Journals / Central Bank Review / 2020 / Cilt: 20 - Sayı: 3

An optimal early warning system for currency crises under modeluncertainty

Pages
99–107
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Taking Egypt as a case study and focusing only on currencycrises, ourfindings show that combined forecast (EW- and DMA-based EWS), to account for uncertainty,perform better than other competing models in both in-sample and out-of-sample forecasts.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper assesses several early warning (EWS) models offinancial crises to propose a model that canpredict the incidence of a currency crisis in developing countries.
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Key Findings & Data:For this purpose, we employ the equalweighting (EW) and dynamic model averaging (DMA) approaches to combine forecast from individualmodels allowing for time-varying weights.
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Conclusion & Impact:Taking Egypt as a case study and focusing only on currencycrises, ourfindings show that combined forecast (EW- and DMA-based EWS), to account for uncertainty,perform better than other competing models in both in-sample and out-of-sample forecasts.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

This paper assesses several early warning (EWS) models offinancial crises to propose a model that canpredict the incidence of a currency crisis in developing countries. For this purpose, we employ the equalweighting (EW) and dynamic model averaging (DMA) approaches to combine forecast from individualmodels allowing for time-varying weights. Taking Egypt as a case study and focusing only on currencycrises, ourfindings show that combined forecast (EW- and DMA-based EWS), to account for uncertainty,perform better than other competing models in both in-sample and out-of-sample forecasts.

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Cite This Article

ABDELSALAM, M. A. M., ABDEL-LATİF, H. (2020). An optimal early warning system for currency crises under modeluncertainty. Central Bank Review, Cilt: 20 - Sayı: 3, 99–107. https://ajindex.com/articles/212364

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