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A new approach for Baltic Dry Index forecasting based on empirical mode decomposition and neural networks

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References

2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm705 cited
2006Forecasting spot and forward prices in the international freight market164 cited
2003Price Discovery, Causality and Forecasting in the Freight Futures Market101 cited
2008An analysis of freight rate volatility in dry bulk shipping markets80 cited
2012Improving prediction of exchange rates using Differential EMD75 cited

Cited by

2022The influence of COVID-19 epidemic on BDI volatility: An evidence from GARCH-MIDAS model70 cited
2019Artificial neural networks in freight rate forecasting50 cited
2018Comparison of Econometric Models and Artificial Neural Networks Algorithms for the Prediction of Baltic Dry Index48 cited
2019A novel hybrid approach to Baltic Dry Index forecasting based on a combined dynamic fluctuation network and artificial intelligence method43 cited
2021Time series forecasting methods for the Baltic dry index41 cited
2022State-space TBATS model for container freight rate forecasting with improved accuracy37 cited
2020A hybrid model for financial time‐series forecasting based on mixed methodologies36 cited

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