عنوان مقاله [English]
Despite that discounted cash flow (DCF) method is widely used for valuing of projects, particularly in mining activities, a new approach named Real Option (RO) has entered for financial valuation of investment projects in last three decades. Compared to the DCF method, the RO benefits from: 1- considering managerial flexibility and its influence on the project’s final value,2- not using project risk rate to discount future values. In the projects with high level of risk such as mining projects, the management flexibility has important effect on increasing the project value, which is simply omitted in the DCF. Besides, one of the main challenges in the DCF is selecting a suitable risk rate for discounting the future values while the RO has overcome on this matter. The mining development operation is among the high risk and costly projects. In the development projects, the option to defer is a common option that exists in the investment management systems. To obtain more benefit using this option, considering the ore price volatility and other sources of risk, managers can defer the investing action to a suitable time. This type of management flexibility makes a premium value to the project, which is easily omitted by traditional valuation methods. These types of options are similar to the American call option existing in the financial markets. In the current study, the option to defer is simulated according to the American call option. This real option is valued using a financial tool which is developed for the American call option, known as the Monte Carlo Least Squares Method (LSM). The LSM is the most efficient RO theory technique that was used here for valuation of mining development projects. Among the RO methods, there are different ways applicable in mining complicated projects; the LSM method is entirely efficient in this regard. In this paper, a valuation algorithm was designed and the Lihir Australian gold mine was valued via programming in MATLAB. Considering the gold price risk and via the Monte Carlo method, the stochastic volatility was simulated using the GBM model (100,000 simulated paths). To reduce the convergence time, the antithetic simulation method was used. On each price path, in backward direction, the mine values (V) minus the executing cost of the development operation (I) are compared with the expected profits from postponing the operation (E (V-I)). Therefore, the maximum values and the optimum policies can be selected. The expected values were estimated by the LSM. The final project value is the expected value of all optimum values, resulting from the optimum decision making policies. The results showed that the DCF estimated value is by 44% less than the RO outcome. It means that the DCF method cannot estimate the additional value of management flexibility while this value is a large portion of the total one estimated by the LSM. These results dictate that, in the projects such as mining activities, the DCF method is not a suitable valuation tool and seems more reasonable to be used along with the RO-based methods, in particular the LSM as the auxiliary tool.