Estimating Jump Activity Using Multipower Variation

69 Pages Posted: 12 Jul 2018 Last revised: 15 Dec 2020

See all articles by Aleksey Kolokolov

Aleksey Kolokolov

University of Manchester - Manchester Business School

Date Written: June 20, 2018

Abstract

Realized multipower variation, originally introduced to eliminate jumps, can be extremely useful for inference in pure-jump models. The paper shows how to build a simple and precise estimator of the jump activity index of a semimartingale observed at a high frequency by comparing different multipowers. The novel methodology allows to infer whether a discretely observed process contains a continuous martingale component. The empirical part of the paper undertakes a nonparametric analysis of jump activity of bitcoin. The implementation of the new jump activity estimator indicates that bitcoin is a pure jump process with high jump activity, which is critically different from conventional currencies that include a Brownian motion component.

Keywords: Jump Activity, Bitcoin, Jumps, Multipower Variation, High-Frequency Data

JEL Classification: C58, C01, G10

Suggested Citation

Kolokolov, Aleksey, Estimating Jump Activity Using Multipower Variation (June 20, 2018). Available at SSRN: https://ssrn.com/abstract=3200040 or http://dx.doi.org/10.2139/ssrn.3200040

Aleksey Kolokolov (Contact Author)

University of Manchester - Manchester Business School ( email )

Booth Street West
Manchester, M15 6PB
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
78
Abstract Views
642
rank
416,962
PlumX Metrics