{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:44:14Z","timestamp":1786977854795,"version":"build-2736575974"},"reference-count":42,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2018,7,12]],"date-time":"2018-07-12T00:00:00Z","timestamp":1531353600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100006280","name":"Ministerio de Ciencia y Tecnolog\u00eda","doi-asserted-by":"publisher","award":["MTM2012-37195"],"award-info":[{"award-number":["MTM2012-37195"]}],"id":[{"id":"10.13039\/501100006280","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2018,11]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>We introduce LASSO\u2010type regularization for large\u2010dimensional realized covariance estimators of log\u2010prices. The procedure consists of shrinking the off\u2010diagonal entries of the inverse realized covariance matrix towards zero. This technique produces covariance estimators that are positive definite and with a sparse inverse. We name the estimator realized network, since estimating a sparse inverse realized covariance matrix is equivalent to detecting the partial correlation network structure of the daily log\u2010prices. The large sample consistency and selection properties of the estimator are established. 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