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Title: Separate noise and jumps: A price duration approach Authors:  Oliver Linton - University of Cambridge (United Kingdom)
Xiaolu Zhao - Dongbei University of Finance and Economics (China)
Seok Young Hong - Lancaster University Management School (United Kingdom) [presenting]
Abstract: The problem of jump detection is studied for high-frequency data using a price duration approach. We propose a novel estimator that separates both the contribution of microstructure noise and that of ``large'' price jumps from the price process, which may have interesting implications on asset pricing and forecasting problems. We show the asymptotic normality of our estimator and suggests practical guidelines for determining the tuning parameter thereof. Making a comparison with the ``star performers'' in a recent comprehensive review, we show that our method performs well via extensive simulation studies.