An Early Warning System for Turkey: The Forecasting Of Economic Crisis by Using the Artificial Neural Networks
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Keywords

Early warning of crises, Turkish economy, Artificial neural network, Currency crises, Learning paradigms, Non-parametric tests, Multilayer perceptron.

How to Cite

Sekmen, F. ., & Kurkcu, M. . (2014). An Early Warning System for Turkey: The Forecasting Of Economic Crisis by Using the Artificial Neural Networks. Asian Economic and Financial Review, 4(4), 529–543. Retrieved from https://archive.aessweb.com/index.php/5002/article/view/1176

Abstract

An economic crisis is typically a rare kind of an event but it impedes monetary stability, fiscal stability, financial stability, price stability, and sustainable economic development when it appears. Economic crises have huge adverse effects on economic and social system. This study uses an artificial neural network learning paradigm to predict economic crisis events for early warning aims. This paradigm is being preferred due to its flexible modeling capacity and can be applied easily to any time series since it does not require prior conditions such as stationary or normal distribution. The present article analyzes economic crises occurred in Turkey for the period 1990-2011. The main question addressed in this paper is whether currency crises can be estimated by using artificial neural networks.

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