Volume-5 Issue-5


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Volume-5 Issue-5, May 2018, ISSN: 2319–6386 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.

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1.

Authors:

Rui Zhang, Fang Chen

Paper Title:

Optimization and Empirical Analysis of Portfolio Model

Abstract: Because the investor's subjective risk preference and the choice of the parameter is different, this paper makes a mathematical modeling for the multi objective portfolio model and transforms it into a single target model. On the other hand, the parameter function is transformed into a linear programming problem, and the optimal investment combination scheme is obtained. Investors can directly choose their own investment direction and make an empirical analysis based on two opposing goals, which are as large as possible and risk as small as possible.

Keywords: Optimization of Portfolio Model, Mathematical Modeling, Linear Programming, Empirical Analysis.

References:

  1. Li Yuming. Securities Investment Science (Second Edition) [M]. Shanghai University of Finance and Economics press, 2017.
  2. Tong Wenbing. The establishment and solution of the linear programming model of venture capital portfolio [J]., statistics and decision making, 2016, (09): 89-91.
  3. Deng Gangyi, Xu Jianyong, Zhou Bin. The linear programming model of risk investment portfolio [J]. mathematics practice and cognition, 1999, (01): 39-42.
  4. Li Xuefeng. Portfolio management [M]. Peking University press, 2015.
  5. Liu Zhiqiang. A solution strategy for linear programming problems with parameters. [J]. middle school mathematics teaching, 2012 (02): 38-39.
  6. The typical application of Matlab and Lingo software in mathematical modeling competition [J]. Mathematical learning and research,2016(03):121.
  7. Zhang qinghai, zhang qiong. Application of Matlab in mathematical modeling [J]. China collective economy,2008(06):170-171.

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2.

Authors:

Yuanxiu Song, Fang Chen

Paper Title:

Data Analysis of "Double Eleven" Shopping Section Based on Regression Model

Abstract: The "Double Eleven" is dominated by commodity trading, and the large increase in the volume of transactions has an undeniable impact on the total retail sales of China's economic indicators. Combination of China statistical yearbook and Chinese commerce intelligence network site data, using E Views software, the "Double Eleven" volume and total retail sales of social consumer goods data modeling analysis, trading as explanatory variables, is social consumer goods as explained variable regression analysis. Through data analysis and testing, the model obtained a linear relationship between the two and presented specific data links, which further explained the contribution of "Double Eleven" to the total retail sales of consumer goods. Based on the data analysis, the corresponding suggestions are made to consumers.

Keywords: "Double Eleven"; Total Retail Sales of Consumer Goods; Linear Regression Model

References:

  1. Pang Hao. Econometrics (third edition) [M]. Beijing: Science press, 2014:48-55.
  2. Wang Lei. Research on the application of big data in shopping craze [J]. Neijiang t echnology, 2016, (5).
  3. Jin Xinyue. "Double Eleven" e-commerce shopping big data analysis [J].The Exam Week, 2017, (82).
  4. Lian Yixin.Analysis of "Double Eleven" economic phenomenon based on date analysis[J]. Commercial Circulation,2016,(1).

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3.

Authors:

Suting Liu, Fang Chen

Paper Title:

Analysis of Residents' Consumption in China's Domestic Tourism

Abstract: Tourism, as a new type of advanced social consumption, integrates the material life consumption and the cultural life consumption organically through tourism consumption. This article adopts econometric statistics methods for domestic tourism consumption in 1997-2016 and establishes a multiple regression model to study the intrinsic interactions between tourism consumption, domestic tourist numbers and total residents' consumption. Based on the results, it makes reasonable forecasts on the future growth of tourism consumption.

Keywords: Total Domestic Tourism Consumption; Residents' Total Consumption; Multiple Regression Model; Multicollinearity;

References:

  1. Yao Zhanqi. Empirical Analysis of Influencing Factors of Domestic Tourism Income in China [J]. Innovation, 2015, (3)
  2. Guo Lijun. Research on Domestic Tourism Revenue Based on Econometrics Model [J]. Cooperation Economy and Technology, 2007, (10).
  3. Wang Zhanxiang. Analysis of the Influencing Factors of China's Domestic Tourism Income [J]. Mall Modernization, 2008, (36).
  4. Xu Jianguo. Empirical analysis of influencing factors of domestic tourism income[J]. Journal of Luohe Vocational and Technical College,2009,(5)

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