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A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices

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Listed:
  • Tim Leung

    (Applied Mathematics Department, University of Washington, Seattle, WA 98195, USA)

  • Theodore Zhao

    (Applied Mathematics Department, University of Washington, Seattle, WA 98195, USA)

Abstract

We analyze the multiscale behaviors of high-frequency intraday prices, with a focus on how asset prices are correlated over different timescales. The multiscale approach proposed in this paper is designed for the analysis of high-frequency intraday prices. It incorporates microstructure noise into the stochastic price process. We consider a noisy fractional Brownian motion model and illustrate its various statistical properties. This leads us to introduce new latent correlation and noise estimators. New numerical algorithms are developed for model estimation using empirical high-frequency data. For a collection of stocks and exchange-traded funds, examples are provided to illustrate the relationship between multiscale correlation and sampling frequency as well as the evolution of multiscale correlation over time.

Suggested Citation

  • Tim Leung & Theodore Zhao, 2024. "A Noisy Fractional Brownian Motion Model for Multiscale Correlation Analysis of High-Frequency Prices," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:6:p:864-:d:1357687
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    References listed on IDEAS

    as
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