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Empirical Analysis of the Impact of High and New Technology on the Export of Traditional Cultural Industry Based on Random Matrix Theory

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  • Xingjia Qie
  • Ning Cao

Abstract

Accurate estimation of covariance matrix is the basis of effective development of high-dimensional optimal portfolio. Random matrix theory provides an effective means to improve the estimation of high-dimensional covariance matrix. Based on the empirical research on the export excess return rate of traditional cultural industry, the result is a combination with higher precision and lower risk. Based on relevant data, this paper constructs a stochastic matrix theoretical model to analyze the impact of human capital, new fixed asset investment, independent innovation and technology purchase, financing sources, and other factors on high-tech industry export. Based on the results of empirical analysis, some policy suggestions are put forward, such as increasing r&d investment, improving enterprises’ innovation ability, and introducing core scientific and technological talents to promote the export scale growth of high-tech industries. Model comparative analysis is made on the influence of traditional industries’ concentrated export, foreign trade environment, and cost advantage on the export of high-tech products. Through comparative analysis of the influencing factors of the export of high-tech products in the two periods before and after the export crisis of traditional culture, the new changes of the influencing factors of the export of high-tech products are analyzed. In addition, through the change of the internal and external environment of the current high-tech product export, the reasons for the new change of the influencing factors are discussed.

Suggested Citation

  • Xingjia Qie & Ning Cao, 2022. "Empirical Analysis of the Impact of High and New Technology on the Export of Traditional Cultural Industry Based on Random Matrix Theory," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, August.
  • Handle: RePEc:hin:jnlmpe:1653961
    DOI: 10.1155/2022/1653961
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