Detection and clustering of lead-lag networks for multivariate time series with an application to financial markets - Bennett, S; Cucuringu, M; Reinert, G (2022)
In this paper, we propose a method for the detection of lead-lag clusters in multivariate time series, using a pairwise lead-lag metric and a directed network clustering algorithm. We demonstrate that the latent network of pairwise lead-lag relationships between time series can be helpfully construed as a directed network, for which there exists a suitable algorithm for the detection of pairs of lead-lag clusters with high pairwise imbalance. Our method is able to detect statistically significant lead-lag clusters in our primary domain of study, the US equity market. We study the nature of these clustersin the context of the empirical finance literature on lead-lag relations.