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Title: Lead-lag analysis of non-synchronously observed time series with R Authors:  Yuta Koike - Tokyo Metropolitan University (Japan) [presenting]
Abstract: A lead-lag relationship is a time-lagged correlation structure of two time series wherein one is correlated to the other with a delay. It has also been well-recognized since long ago that the non-synchronicity of observation times of two time series causes a serious bias in estimating lead-lag relationships. To overcome this issue, a recent work has introduced a novel approach to compute the cross-covariances of the returns of two non-synchronously observed time series as well as proposed a simple statistic to measure their lead-lag relationship. The methodology is not only applicable to high-frequency financial data but also applicable to SNS data, so it could provide a useful tool for lead-lag analysis of time series to empirical researchers in any areas. R package yuima provides systematic functions to conveniently apply this methodology to real time series. The aim is to present them to empirical researchers as well as to show what we can really do in yuima. As an illustration, we will demonstrate its application to real data.