A Multiscale Estimator for Pricing Error Decomposition in High-Frequency Financial Markets

77 Pages Posted: 15 May 2019 Last revised: 20 Mar 2023

See all articles by Louis R. Piccotti

Louis R. Piccotti

Oklahoma State University - Stillwater - Spears School of Business

Date Written: March 20, 2023

Abstract

For a Lévy process corrupted with microstructure noise, sampling distributions are derived for the information-related and information-unrelated pricing error parameters and for the variance of latent true price returns (a noise-robust and consistent estimator of realized variance). The test statistics converge in distribution to the standard normal distribution, while statistics for joint tests, tests for intraday seasonality, and tests for time varying parameters converge in distribution to the χ^2 distribution. Simulation evidence verifies that test statistics display good size and power properties. As an application, the proposed tests are taken to a sample of exchange rates, commodities, and index futures.

Keywords: market microstructure noise, multi-frequency estimator, high-frequency data

JEL Classification: C01, C1, G14

Suggested Citation

Piccotti, Louis R., A Multiscale Estimator for Pricing Error Decomposition in High-Frequency Financial Markets (March 20, 2023). Available at SSRN: https://ssrn.com/abstract=3375054 or http://dx.doi.org/10.2139/ssrn.3375054

Louis R. Piccotti (Contact Author)

Oklahoma State University - Stillwater - Spears School of Business ( email )

460 Business
Stillwater, OK 74078-0555
United States

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