Baltic dry index forecast using financial market data: Machine learning methods and SHAP explanations.
The Baltic Dry Index (BDI) is a critical benchmark for assessing freight rates and chartering activity in the global shipping market. This study forecasts the BDI using diverse financial data, including commodities, currencies, stock markets, and volatility indices. Unlike previous research, our app...
Saved in:
Main Authors: | Hyeon-Seok Kim, Do-Hyeon Kim, Sun-Yong Choi |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0325106 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Baltic dry index forecast using financial market data: Machine learning methods and SHAP explanations
by: Hyeon-Seok Kim, et al.
Published: (2025-01-01) -
Modeling Stylized Facts in FX Markets with FINGAN-BiLSTM: A Deep Learning Approach to Financial Time Series
by: Dong-Jun Kim, et al.
Published: (2025-06-01) -
SHapley Additive exPlanations (SHAP) for Landslide Susceptibility Models: Shedding Light on Explainable AI
by: H. Al-Najjar, et al.
Published: (2025-07-01) -
Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam
by: Mohammad Teddy Syamkalla, et al.
Published: (2024-08-01) -
The siege machines during the Baltic crusades
by: Sven Ekdahl
Published: (2007-01-01)