A Multiscale Estimator for Pricing Errors in High-Frequency Financial Markets

71 Pages Posted: 15 May 2019 Last revised: 20 May 2020

See all articles by Louis R. Piccotti

Louis R. Piccotti

Oklahoma State University - Stillwater - Spears School of Business

Date Written: May 19, 2020

Abstract

For a Lévy process corrupted with microstructure noise, I derive the sampling distributions 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 properties. As an empirical example, 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 Errors in High-Frequency Financial Markets (May 19, 2020). 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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