ABSTRACT Mining projects are subject to multiple sources of market uncertainties such as metal price, exchange rates, and their volatilities. Assessing a mining project's exposure to market risk usually requires Monte Carlo simulations to capture a range of probable outcomes. The probability of a major loss is extracted from the probability density function of simulated prices at a given time into the future. This article proposes an approach to calibrate the stochastic process to be used in Monte Carlo simulations. The simulations are then used for measuring the cash flow at risk of a mining project. To assess the performance of the proposed approach, a case study is conducted on a mining project. The results show that the calibration approach is robust and apt at fitting various stochastic processes to historical observations.

中文翻译：

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使用蒙特卡洛模拟和根据历史数据校准的随机过程对采矿项目的风险现金流进行估值

摘要 采矿项目受到多种市场不确定性来源的影响，例如金属价格、汇率及其波动性。评估采矿项目的市场风险敞口通常需要蒙特卡罗模拟来捕捉一系列可能的结果。重大损失的概率是从未来给定时间的模拟价格的概率密度函数中提取的。本文提出了一种校准蒙特卡罗模拟中使用的随机过程的方法。然后使用模拟来衡量采矿项目面临风险的现金流量。为了评估所提议方法的性能，对一个采矿项目进行了案例研究。结果表明，校准方法是稳健的，并且适合将各种随机过程拟合到历史观察中。