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  • 8 - Estimation of Integrated Covariance Matrix Using High-Frequency Data with Applications in Portfolio Choice

  • from Part II - Continuous-Time Models and High-Frequency Financial Econometrics
  • Edited by Shuping Shi, Macquarie University, Sydney, Xiaohu Wang, Fudan University, Shanghai, Tao Zeng, Zhejiang University, China
  • Book:
    Financial Econometrics
    Published online:
    20 February 2025
    Print publication:
    27 February 2025, pp 235-268

  • Summary

    This chapter reviews alternative methods for estimating the integrated covariance matrix (ICM) using high-frequency data and their properties. The high-frequency data are assumed to come from a continuous-time model. The alternative estimators are justified by their asymptotic properties under the infill asymptotic scheme, which requires that the time interval Δ between any two consecutive observations go to zero. When reviewing the methods, we separate the methods that assume the dimension of the ICM is fixed and those that assume the dimension of the ICM goes to infinity with the sample size. Comparisons of the performances of alternative ICM estimators in portfolio choice are discussed.