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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.
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Authors and Affiliations

Shuwei Huang
1 2 3
ORCID: ORCID
Zhaoyang Ma
1
Feng Jin
1
ORCID: ORCID
Yuansheng Zhang
1

  1. BGRIMM Technology Group, China
  2. Beijing Key Laboratory of Nonferrous Intelligent Mining Technology, China
  3. BGRIMM Intelligent Technology Co. Ltd, China

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