Wavelet-based methods for high-frequency lead-lag analysis

Takaki Hayashi, Yuta Koike

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We propose a novel framework to investigate lead-lag relationships between two financial assets. Our framework bridges a gap between continuous-time modeling based on Brownian motion and the existing wavelet methods for lead-lag analysis based on discrete-time models and enables us to analyze the multiscale structure of lead-lag effects. We also present a statistical methodology for the scale-by-scale analysis of lead-lag effects in the proposed framework and develop an asymptotic theory applicable to a situation including stochastic volatilities and irregular sampling. Finally, we report several numerical experiments to demonstrate how our framework works in practice.

Original languageEnglish
Pages (from-to)1208-1248
Number of pages41
JournalSIAM Journal on Financial Mathematics
Volume9
Issue number4
DOIs
Publication statusPublished - 2018 Jan 1

Fingerprint

Wavelets
Lead
Irregular Sampling
Stochastic Volatility
Discrete-time Model
Brownian movement
Asymptotic Theory
Brownian motion
Continuous Time
Numerical Experiment
Sampling
Framework
Lag
Methodology
Modeling
Demonstrate
Experiments
Lead-lag effect

Keywords

  • Brownian motion
  • High-frequency data
  • Lead-lag effect
  • Multiscale modeling
  • Wavelet

ASJC Scopus subject areas

  • Numerical Analysis
  • Finance
  • Applied Mathematics

Cite this

Wavelet-based methods for high-frequency lead-lag analysis . / Hayashi, Takaki; Koike, Yuta.

In: SIAM Journal on Financial Mathematics, Vol. 9, No. 4, 01.01.2018, p. 1208-1248.

Research output: Contribution to journalArticle

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