[HTML][HTML] Forecasting: theory and practice

F Petropoulos, D Apiletti, V Assimakopoulos… - International Journal of …, 2022 - Elsevier
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Predictions of steel price indices through machine learning for the regional northeast Chinese market

B **, X Xu - Neural Computing and Applications, 2024 - Springer
Projections of commodity prices have long been a significant source of dependence for
investors and the government. This study investigates the challenging topic of forecasting …

Thermal coal futures trading volume predictions through the neural network

B **, X Xu, Y Zhang - Journal of Modelling in Management, 2024 - emerald.com
Purpose Predicting commodity futures trading volumes represents an important matter to
policymakers and a wide spectrum of market participants. The purpose of this study is to …

Agricultural Product Price Forecasting Methods: A Review

F Sun, X Meng, Y Zhang, Y Wang, H Jiang, P Liu - Agriculture, 2023 - mdpi.com
Agricultural price prediction is a hot research topic in the field of agriculture, and accurate
prediction of agricultural prices is crucial to realize the sustainable and healthy development …

Forecasting the price of Bitcoin using deep learning

M Liu, G Li, J Li, X Zhu, Y Yao - Finance research letters, 2021 - Elsevier
After constructing a feature system with 40 determinants that affect the price of Bitcoin
considering aspects of the cryptocurrency market, public attention, and the macroeconomic …

Risk spillovers between FinTech and traditional financial institutions: Evidence from the US

J Li, J Li, X Zhu, Y Yao, B Casu - International Review of Financial Analysis, 2020 - Elsevier
In this paper, we propose a novel approach to examine the risk spillovers between FinTech
firms and traditional financial institutions, during a time of fast technological advances …

Machine learning price index forecasts of flat steel products

B **, X Xu - Mineral Economics, 2024 - Springer
Investors and authorities have always placed a high emphasis on commodity price
forecasting. In this study, the issue of daily price index forecasting for flat steel products on …

Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat

X Xu, Y Zhang - Intelligent Systems in Accounting, Finance and …, 2022 - Wiley Online Library
Agricultural commodity price forecasting represents a key concern for market participants.
We explore the usefulness of neural network modeling for forecasting problems in datasets …

Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? Mixed-data sampling approach

J Wu, M Li, E Zhao, S Sun, S Wang - Tourism Management, 2023 - Elsevier
Abstract The coronavirus disease (COVID-19) pandemic has already caused enormous
damage to the global economy and various industries worldwide, especially the tourism …

Regional steel price index forecasts with neural networks: evidence from east, south, north, central south, northeast, southwest, and northwest China

X Xu, Y Zhang - The Journal of Supercomputing, 2023 - Springer
For policy makers and a diverse spectrum of market participants, understandings of
commodity price forecasts are considered as an important matter. In this work, we focus on …