Robust estimation of time-dependent precision matrix with application to the cryptocurrency market

作     者：Paola Stolfi Mauro Bernardi Davide Vergni 

作者机构：Institute for Applied Mathematics“Mauro Picone”(IAC)-National Research Council of ItalyVia dei Taurini 1900185 RomeItaly Department of Statistical SciencesUniversity of PadovaVia C.Battisti24135121 PaduaItaly 

出 版 物：《Financial Innovation》 (金融创新（英文）)

年 卷 期：2022年第8卷第1期

页      面：1313-1337页

核心收录：

学科分类：0202[经济学-应用经济学] 1202[管理学-工商管理] 07[理学] 0701[理学-数学] 070101[理学-基础数学] 

主　　题：Time-varying models Robust methods Kernel estimation Precision matrix Divergence 

摘      要：Most financial signals show time dependency that,combined with noisy and extreme events,poses serious problems in the parameter estimations of statistical ***,when addressing asset pricing,portfolio selection,and investment strategies,accurate estimates of the relationship among assets are as necessary as are delicate in a time-dependent *** this regard,fundamental tools that increasingly attract research interests are precision matrix and graphical models,which are able to obtain insights into the joint evolution of financial *** this paper,we present a robust divergence estimator for a time-varying precision matrix that can manage both the extreme events and time-dependency that affect financial time ***,we provide an algorithm to handle parameter estimations that uses the“maximization–minimization*** apply the methodology to synthetic data to test its ***,we consider the cryptocurrency market as a real data application,given its remarkable suitability for the proposed method because of its volatile and unregulated nature.