Inference for Time-Varying Lead-Lag Relationships from Ultra High Frequency Data

40 Pages Posted: 2 Mar 2017

See all articles by Yuta Koike

Yuta Koike

Tokyo Metropolitan University

Date Written: February 28, 2017

Abstract

A new approach for modeling lead-lag relationships in high frequency financial markets is proposed. The model is accommodated to non-synchronous trading and market microstructure noise as well as intraday variations of lead-lag relationships, which are essential for empirical applications. A simple statistical methodology for analyzing the proposed model is presented as well. The methodology is illustrated by an empirical study to detect lead-lag relationships between the S&P 500 index and its two derivative products.

Keywords: High-Frequency Data, Lead-Lag Relationship, Microstructure Noise, Non-Synchronous Observations, Semimartingale, Stable Convergence

JEL Classification: C14, C51, C58

Suggested Citation

Koike, Yuta, Inference for Time-Varying Lead-Lag Relationships from Ultra High Frequency Data (February 28, 2017). Available at SSRN: https://ssrn.com/abstract=2924301 or http://dx.doi.org/10.2139/ssrn.2924301

Yuta Koike (Contact Author)

Tokyo Metropolitan University ( email )

Marunouchi Eiraku Bldg. 18F
1-4-1 Marunouchi
Chiyoda-ku, Tokyo 100-0005
Japan

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