چکیده:
The demand for durable goods, including automobiles, is accompanied by fluctuations. Econometric methods are not suitable methods for forecasting demand. In this research, car demand is predicted using the real options method and Monte Carlo simulation. The real options method models options based on their fluctuations and the probability distribution of the model's error. This method has an advantage over econometric methods by considering the risks and uncertainties present in the future demand trend. In this research, forecasting has been performed based on the real options approach, assuming both the presence and absence of correlation between product demands. The MAE, MSE, and RMSE criteria show that forecasting based on this approach with the assumption of correlation is more appropriate.
خلاصه ماشینی:
In this research, using the real option approach and employing Monte Carlo simulation, the demand for products of the Saipa automotive group for the period 1387- 1389 has been forecasted under the assumption of the existence and non-existence of correlation between product demands.
The sections of this article are as follows: In the second section, a review of the real option method is conducted; in the third section, a review of demand modeling and the demand modeling process within the real option framework is addressed; in the fourth section of the article, expected demand is examined; in the fifth section, first the research data and descriptive statistics of the research data are reported, then using the real option approach, in-sample and out-of-sample demand forecasting under various assumptions for a future period is performed, and the results are evaluated using various criteria; and in the sixth section, the research results are presented.
Ming-Guan Huang, (2008), “Real options approach-based demand forecasting method for a range of products with highly volatile and correlated demand”, Department of Finance and Banking, Shih Chien University,70,Ta-Chih Street,Taipei,Taiwan,ROC.
From equation number (7), the demand forecasting model at time T+ for product i can be expressed as follows: (Refer to page image) , , If the correlation between demands is considered, in equation (17), the set of independent variables η must be replaced with the set of correlated variables ε.
Therefore, this study presents a demand forecasting method based on the Real Option approach for the demand of a group of products with high fluctuations and correlation.
In this research, automobile demand is forecasted using the real options method and Monte Carlo simulation.
In this research, forecasting has been performed based on the real options approach, assuming both the existence and non-existence of correlation between product demands.
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