@ARTICLE{Huang_Shuwei_Prediction_2022,
 author={Huang, Shuwei and Ma, Zhaoyang and Jin, Feng and Zhang, Yuansheng},
 volume={vol. 38},
 number={No 2},
 journal={Gospodarka Surowcami Mineralnymi - Mineral Resources Management},
 pages={61-75},
 howpublished={online},
 year={2022},
 publisher={Komitet Zrównoważonej Gospodarki Surowcami Mineralnymi PAN},
 publisher={Instytut Gospodarki Surowcami Mineralnymi i Energią PAN},
 abstract={The mean-reversion model is introduced into the study of mineral product price prediction. The gold price data from January 2018 to December 2021 are selected, and a mean-reverting stochastic process simulation of the gold price was carried out using Monte Carlo simulation (MCS) method. By comparing the statistical results and trend curves of the mean-reversion (MR) model, geometric Brownian motion (GBM) model, time series model and actual price, it is proved that the mean-reversion process is valid in describing the price fluctuation of mineral product. At the same time, by comparing with the traditional prediction methods, the mean-reversion model can quantitatively assess the uncertainty of the predicted price through a set of equal probability stochastic simulation results, so as to provide data support and decision-making basis for the risk analysis of future economy.},
 type={Article},
 title={Prediction of mineral product price based on mean reversion model},
 URL={http://journals.pan.pl/Content/123714/PDF-MASTER/Huang%20i%20inni.pdf},
 doi={10.24425/gsm.2022.141665},
 keywords={mineral-product price, mean reversion model, Monte Carlo simulation, uncertainty analysis},
}