A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data

Huosong Xia; Xiaoyu Hou; Justin Zuopeng Zhang; Mohammad Zoynul Abedin

doi:10.1002/for.3185

A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data

Huosong Xia, Xiaoyu Hou, Justin Zuopeng Zhang, Mohammad Zoynul Abedin

Coggin College of Business

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	112-135
Number of pages	24
Journal	Journal of Forecasting
Volume	44
Issue number	1
DOIs	https://doi.org/10.1002/for.3185
State	Published - Jan 2025
Externally published	Yes

ASJC Scopus Subject Areas

Modeling and Simulation
Economics and Econometrics
Computer Science Applications
Strategy and Management
Statistics, Probability and Uncertainty
Management Science and Operations Research

Keywords

XAI
big data mining
forecasting
probabilistic modelling

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10.1002/for.3185

Cite this

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title = "A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data",

keywords = "XAI, big data mining, forecasting, probabilistic modelling",

author = "Huosong Xia and Xiaoyu Hou and Zhang, {Justin Zuopeng} and Abedin, {Mohammad Zoynul}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s). Journal of Forecasting published by John Wiley & Sons Ltd.",

year = "2025",

month = jan,

doi = "10.1002/for.3185",

language = "English",

volume = "44",

pages = "112--135",

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AU - Xia, Huosong

AU - Hou, Xiaoyu

AU - Zhang, Justin Zuopeng

AU - Abedin, Mohammad Zoynul

PY - 2025/1

Y1 - 2025/1

KW - XAI

KW - big data mining

KW - forecasting

KW - probabilistic modelling

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U2 - 10.1002/for.3185

DO - 10.1002/for.3185

M3 - Article

AN - SCOPUS:85201291838

SN - 0277-6693

VL - 44

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JO - Journal of Forecasting

JF - Journal of Forecasting

IS - 1

ER -

A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data

ASJC Scopus Subject Areas

Keywords

Access to Document

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