According to the 2015 edition of the Australian Valmin Standards, there is a distinction between two concepts in mineral rights valuation: Technical Value and Market Value. The Technical Value refers to the expected revenue from the mineral rights at a specific valuation date, excluding any discount rates related to market factors. In contrast, the Market Value represents the fair transaction price agreed upon by both parties involved in the mineral rights transaction at the same valuation date. The mineral rights valuation report should present the Market Value of the mineral rights, as the mineral rights valuer cannot determine the fair transaction price between the prospective buyers and sellers. Therefore, the Market Value of the mineral rights should be expressed in terms of a recommended value and a valuation range, enabling both parties to refer to the valuer’s provided valuation range and reach a fair transaction. The valuation range itself reflects the precision of the valuation result. Clearly, if the valuation range is excessively wide, the reference value of the valuation result will be diminished. The main factors affecting the precision of mineral rights valuation results are summarized below:

Resource quantity and reserve levels
Western countries typically classify resource quantities into three categories: Measured (proven), Indicated (controlled), and Inferred (estimated). These categories roughly correspond to China’s resource classification levels of 331 (proven), 332 (controlled), and 333 (estimated). The accuracy of these resource estimates decreases progressively, with corresponding uncertainties of approximately ±10–15%, ±25–35%, and ±50–100%, respectively. Reserve classification must be based on at least a pre-feasibility study. Specifically, 332 resources can be reclassified as Probable reserves, while 331 resources can be reclassified as Proved or Probable reserves. Proved and Probable reserves roughly correspond to China’s recoverable reserves (111) and pre-recoverable reserves (121 and 122), respectively. The accuracy of these reserves improves accordingly, with uncertainties of approximately ±5–10% and ±15–25%, respectively.

It is not difficult to see that, compared to resource estimates, reserve estimates exhibit significantly higher accuracy. The reason is that, during the feasibility study, certain resources deemed unfeasible for development and exploitation were excluded due to limitations in mining technology. At the same time, the cut-off grade used for defining reserves has been raised, thereby enhancing the credibility of the spatial continuity of ore bodies. However, errors inherent in both resource estimates and reserves will always remain and will not change during the valuation process.
 
Degree of feasibility study
According to their level of detail, feasibility studies can be categorized—from low to high—as preliminary studies, pre-feasibility studies, and feasibility studies. Correspondingly, the accuracy gradually improves, reaching ±30–50%, ±20–25%, and ±10–15%, respectively. Among these, the accuracy of capital investment estimates is ±50%, ±25%, and ±15%, while the accuracy of operating cost estimates is ±35%, ±25%, and ±15%. However, some argue that the accuracy of operating cost estimates is influenced by both the design scheme adopted in the feasibility study and the accuracy of the capital investment estimate. Once the accuracy of the capital investment estimate has been established, the accuracy of operating cost estimates should theoretically improve significantly, reaching ±10%, ±5%, and ±0%, respectively (data from different sources in Western countries are not entirely consistent). The total error associated with the feasibility study cannot simply be obtained by adding the errors in capital investment estimation and operating cost estimation, because the inherent uncertainty in resource quantities has already been factored into the overall error corresponding to the level of feasibility study.

The accuracy of the 332 resource estimate is ±25–35%. After preliminary feasibility studies and conversion into pre-mining reserves (121 and 122), the accuracy improves to ±15–25%. The accuracy of capital expenditure estimates is ±25%, while the accuracy of operating cost estimates is ±5%. Following the full feasibility study, the accuracy of pre-mining reserves cannot be significantly improved—reaching, at most, ±5–10%. However, the accuracy of capital expenditure estimates may see some improvement, though it will be difficult to achieve ±15%. Similarly, the accuracy of operating cost estimates will remain challenging to reach ±0%. The accuracy of the 331 resource estimate is ±10–15%. After preliminary feasibility studies and conversion into mining reserves (111), the accuracy improves to ±5–10%. The accuracy of capital expenditure estimates may still be ±25%, while the error in operating cost estimates remains at ±5%. Following the full feasibility study, the accuracy of mining reserves cannot be further enhanced; however, the accuracy of capital expenditure estimates can improve to ±15%, and the accuracy of operating cost estimates can rise to ±0%.

