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<p>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 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({\chi }^{2}\)</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mrow> <mi>χ</mi> </mrow> <mn>2</mn> </msup> </math></EquationSource> </InlineEquation> 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.</p>

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A multiscale estimator for pricing error decomposition in high-frequency financial markets

  • 期刊论文

  • 发表日期：

    2025年5月21日

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  • Louis R. Piccotti

摘要

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 \({\chi }^{2}\) 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.