Estimation of the lead–lag parameter between two stochastic processes driven by fractional Brownian motions

• Published in: Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems Vol. 22; no. 3; pp. 323 - 357
• Main Author: Chiba, Kohei
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.10.2019; Springer Nature B.V
• Subjects: Computer simulation; Convergence; Economic models; Ion migration; Mathematical models; Mathematics; Mathematics and Statistics; Parameter estimation; Probability Theory and Stochastic Processes; Process parameters; Statistical Theory and Methods; Stochastic models; Stochastic processes; 60G22; 62M09; Non-synchronous observations; Contrast estimation; Fractional Brownian motion; Lead–lag effect
• ISSN: 1387-0874; 1572-9311
• DOI: 10.1007/s11203-018-09195-5

In this paper, we consider the problem of estimating the lead–lag parameter between two stochastic processes driven by fractional Brownian motions (fBMs) of the Hurst parameter greater than 1/2. First we propose a lead–lag model between two stochastic processes involving fBMs, and then construct a consistent estimator of the lead–lag parameter with possible convergence rate. Our estimator has the following two features. Firstly, we can construct the lead–lag estimator without using the Hurst parameters of the underlying fBMs. Secondly, our estimator can deal with some non-synchronous and irregular observations. We explicitly calculate possible convergence rate when the observation times are (1) synchronous and equidistant, and (2) given by the Poisson sampling scheme. We also present numerical simulations of our results using the R package YUIMA.