Testing for Jumps in a Discretely Observed Price Process with Endogenous Sampling Times

53 Pages Posted: 14 Nov 2021 Last revised: 18 May 2024

See all articles by Qiyuan Li

Qiyuan Li

Singapore Management University - School of Economics

Yifan Li

The University of Manchester - Alliance Manchester Business School; Lancaster University - Department of Accounting and Finance

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Sandra Nolte (Lechner)

Lancaster University Management School

Shifan Yu

University of Oxford - Oxford-Man Institute of Quantitative Finance; Lancaster University Management School

Date Written: May 17, 2024

Abstract

This paper introduces a novel nonparametric high-frequency jump test for discretely observed Itô semimartingales. Based on observations sampled recursively at first exit times from a symmetric double barrier, our method distinguishes between threshold exceedances caused by the Brownian component and jumps, which enables the construction of a feasible, noise-robust statistical test. Simulation results demonstrate superior finite-sample performance of our test compared to classical methods. An empirical analysis of NYSE-traded stocks provides clear statistical evidence for jumps, with the results highly robust to spurious detections.

Keywords: High-Frequency Data, Jump Test, Market Microstructure Noise, Stochastic Sampling Scheme, First Exit Time

JEL Classification: C12, C14, C22, C58

Suggested Citation

Li, Qiyuan and Li, Yifan and Nolte, Ingmar and Nolte (Lechner), Sandra and Yu, Shifan, Testing for Jumps in a Discretely Observed Price Process with Endogenous Sampling Times (May 17, 2024). Available at SSRN: https://ssrn.com/abstract=3943203 or http://dx.doi.org/10.2139/ssrn.3943203

Qiyuan Li

Singapore Management University - School of Economics ( email )

90 Stamford Road
178903
Singapore

Yifan Li

The University of Manchester - Alliance Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

Lancaster University - Department of Accounting and Finance ( email )

The Management School
Lancaster LA1 4YX
United Kingdom

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Sandra Nolte (Lechner)

Lancaster University Management School ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Shifan Yu (Contact Author)

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Lancaster University Management School ( email )

Department of Accounting and Finance
Lancaster University Management School
Lancaster, LA1 4YX
United Kingdom

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