Forecasting Turkey’s Credit Ratings with Multivariate Grey Model and Grey Relational Analysis

Abstract

The concept of credit rating rooted back to mid-nineteenth century has become one of the most important elements in the world economy together with the globalization period gradually accelerating in the last two decades and increasing the interaction and sensitivity in the international markets. With the globalization and deepening in the financial markets; the effect, reliability and stability of knowledge of the actors who are in charge for directing the global capital flows have quite a big importance in terms of the decisions to be made in the future. In this process, credit rating agencies eliminating the information asymmetry between the countries and institutions who want to create financial resource by borrowing from the savings owners and foreign institutions. Credit ratings determined by the mentioned organizations are accepted as an indicator of the countries to meet the financial obligations in other words their creditworthiness. For Turkey's economy having a structure with a high level of external financing needs in terms of accelerating the growth and development process, it is inevitable to have an international creditworthiness increasing long-term investment tendency meeting foreign capitals' trust search. In this study, firstly the determinants of the credit ratings given by credit rating agencies are determined and then forecasting Turkey's future credit ratings by combining them with multivariate grey model and grey relational analysis are performed.

A Nonhomogeneous Multivariable Grey Prediction NMGM Modeling Mechanism and Its Application

“…In recent years, great attention has been devoted to optimizing and expanding applications of MGM(1, ) model [33][34][35][36][37][38]. Xiong et al [33] provided background values to improve the original MGM model, which can be used to eliminate the random fluctuations and errors of the observational data.…”

“…Guo et al [37] constructed SMGM through coupling self-memory principle of dynamic system to MGM; the example showed that SMGM had superior predictive performance over other traditional grey prediction models. Karaaslan andzden [38] analyzed Turkey's ratings credit by multivariable grey prediction model and expanded the application scope of multivariable grey prediction model. Those studies illustrated that multivariable grey prediction model is widely used in many fields.…”