A Comparison of Currency Crisis Dating Methods: Turkey 1990-2014

Ari, Ali; Cergibozan, Raif

doi:10.14254/1800-5845.2016/12-3/2

Cited by 6 publications

(4 citation statements)

References 58 publications

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“…The CCIs which will be used in the study are proposed by Eichengreen [15], Kaminsky [18], Corsetti et al [10], Krkoska [21], Von Hagen and Ho [29], Bussierre [4], Yiu et al [31], Alvarez-Plata and Schrooten [1], Bunda and Co-Zorri [6], and Johansen [17]. The de…nitions of CCIs given by the researchers introduced above are given in Equation 17-26 and cited from Ari and Cergibozan [2].…”

Section: Currency Crisis Indices (Cci)mentioning

confidence: 99%

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Meta fuzzy index functions

Tak

2020

Communications Faculty of Science University of Ankara Series A1Mathematics and Statistics

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Meta-analysis was introduced to aggregate the …ndings of di¤erent primary studies in statistical aspects. However, in the proposed study, the term "meta" is used to aggregate di¤erent models for a speci…c topic with the help of fuzzy c-means clustering method. One of the motivations of the proposed method is based on the concept of indices. In the literature, there are numerous proposed indices under di¤erent conditions for a speci…c purpose. Our assumption is that each index has some information for a given dataset. Therefore, meta fuzzy index functions, which include each index in each function with a certain degree of membership value, are introduced in the proposed method. Currency crisis and process capability indices are chosen as applications in order to show that the proposed method can be useful tool in terms of indices.

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Section: Currency Crisis Indices (Cci)mentioning

confidence: 99%

“…where RER is the reel exchange rate, RIR is the reel exchange rate, 2 RER , 2 RES , and 2 RIR the standard deviations of the reel exchange rate, reserves and the reel interest rate respectively.…”

Section: Currency Crisis Indices (Cci)mentioning

confidence: 99%

Meta fuzzy index functions

Tak

2020

Communications Faculty of Science University of Ankara Series A1Mathematics and Statistics

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“…We have preferred to use the currency crisis indices that are cited in Ari and Cergibozan (2016a), because they brought upon an extensive research for all the indices used in the literature to date currency crises. Because a speculative attack on national currency results either in severe depreciation or devaluation leading to the currency crisis, the central bank or the monetary authority take the position to maintain the value of the national currency either by expending a large amount of foreign reserves or by swiftly increasing interest rates (Claessens & Kose, 2013).…”

Section: Currency Crisis Indices Used In the Analysismentioning

confidence: 99%

“…There are several papers in the literature for dating currency crises (Ari & Cergibozan, 2016a; Boonman, 2019; Jacobs, 2004) and designing EWSs (Ari & Cergibozan, 2016b; Ari & Cergibozan, 2018; Boonman, Jacobs, Kuper, & Romero, 2019; Çeşmeci & Önder, 2008; Kaminsky, Lizondo, & Reinhart, 1998). The main difference of the proposed MPFIFs from the above‐cited papers is that MPFIFs aggregate the information of all currency‐indexing methods in functions rather than relying on only one currency‐indexing method.…”

Section: Introductionmentioning

confidence: 99%

Dating currency crises and designing early warning systems: Meta‐possibilistic fuzzy index functions

Tak

Gök

2020

Int. J Fin Econ

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In order to analyse the currency crises in Turkey over the period of January 1990 and October 2019, we first dated currency crises with meta‐possibilistic fuzzy index functions. Then, we determined the significant predictors or leading indicators of currency crisis with logistic regression. Finally, we tried to measure and compare the in‐sample and out‐of‐sample performances of our method with an index generated by principal component analysis (PCA). We found that the models using the currency crisis index generated by our method have higher in‐sample and out‐of‐sample performances than the models using the currency crisis index generated by PCA. We concluded that the change in real exchange rate, bank loans over bank deposits, bank reserves over bank assets, growth in foreign reserves, growth in central bank foreign assets, M2 over foreign assets, change in exports, change in imports, industrial production index, M1 growth, M2 growth, foreign reserves over M1, central bank foreign assets over M1 and public sector credit growth are the leading indicators of currency crisis among 20 explanatory variables. As policy implications, we recommend that government and the monetary authority should strictly monitor the ratio of bank loans over bank deposits, public sector credit growth, the volatility of foreign trade, ratio of foreign reserves and central bank foreign assets over money supply among significant explanatory variables to avoid currency crisis as policy implications.

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