An early warning system approach for the identification of currency crises with data mining techniques

2012 ◽  
Vol 23 (7-8) ◽  
pp. 2471-2479 ◽  
Author(s):  
Dilek Karahoca ◽  
Adem Karahoca ◽  
Özerk Yavuz
2013 ◽  
pp. 1349-1383
Author(s):  
Hakikur Rahman

This chapter is a conceptual contribution to this book on data mining applications upholding ethical issues related to two extremely important aspects of the Bangladeshi population: the early warning system and the disaster management system. The chapter tries to provide a few conceptual ideas to introduce ethical data mining application in these systems to support the agencies that are involved for an improved, efficient, and transparent support system in the country, especially across the Bay of Bengal. Resembling a triangular shape (deltaic), a major portion of the bay touches the southern portion of Bangladesh. Sediments from rivers have made the bay a shallow sea. Due to its shallowness and shape, monsoon rains and cyclone storms become destructive, causing great loss of life along the southern part of the country. Moreover, the three mighty rivers (Padma, Jamuna, and Meghna) form one of the largest river systems in the world. They have a large number of distributaries and tributaries, which cause a major portion of the country to be inundated by monsoon rain. In addition, being the lowest landing zone of the Himalayan water, Bangladesh becomes victim to floods almost every year. Loss of lives, destruction of properties, suffering of numerous people and hampering of economic development have become part and parcel of Bangladeshi communities. This chapter suggests that the newly emerged data mining techniques can be introduced to collect, synthesize, analyze, archive, disseminate, and even make future forecasts forming a reliable early warning system across the Bay of Bengal.


Author(s):  
Hakikur Rahman

This chapter is a conceptual contribution to this book on data mining applications upholding ethical issues related to two extremely important aspects of the Bangladeshi population: the early warning system and the disaster management system. The chapter tries to provide a few conceptual ideas to introduce ethical data mining application in these systems to support the agencies that are involved for an improved, efficient, and transparent support system in the country, especially across the Bay of Bengal. Resembling a triangular shape (deltaic), a major portion of the bay touches the southern portion of Bangladesh. Sediments from rivers have made the bay a shallow sea. Due to its shallowness and shape, monsoon rains and cyclone storms become destructive, causing great loss of life along the southern part of the country. Moreover, the three mighty rivers (Padma, Jamuna, and Meghna) form one of the largest river systems in the world. They have a large number of distributaries and tributaries, which cause a major portion of the country to be inundated by monsoon rain. In addition, being the lowest landing zone of the Himalayan water, Bangladesh becomes victim to floods almost every year. Loss of lives, destruction of properties, suffering of numerous people and hampering of economic development have become part and parcel of Bangladeshi communities. This chapter suggests that the newly emerged data mining techniques can be introduced to collect, synthesize, analyze, archive, disseminate, and even make future forecasts forming a reliable early warning system across the Bay of Bengal.


2015 ◽  
Vol 62 (4) ◽  
pp. 493-510 ◽  
Author(s):  
Vesna Bucevska

The purpose of this paper is to develop an econometric model of early warning system (EWS) for predicting currency crises in EU candidate countries. Using actual quarterly panel data for three EU candidate countries (Croatia, Macedonia and Turkey) in the period January 2005 - June 2010, we estimate a binomial logit model, which accurately predicts potential episodes of outbreak of currency crisis. In addition, we find that real GDP growth rate, participation in an IMF loan program, current account and fiscal balance and short-term external indebtedness are the most significant common predictors of currency crises across EU candidate countries. These results imply implementing policy measures aimed at raising the growth potential of the domestic economies of EU candidate countries, monitoring their short-term external indebtedness, improving their external competitiveness, cutting public spending and increasing the confidence of residents and non-residents in their domestic banking sectors.


EconoQuantum ◽  
2018 ◽  
Vol 14 (2) ◽  
pp. 47-68
Author(s):  
Tjeerd M. Boonman ◽  
◽  
Jan P. A. M. Jacobs ◽  
Gerard H. Kuper ◽  
◽  
...  

Author(s):  
Ali Serhan Koyuncugil

This chapter introduces an early warning system for SMEs (SEWS) as a financial risk detector which is based on data mining. In this study, the objective is to compose a system in which qualitative and quantitative data about the requirements of enterprises are taken into consideration, during the development of an early warning system. Furthermore, during the formation of system; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. Using the system, SME managers could easily reach financial management, risk management knowledge without any prior knowledge and expertise. In other words, experts share their knowledge with the help of data mining based and automated EWS.


2014 ◽  
Vol 237 (3) ◽  
pp. 1095-1104 ◽  
Author(s):  
Cuneyt Sevim ◽  
Asil Oztekin ◽  
Ozkan Bali ◽  
Serkan Gumus ◽  
Erkam Guresen

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