develop a special branch of statistics called chemometrics , it is possible to have eitherfinometrics or accometrics .