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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

Published online by Cambridge University Press:  20 February 2025

Edited by
Shuping Shi ,
Xiaohu Wang  and
Tao Zeng
Shuping Shi
Affiliation:
Macquarie University, Sydney
Xiaohu Wang
Affiliation:
Fudan University, Shanghai
Tao Zeng
Affiliation:
Zhejiang University, China
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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.

Keywords

high-frequency dataintegrated covariance matrixmicrostructure noisehigh dimensionalityinfill asymptotic
Type
Chapter
Information
Financial Econometrics
Theory and Applications
 , pp. 235 - 268
Publisher: Cambridge University Press
Print publication year: 2025

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