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We introduce a new non parametric method that allows for a direct, fast andefficient estimation of the matrix of kernel norms of a multivariate Hawkesprocess, also called branching ratio matrix. We demonstrate the capabilities ofthis method by applying it to high-frequency order book data from the EUREXexchange. We show that it is able to uncover (or recover) various relationshipsbetween all the first level order book events associated with some asset whenmapped to a 12-dimensional process. We then scale up the model so as to accountfor events on two assets simultaneously and we discuss the joint high-frequencydynamics.

Analysis of order book flows using a nonparametric estimation of the branching ratio matrix