Developing an early warning system to predict currency crises

Keywords: Early warning system Currency crisis Perfect signal Artificial neural networks (ANN) Decision tree Logistic regression a b s t r a c t The purpose of this paper is to develop an early warning system to predict currency crises. In this study, a data set covering the period of January 1992–December 2011 of Turkish economy is used, and an early warning system is developed with artificial neural networks (ANN), decision trees, and logistic regression models. Financial Pressure Index (FPI) is an aggregated value, composed of the percentage changes in dollar exchange rate, gross foreign exchange reserves of the Central Bank, and overnight interest rate. In this study, FPI is the dependent variable, and thirty-two macroeconomic indicators are the independent variables. Three models, which are tested in Turkish crisis cases, have given clear signals that predicted the 1994 and 2001 crises 12 months earlier. Considering all three prediction model results, Turkey's economy is not expected to have a currency crisis (ceteris paribus) until the end of 2012. This study presents uniqueness in that decision support model developed in this study uses basic macroeconomic indicators to predict crises up to a year before they actually happened with an accuracy rate of approximately 95%. It also ranks the leading factors of currency crisis with regard to their importance in predicting the crisis. A financial crisis is a state which causes economic, social, and political disasters that lead to a shift from equilibrium. This equilibrium creates uncertainty and chaos while causing redistribution of capital. Individuals who can foresee the crisis can use it to their advantage by reallocating capital and can transform the drawbacks of the impending crisis into opportunities. On the other hand, the ones who cannot foresee the crisis would suffer from unemployment and poverty. Therefore, the foresight to predict a crisis has attracted the attention of many researchers in the field of economics. However, due to the complexity of the context and number of factors that cause a crisis, predicting a crisis has been a very challenging problem. More interestingly, these factors have constantly changed over time. Considering all these, it would be a wise approach to take precautions against the potential crisis and prepare accordingly by foreseeing its effects via the past crisis and past economic indicators. There are various methods in literature that have been used to predict the crisis, most of which are statistical and econometric models. …