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Journals / JOEEP: Journal of Emerging Economies and Policy / 2023 / Cilt: 8 Sayı: 2

Forecasting the China Container Freight Index with Ensemble Models

Ensemble Modelleriyle Çin Konteyner Navlun Endeksi'nin Tahmin Edilmesi

Tolga Tuzcuoğlu(TÜRK-ALMAN ÜNİVERSİTESİ)0000-0002-5269-9701
Hüseyin Gencer(PİRİ REİS ÜNİVERSİTESİ)0000-0002-4945-4420
Pages
416–423
Publication Date
2023-12-30
DOI
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AI Summary & Key Takeaways

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

The study results show that the models provide promising results in forecasting CCFI and can be used as an essential decision support system.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Stakeholders in the sector need to be able to predict how freight rates will change in container transportation.
📊
Key Findings & Data:For the first time in the literature, this study presents aggregate time series models for the prediction of CCFI (China Container Freight Index), one of the most critical indicators showing the change of freight rates in container shipping.
💡
Conclusion & Impact:The study results show that the models provide promising results in forecasting CCFI and can be used as an essential decision support system.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Navlun Endeksi Tahmini · Toplu Modeller · Finansal Tahminleme

Abstract

Stakeholders in the sector need to be able to predict how freight rates will change in container transportation. For the first time in the literature, this study presents aggregate time series models for the prediction of CCFI (China Container Freight Index), one of the most critical indicators showing the change of freight rates in container shipping. The study results show that the models provide promising results in forecasting CCFI and can be used as an essential decision support system.

Özet

Konteyner taşımacılığında navlun oranlarının nasıl değişeceğini sektördeki paydaşların öngörebilmesi oldukça önemlidir. Bu çalışma, literatürde ilk defa olmak üzere, konteyner taşımacılığında navlun oranlarının değişimini gösteren en önemli göstergelerden biri olan CCFI (Çin Konteyner Navlun Endeksi) 'nin tahmini için toplu zaman serisi modelleri sunmaktadır. Çalışmanın sonuçları, modellerin CCFI’nin tahmininde oldukça iyi sonuçlar verdiğini ve önemli bir karar destek sistemi olarak kullanılabileceğini göstermektedir.

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Cite This Article

Tuzcuoğlu, T., Gencer, H. (2023). Forecasting the China Container Freight Index with Ensemble Models. JOEEP: Journal of Emerging Economies and Policy, Cilt: 8 Sayı: 2, 416–423. https://ajindex.com/articles/1504308

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