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Study on Application of time series analysis based on cigarette sales

Author: CaoLuDong
Tutor: LiXingXu
School: Yunnan University of Finance
Course: Applied Statistics
Keywords: seasonal time series cigarette sales forecasting
Type: Master's thesis
Year: 2013
Downloads: 2
Quote: 0
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Many social and economic phenomena have close relationship with time. Inorder to understand these economic phenomena,we need to study the law of thechanges over time. The study of series rules cannot without data analysis ofeconomic phenomenon. And commonly this kind of observation data is time seriesdata. This paper use the monthly sales of48cigarette to analysis and discuss based onthe basic principle of seasonal time series analysis. Stochastic time series analysisoriginated in the20th century by the British statistician Yule put forward using thelinear regression equation model to fitting a time sequence of ideas. With thedevelopment of computer applications in the1970s, American Box and Jenkinspublished monograph book "time series analysis, forecast and control", whichsystematically expounded the time series modeling theory, making the time seriesanalysis method widely used, and providing the system methods of forecasting. All ofthese theoretical knowledge introduction laid a solid foundation for the establishmentof the new model in this paper.This article is divided into six chapters, the first chapter is the introduction. Thispart firstly introduces the research background, purpose and the selected topicsignificance. Next to the advances of domestic and foreign scholars for the tobaccoindustry. Finally elaborated the paper research methods, as well as the possibleinnovation and deficiency. The second chapter is mainly instruction the time seriestheory. Fist of all, we reviewed the history of the time series theory, particularlypointed out that in the1970’s, Box and Jenkins, published monographs "time seriesanalysis, forecast and control". Followed by illustrating the characteristic of seasonaltime series, this paper expounds the difference and the seasonal difference of timeseries and the inspection methods. Especially the seasonal time series modelingprocess has carried on the detailed instructions. The third chapter has carried on theanalysis about the present situation of the tobacco industry. The fourth chapter is tomake an empirical analysis of the type of cigarette sales in China. First of all I takethe descriptive statistical analysis the monthly sales data of cigarettes for four years.Then I use the principle of seasonal time series to make the data analysis of the fistclass cigarette.And then establishes the season time predictionmodel ARIMA(1,1,0)(1,1,1)12. Finally using the prediction model to make a forecast The fifth chapter is through the analysis of chapter4you can see the future type ofcigarette market will keep continuing expansion situation, what we should takerelative measures to promote the healthy and stable development of the cigarettemarket. Chapter6is the full text summary. Summarized in this paper, mainconclusions and innovations, follow-up studies were discussed.This article adopts the way of combining qualitative analysis with quantitativeanalysis.By comparing the domestic cigarette market sales,I carried on the descriptivestatistical analysis of the current industry development situation. Then, based on timethe seasonal time series analysis theory and the data of monthly cigarette sales, weestablished the forecasting model ARIMA(1,1,0)(1,1,1)12.

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