Academic Journal of Business & Management, 2022, 4(17); doi: 10.25236/AJBM.2022.041708.
Junchao Zhang, Yisheng Huang, Chengbiao Huang, Wei Huang
Guilin University of Technology at Nanning, Chongzuo, Guangxi, China, 532200
The stock market is the most active and main component of the stock market. The operating situation of the stock market is a thumbnail of a country's macroeconomic development. With the continuous development of China's market economy, the increasingly perfect financial market, and the soaring enthusiasm for investment in society, stocks, as a way and means of financing, play an increasingly important role in promoting investment and financing, improving the turnover rate and efficiency of funds, promoting the rational allocation of scarce resources, stabilizing the capital chain of the real economy, and thus improving the welfare of the whole society. It is of theoretical and practical significance to study the relationship between stock turnover and macroeconomic variables, explore the influencing factors of stock turnover, so as to make more accurate analysis and prediction in the future, grasp the market situation more accurately, and better serve the economy and society. Based on the requirements given by the title: the data information given by the "Digital Economy" section every five minutes from July 14, 2021 to January 28, 2022 will be filtered out of the given attachments, and the unnecessary time data will be deleted to obtain a new attachment table. According to the macro market indicators, domestic market indicators, technical indicators, international market indicators 46 sub categories of indicators in the exchange rate category use the clustering method of taking the average value to express the indicators of the month, use the method of multiple linear regression to construct a multiple linear regression model to obtain the correlation coefficient, and analyze to get the more influential indicators.
Multiple linear regression, ARIMA time series model, SPSS, Least square method
Junchao Zhang, Yisheng Huang, Chengbiao Huang, Wei Huang. Research on ARIMA Based Quantitative Investment Model. Academic Journal of Business & Management (2022) Vol. 4, Issue 17: 54-62. https://doi.org/10.25236/AJBM.2022.041708.
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