id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-027463-uc0j3fyi	Brandi, Giuseppe	A New Multilayer Network Construction via Tensor Learning	2020-05-25		.txt	text/plain	2474	147	52	Tensors are objects that naturally represent multilayer networks and in this paper, we propose a new methodology based on Tucker tensor autoregression in order to build a multilayer network directly from data. The constructed multilayer network shows a strong interconnection between the volumes and prices layers across all the stocks considered while a lower number of interconnections between the uncertainty measures is identified. In particular, we use the tensor learning approach establish in [6] to estimate the tensor coefficients, which are the building blocks of the multilayer network of the intra and inter dependencies in the analyzed financial data. The multilayer network built via the estimated tensor autoregression coefficient B represents the interconnections between and within each layer. In this paper, we proposed a methodology to build a multilayer network via the estimated coefficient of the Tucker tensor autoregression of [6] .	./cache/cord-027463-uc0j3fyi.txt	./txt/cord-027463-uc0j3fyi.txt