A new approach to modeling early warning systems for currency crises: Can a machine-learning fuzzy expert system predict the currency crises effectively?

Abstract

This paper presents a hybrid causal model for predicting the occurrence of currency crises by using the neuro fuzzy modeling approach. The model integrates the learning ability of the neural network with the inference mechanism of fuzzy logic. The empirical results show that the proposed neuro fuzzy model leads to a better prediction of crisis. Significantly, the model can also construct a reliable causal relationship among the variables through the obtained knowledge base. Compared to neural network and the traditionally used techniques such as logic, the proposed model can thus lead to a somewhat more prescriptive modeling approach based on determinate causal mechanisms towards finding ways to prevent currency crises. (C) 2008 Elsevier Ltd. All rights reserved

Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?

“…The results of the KLR method are shown in Table 3. Table 3, it appears that the inflation has a noise-to-signal ratio less than 0.5 4 (Lin et al 2008) in all regimes.…”

Systemic banking crisis early warning systems using dynamic Bayesian networks

“…These include expert systems based on self-organising maps ( Jagric, Bojnec, & Jagric, 2015 ), neural network models ( Celik & Karatepe, 2007;Iturriaga & Sanz, 2015;Nag & Mitra, 1999;Sevim, Oztekin, Bali, Gumus, & Guresen, 2014 ), regression trees ( Manasse & Roubini, 2009 ), binary classification trees ( Duttagupta & Cashin, 2008 ), hybrid models ( Lin, Khan, Chang, & Wang, 2008;Lin, 2009 ), grey rational analysis ( Lin & Wu, 2011 ), support vector machines ( Ahn, Oh, Kim, & Kim, 2011;Feki, Ishak, & Feki, 2012 ), random forests ( Alessi & Detken, 2014 ), and the multiple-indicator-multiple-cause method ( Rose & Spiegel, 2012 ). Comparisons between such methods have been conducted by Boyacioglu, Kara, and Baykan (2009) .…”

Coupled market behavior based financial crisis detection

“…Suppose there are C coupled HMMs, N is the number of hidden states, the elements of a CHMM are as follows [22]:…”

“…However, different indicators often produce different prediction outcomes for financial crisis. To obtain a more stable prediction outcome, multiple indicators are used and combined for the signaling [22],…”