HOT ROLLED COIL PRICE FORECASTING AND MARKET INTELLIGENCE
ARUN KRISHNAN
, Awadesh Jindal , Harriet Linda
AI, HRC, machine learning
Hot Rolled Coil (HRC) is a foundational commodity in multiple industrial sectors, including automotive, construction, and manufacturing. Due to its high demand and sensitivity to global market forces, forecasting its price accurately is a major economic challenge. This paper proposes a machine learning-based framework that utilizes regression techniques and deep learning to model the price fluctuations of HRC. Incorporating a wide range of factors—from raw material costs to geopolitical impacts—the study demonstrates the effectiveness of AI models, particularly polynomial regression and XGBoost, in generating real-time price forecasts. The system enables industries to adopt a data-driven approach to procurement, financial risk management, and strategic inventory planning.
"HOT ROLLED COIL PRICE FORECASTING AND MARKET INTELLIGENCE", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.a413-a416, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504064.pdf
Volume 12
Issue 4,
April-2025
Pages : a413-a416
Paper Reg. ID: TIJER_157393
Published Paper Id: TIJER2504064
Downloads: 000305
Research Area: Science and Technology
Country: Kattankulathur, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