Therefore, the accuracy of estimates for infrastructure investment and operating costs at the feasibility study stage is to some extent constrained by the reserve classification—specifically, the pre-mining recoverable reserves. Once the feasibility study reaches the feasibility stage, the valuation range can narrow as the accuracy of estimates for infrastructure investment and operating costs improves; however, this range still falls short of the level of the recoverable reserves valuation range.

Mineral product sales price
The principle behind mineral rights valuation is to determine the expected revenue from the mineral rights. The expected sales price of mineral products directly and significantly affects the expected revenue from these rights. No one can accurately predict future market conditions. Therefore, whether using the sales price of mineral products on a specific valuation date or forecasts of future markets provided by authoritative agencies, errors will always be present, and uncertainty remains considerable.

Discount rate accuracy
The discount rate is a comprehensive reflection of all market factors and risks that influence the valuation of mining rights, and its value varies over time. In terms of content, it takes into account such factors as the risk associated with the project’s location—the country risk—, the debt levels of the project type and the industry in which the project operates, the corporate income tax rate, expectations regarding the boom and bust cycles of the mining market, and the project’s own inherent risks. As a result, different mining rights appraisers may provide discount rate data that differ from one another for the same project, introducing an element of error. Assuming an objective discount rate of 10%, a margin of error of ±10% would translate into a discount rate range of 9% to 11%.

Commentary
The accuracy of mineral rights valuation results does not merely refer to the precision of the valuation process itself. The optimal range for mineral rights valuation is ±10% around the recommended valuation figure. As outlined above, this level of accuracy can only be achieved when the recoverable reserves have reached the feasibility study stage (category 111) and are evaluated using the discounted cash flow (DCF) method. This fact indirectly highlights that the DCF method is not suitable for resource estimation projects. In China, even after completing studies on development and utilization plans, the valuation accuracy remains relatively low, because such plans still amount to only preliminary studies. In developed mining countries, the DCF method is typically applied to feasibility study and development projects (equivalent to mining rights projects in China) as well as to production projects—projects that generate actual cash flow returns and are treated as mining rights projects in China.

The accuracy of mineral rights valuation primarily depends on the accuracy of reserve classification, the precision of capital expenditure estimates, the accuracy of operating cost estimates, and errors in mineral product prices (mineral rights valuers typically overlook discount rate errors). The net present value (NPV) error in mineral rights valuation cannot be simply obtained by summing up the errors from these individual factors. Instead, a Monte Carlo simulation can be used to derive an approximate normal distribution model for the NPV distribution. In this process, based on the reserve classification accuracy identified in the due diligence report and the data on capital expenditures, operating costs, and mineral product price estimates provided by the feasibility study, the error in reserve classification is translated into corresponding errors in capital expenditure and operating cost estimates. The mode of the approximate normal distribution model for NPV can serve as the recommended valuation figure, while two standard deviations represent the valuation error with a 95% probability (or confidence level). It would be inconsistent and untenable to simply take the recommended valuation figure as a base and then add or subtract 10% to arrive at a range of mineral rights valuation values without considering the aforementioned error sources or conducting sensitivity analyses.

In general, for exploration projects lacking resources, the valuation error of mineral rights is typically ±40%; for resource projects, the error is around ±30%. For feasibility study and development projects as well as production projects, the error is primarily influenced by the level of the feasibility study. The levels of feasibility studies involved mainly refer to preliminary feasibility studies and detailed feasibility studies. The valuation error for preliminary feasibility studies is generally ±20%, while the error for detailed feasibility studies ranges from ±5% to ±10%.