Methods and Indexes to Monitor the Economic Crisis (A Review)

The ability in forecasting the future state of financial condition and predicting the incoming economic crisis has become very crucial in preparing the countries towards economic downturn. Therefore, a necessary preventive action can be taken much earlier in order to avoid more severe outcome. The purpose of this paper is to evaluate and analyse some of the classifiers that have been used all over the world to predict the possibility of such crisis. Those classifiers that will be covered are Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithm (GA), Data Envelopment Analysis (DEA) and Support Vector Machine (SVM). The study analyses multiple published papers and researches that has been conducted within 1996-2012 period. The first criterion will be in accordance to the individual description, method and analysis of each classifier, followed by the gap analysis of the multiple in-scope classifiers studies that have been observed. Referring to the review that has been done, the findings show that the Fuzzy Logic (FL), Neural Network (NN), Genetic Algorithms (GA), Support Vector Machines (SVM), and Data Envelopment Analysis (DEA) can be used in predicting the financial crisis. It can also be evidenced that there is still a lack of study that combines those classifiers in producing a better, more efficient and accurate method.

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