Evaluating the Underlying Components of High Frequency Financial Data: Finite Sample Performance and Microstructure Noise Effects

37 Pages Posted: 3 Aug 2020

See all articles by Rodrigo Hizmeri

Rodrigo Hizmeri

Lancaster University

Marwan Izzeldin

Lancaster University Management School

Date Written: June 19, 2020

Abstract

This paper examines the finite sample properties of novel theoretical tests that evaluate the presence of: a) Brownian motion, b) jumps; c) finite vs. infinite activity jumps. In allowing for Gaussian, t-distributed, and Gaussian-T mixture noise, our Monte Carlo experiment guides a search for optimal performance across sampling frequencies. Using 100 stocks and SPY, we find that: i) a Brownian and a jump component characterize 1-min stock data; ii) Jumps should allow for both finite and infinite activity; iii) Rejection rates are time-varying, such that more jump days are usually associated with an increase of infinite jumps vis-à-vis finite jumps.

Keywords: high-frequency data, infinite jumps, finite jumps, Brownian motion, microstructure noise, continuous-time-models

JEL Classification: C14, C15, C58, G01

Suggested Citation

Hizmeri, Rodrigo and Izzeldin, Marwan, Evaluating the Underlying Components of High Frequency Financial Data: Finite Sample Performance and Microstructure Noise Effects (June 19, 2020). Available at SSRN: https://ssrn.com/abstract=3639110 or http://dx.doi.org/10.2139/ssrn.3639110

Rodrigo Hizmeri (Contact Author)

Lancaster University ( email )

Economics Department,
LUMS,
Bailrigg Lancaster, LA1 4YX
United Kingdom

Marwan Izzeldin

Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom
01524 594674 (Phone)

HOME PAGE: http://www.lums.lancs.ac.uk/profiles/marwan-izzeldin/

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