Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market
Throughout history, governments and investors have relied on predictions of prices for a broad spectrum of commodities. Using time-series data covering 08/23/2013–04/15/2021, this study investigates the challenging problem of predicting scrap steel prices, which are issued daily for the northeast Ch...
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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2024-12-01
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| Series: | International Journal of Empirical Economics |
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| Online Access: | https://www.worldscientific.com/doi/10.1142/S2810943024500112 |
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| _version_ | 1841543707967356928 |
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| author | Bingzi Jin Xiaojie Xu |
| author_facet | Bingzi Jin Xiaojie Xu |
| author_sort | Bingzi Jin |
| collection | DOAJ |
| description | Throughout history, governments and investors have relied on predictions of prices for a broad spectrum of commodities. Using time-series data covering 08/23/2013–04/15/2021, this study investigates the challenging problem of predicting scrap steel prices, which are issued daily for the northeast China market. Previous research has not sufficiently taken into account estimates for this significant commodity price measurement. In this instance, Gaussian process regression methods are created using Bayesian optimisation approaches and cross-validation processes, and the resulting price forecasts are constructed. This empirical prediction methodology provides reasonably accurate price estimates for the out-of-sample period from 09/17/2019 to 04/15/2021, with a root mean square error of 9.6951, mean absolute error of 5.4218, and correlation coefficient of 99.9122%. Governments and investors can arrive at informed decisions regarding regional scrap steel markets by using pricing research models. |
| format | Article |
| id | doaj-art-995f28c0587e4d54add532bca7971b27 |
| institution | Kabale University |
| issn | 2810-9430 2810-9449 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | World Scientific Publishing |
| record_format | Article |
| series | International Journal of Empirical Economics |
| spelling | doaj-art-995f28c0587e4d54add532bca7971b272025-01-13T08:01:41ZengWorld Scientific PublishingInternational Journal of Empirical Economics2810-94302810-94492024-12-01030410.1142/S2810943024500112Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese MarketBingzi Jin0Xiaojie Xu1Advanced Micro Devices (China) Co., Ltd., Shanghai, P. R. ChinaNorth Carolina State University, Raleigh, NC 27695, USAThroughout history, governments and investors have relied on predictions of prices for a broad spectrum of commodities. Using time-series data covering 08/23/2013–04/15/2021, this study investigates the challenging problem of predicting scrap steel prices, which are issued daily for the northeast China market. Previous research has not sufficiently taken into account estimates for this significant commodity price measurement. In this instance, Gaussian process regression methods are created using Bayesian optimisation approaches and cross-validation processes, and the resulting price forecasts are constructed. This empirical prediction methodology provides reasonably accurate price estimates for the out-of-sample period from 09/17/2019 to 04/15/2021, with a root mean square error of 9.6951, mean absolute error of 5.4218, and correlation coefficient of 99.9122%. Governments and investors can arrive at informed decisions regarding regional scrap steel markets by using pricing research models.https://www.worldscientific.com/doi/10.1142/S2810943024500112Regional scrap steel pricetime-series forecastGaussian process regressionBayesian optimizationcross validation |
| spellingShingle | Bingzi Jin Xiaojie Xu Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market International Journal of Empirical Economics Regional scrap steel price time-series forecast Gaussian process regression Bayesian optimization cross validation |
| title | Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market |
| title_full | Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market |
| title_fullStr | Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market |
| title_full_unstemmed | Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market |
| title_short | Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market |
| title_sort | machine learning based scrap steel price forecasting for the northeast chinese market |
| topic | Regional scrap steel price time-series forecast Gaussian process regression Bayesian optimization cross validation |
| url | https://www.worldscientific.com/doi/10.1142/S2810943024500112 |
| work_keys_str_mv | AT bingzijin machinelearningbasedscrapsteelpriceforecastingforthenortheastchinesemarket AT xiaojiexu machinelearningbasedscrapsteelpriceforecastingforthenortheastchinesemarket |