Formation of Long-Term Prognosis of Global Automotive Industry, Based on Fundamental Factors - Кирилл Юрьевич Курилов (Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438, 2012)
Author: Kirill Yurievich Kurilov - National Research University "Higher School of Economics."The specificity of the automotive industry - a lot of competition, the need to rapidly update the model range, innovative development and attract significant investment makes paramount the formation of projections of the future development of the industry - namely, sales and production cars. Lack of reliable forecast can lead to short-term negative consequences, such as overstocking of finished goods warehouses and enterprise into bankruptcy car manufacturer. A striking example is the American company car manufacturer GM, which in 2008 due to incorrect strategy selected went bankrupt and was rescued by emergency financial effects of the state. However, well-formed forecasts of sales volume can achieve a leading position in the market of vehicles. For example, Toyota as a result of the crisis in 2008 to 2009 was able to consolidate its position as a manufacturer of automobiles.Forecasting can be carried out by various methods, including using the analysis of the impact on the volume of vehicles of various factors and the construction of the regression equation. This approach is more objective because it uses established statistical relationship between the predicted parameter and factors that render it the most significant impact. To form the regression equation used data on volumes of production of vehicles for the period from 1950 to 2009, as well as data on oil prices, inflation, income and population, as well as vehicle registration. For each of the indicators evaluated the effect of rate of production (sales) of vehicles. As a result of the analysis of the forces of influence of each factor selected indicators have a significant impact on sales figures and production vehicles. Between all the selected parameters was determined by showing the pair correlation between them. As a result of this evaluation were excluded indicators that have a significant relationship between them.Оn the basis of the selected groups of factors were generated forecast changes in production until 2025. Using the data prepared by the forecast of change in sales of vehicles.