Quantitative Business Methods Forecasting Models

Question: Describe about the Quantitative Business Methods for Forecasting Models. Answer: Part (a) The forecasting models present , helps in analysing the future trends in which a particular sector might show the trend of its future prospect to be followed (Anderson, et al., 2013). For framing the efficient forecasting method of the telecommunications apparatus and computer sector , the model that should be used in order to achieve an efficient forecast, is the moving average method. Moving Average Method as stated by Ali, et al., (2015), based on a given series and number sets of a previous data extracted from the companys source of data provided, moving average can be conducted. This is a statistical tool that analyses the average data based on the intervals. On performing the specified formula, the pattern of the past trend and events of an organization can be achieved. This past trend or pattern, is helpful in determining the future prospects of the organization. It is assumed that a companys future trends follows the past trends that has been followed. Hence, with the use of moving average methods, we can derive forecast for the telecommunication apparatus and computer sector, that would show how the future trend and pattern of the industry would be in the year 2017. Part (b) Moving average is calculated based on the source derived from the data provided for the retail sales index of the telecommunications apparatus and computer sector. As stated by Guo, et al., (2013), retail sales index analyses the short term trends and changes that has occurred in the consumption structure of a particular market respective sector. In this analysis , the retail sales index of the telecommunication and the computer sector has been analysed for from January , 2013 to June , 2016. The retail sales index of these years with the base index of the year 2014, shows, how the changes has been discovered in the consumption pattern of the people for the referred sector. In order to forecast the future trend of consumption made with respect to the telecommunication apparatus and computer sector, the statistical analysis of moving average has been determined , with the interval of 6 months. The moving average results have helped us to analyse the current trend that has fooled in the retail sales index of the industry for the past 4 years. According to Huarng, Yu, (2014), Moving Average (Ft) = (sum of actual values in previous n periods) / n = (Y t-1 + Y t-2 + ..... + Y t-n) / n Figure 1 shows the moving average results that has been derived by conducting the process. Figure 1 : Trend Of The Moving Average (Source : As Created By The Author) In figure 2, the original retail sales index and the moving average index with the interval of 6 months has been analysed ,where we see how these two line are plotted against the same time period. The blue line indicates the original retail sales index of the telecommunication apparatus and the computer sector, whereas, the red lines shows the moving average at an interval of six months. A purple dotted line has been used to show the trend in which these two lines move. This helps in predicting the future trend of consumption forecast in the telecommunication and the computer sector. Figure 2 : Retail Sales Index, Moving Average And Forecast For Telecommunication Apparatus And Computer Sector (Source : As Created By The Author) Part (c) With the help of figure 2, it can be seen that a downward sloping trend line in attained with the help of the forecasting model , moving average used. This trend line indicates that there is most probably a fall in the future retail sales index, which indicates that comparatively to the base year 2014, there would be a fall in consumption pattern of the telecommunications apparatus and the computer sector in the year 2017. With the help of this pattern, the management group of this industry has been capable of achieving a vivid view of the future projection path. Hence, in order to mend the pattern, the management group of the company must raise their technological tools to be implemented in the production process, raise the connectivity and use efficient cost effective methods of production in order to lower their cost of production (Li, et al., 2013). Low cost of production would enable the people to provide the service to the customers at much lower rate. Hence, this would affect the demand of the sector positively. A positive raise in the sales of the sector would help in attaining a pattern different from the trend line. Achieving a sudden growth of the telecommunication sector is not possible, yet with the implementation of strategical plans , this could be achieved within a span of two years. Reference Ali, A., Wang, Y., Li, W., He, X. (2015, December). Implementation of simple moving voltage average technique with direct control incremental conductance method to optimize the efficiency of DC microgrid. InEmerging Technologies (ICET), 2015 International Conference on(pp. 1-5). IEEE. Anderson, E., Malin, B. A., Nakamura, E., Simester, D., Steinsson, J. (2013).Informational rigidities and the stickiness of temporary sales(No. w19350). National Bureau of Economic Research. Guo, Z. X., Wong, W. K., Li, M. (2013). A multivariate intelligent decision-making model for retail sales forecasting.Decision Support Systems,55(1), 247-255. Huarng, K. H., Yu, T. H. K. (2014). A new quantile regression forecasting model.Journal of Business Research,67(5), 779-784. Li, H. Z., Guo, S., Li, C. J., Sun, J. Q. (2013). 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