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By doing so, the number of new parameters to be estimated at each regime is drastically reduced and the break dynamics becomes easier to be interpreted. The Sparse CP\u2010VAR model disentangles the dynamics of the mean parameters and the covariance matrix. The former uses CP dynamics with shrinkage prior distributions, while the latter is driven by an infinite hidden Markov framework. An extensive simulation study is carried out to compare our approach with existing ones. We provide applications to financial and macroeconomic systems. It turns out that many off\u2010diagonal VAR parameters are zero for the entire sample period and that most break activity is in the covariance matrix. We show that this has important consequences for portfolio optimization, in particular when future instabilities are included in the predictive densities. Forecasting\u2010wise, the Sparse CP\u2010VAR model compares favorably to several time\u2010varying parameter models in terms of density and point forecast metrics.<\/jats:p>","DOI":"10.1002\/jae.2844","type":"journal-article","created":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T09:51:45Z","timestamp":1625824305000},"page":"703-727","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Sparse change\u2010point VAR models"],"prefix":"10.1002","volume":"36","author":[{"given":"Arnaud","family":"Dufays","sequence":"first","affiliation":[{"name":"EDHEC Business School  Lille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuo","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Econometrics &amp; Business Statistics Monash University  Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeroen V.K.","family":"Rombouts","sequence":"additional","affiliation":[{"name":"ESSEC Business School  Cergy France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Economics University of Melbourne  Victoria Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,8,19]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/jae.2555"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/0022-1082.00205"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/07350015.2015.1123636"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/jae.2387"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2014.960967"},{"key":"e_1_2_9_7_1","first-page":"14","article-title":"Vector autoregressions with parsimoniously time varying parameters and an application to monetary policy","author":"Callot L.","year":"2015","journal-title":"Tinbergen Institute Discussion Paper"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/rfs\/hhm055"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2019.04.024"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asq017"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2013.05.003"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2013.866566"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-4076(97)00115-2"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1093\/jjfinec\/nbs004"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/jae.1127"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jfineco.2012.04.003"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/07474938.2018.1454366"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jeconom.2019.10.008"},{"key":"e_1_2_9_19_1","doi-asserted-by":"crossref","unstructured":"Farmer L. 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