Common price and volatility jumps in noisy high-frequency data
type: Item
instance of: scholarly article
title: Common price and volatility jumps in noisy high-frequency data
zbMATH Open document ID: 1398.62281
DOI: 10.1214/18-EJS1444
author: Markus Bibinger
author: Lars Winkelmann
published in: Electronic Journal of Statistics
publication date: 2018-08-14T00:00:00Z
full work available at URL: https://projecteuclid.org/euclid.ejs/1529308886
review text: This paper deals with testing high-frequency financial data for simultaneous jumps in price and volatility. The investigated data model is of the form \[ Y_{i} = X_{i/n} + \epsilon_i \] with the latent log-price process \(X\) satisfying \[ X_t = X_0 + \int_0^t b_s d s + \int_0^t \sigma_s d W_s + P(t), \] where \(P\) is another specific random process generating jumps. To test for simultaneous jumps in price and volatility, first price jumps are localized via thresholding, and afterwards local tests for volatility jumps based on self-scaling test statistics are performed. The asymptotic distribution of this test statistic is analyzed, such that the testing procedure can be properly calibrated. Details on a possible implementation are provided, as well as a simulation study which reveals the investigated procedure to be robust w.r.t. the microstructure noise \(\epsilon_i\). The procedure is furthermore applied to real NASDAQ data.
reviewed by: Frank Werner
Mathematics Subject Classification ID: 62P05
Mathematics Subject Classification ID: 62M09
Mathematics Subject Classification ID: 62G10
Mathematics Subject Classification ID: 62M10
zbMATH DE Number: 6917430
zbMATH Keywords: high-frequency data
zbMATH Keywords: microstructure noise
zbMATH Keywords: nonparametric volatility estimation
zbMATH Keywords: volatility jumps
MaRDI profile type: Publication
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Wikidata QID: Q129679947
description: scientific article; zbMATH DE number 6917430