EXPLAINING INTERNATIONAL INVESTMENT PATTERNS: A NEURAL NETWORK APPROACH

Abstract

This paper aims to explain foreign portfolio investment impact on the dynamics of regional (Central and East Europe) capitalization structure in terms of sectorial investment distribution. Complexity of the problem domain has predetermined the use of interdisciplinary research framework. The ultimate result of this data analysis is a universally applicable model aimed at the nontraditional estimation of sectorial indices weights according to the relative capitalization of the economic sectors. The novelty of the proposed model lays in the application of neural network methods, which were thoroughly designed for the sectorial indices’ weights estimation. There is no experiment in the field which would focus on such an experimental setting. The overall NN research framework has developed into the software capable considerably to automate the whole research process. The results of the new approach decidedly outperformed the multivariate linear regression forecasting performance. We argue that the proposed NN approach will extend the assessment and forecasting power of the nonlinearities present in a nowadays volatile investment environment.