A Functional Generalized Hill Process and Its Uniform Theory

Lo, Gane Samb; Dème, El Hadji

doi:10.5539/ijsp.v1n2p250

Cited by 1 publication

(1 citation statement)

References 19 publications

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“…Many studies extended the Hill estimator to more general case ξ ∈ R such that adapted Hill estimator, moment estimator and the QQ-estimator ( (Embrechts et al 1999), (Gencay & Selcuk 2004) and (Marimoutou et al2009)). Some other popular and remarkable estimators are the Moments estimators of (Dekkers et al 1989), the Generalized Hill estimator of (Diop & Lo, 2006, (Lo & Dème, 2012) and recently the (Ngom & LO, 2016).…”

Section: Journal Of Mathematics Researchmentioning

confidence: 99%

Return Levels Approach and Periods of Currency Crises

Hamidou¹,

Mung’atu²,

Orwa³

2018

JMR

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Dating and observing currency crisis periods lie at the heart of much international researchers. This is due to the lack of agreement in one research methodology. Until today, there does not exist a single theory or specific international policy regulation that can explain this phenomenon in global. To identify the periods of currency crisis, many methods have been brought out. Literature first employed a combination of sample mean and standard deviation. Some recent studies have attempted to use extreme value theory (EVT). Although these procedures have been more criticized in most of the literature. These drawbacks of existing approaches give rise to a new approach which is the main goal of this research. The main purpose of this study is to employ return levels technique to date currency crisis periods. The study will discuss only one method the block maxima approach. The stress losses i.e the generalized extreme value (GEV) distribution will be fitted to the annual block maxima to estimate the T-year return levels of extreme exchange market pressure index (EMPI). The parameters of the GEV distribution are estimated using the ML estimator method. Beside, a detailed procedure of the new approach is implemented. A comparison study between our identification approach and the existing conventional approach in the most literature is also conducted. We further illustrate the method by an empirical study on identifying periods of currency crisis of Kenya as case study. For practical implement the study focuses only on one single currency crisis model known as the alternative EMP index model for the intent of arbitrating the performance among various techniques. Results suggest that our new approach (RLDT) is performing better than the conventional method when the return period is considered big. Nonetheless, our technique appears to dominate the existing conventional approaches. This paper covers only a small area of this growing field of research. Hopefully, our investigations to contribute to these efforts by showing that return level dating technique derived from stress-losses model may have a place in the toolbox of economists looking for more accurate techniques in predicting currency crises.

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