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With the development of science and technology, high-dimensional data are widely applied in the research of econometrics. Designing efficient computing algorithm for high-dimensional econometric models become more and more important recently. Portfolio optimization and quantile regression (QR) are two fundamental pillars in econometrics and finance, respectively. This chapter focuses on introducing efficient computing algorithms for these two models.

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Efficient Computing for High-Dimensional Econometric Models

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Zheng Zhang,
  • Kun Zhang,
  • Xing Yan,
  • Songshan Yang,
  • Yuqian Zhang

摘要

With the development of science and technology, high-dimensional data are widely applied in the research of econometrics. Designing efficient computing algorithm for high-dimensional econometric models become more and more important recently. Portfolio optimization and quantile regression (QR) are two fundamental pillars in econometrics and finance, respectively. This chapter focuses on introducing efficient computing algorithms for these two models.