{"id":664,"date":"2013-06-04T13:00:33","date_gmt":"2013-06-04T12:00:33","guid":{"rendered":"http:\/\/mathfinance.sns.it\/new_site\/?p=664"},"modified":"2015-07-17T13:59:31","modified_gmt":"2015-07-17T12:59:31","slug":"ying-chen-filtering-asynchronous-high-frequency-data","status":"publish","type":"post","link":"http:\/\/mathfinance.sns.it\/index.php\/ying-chen-filtering-asynchronous-high-frequency-data\/","title":{"rendered":"Ying Chen, \u201cFiltering Asynchronous High Frequency Data\u201d"},"content":{"rendered":"<p style=\"text-align: center;\"><span lang=\"IT\">Tuesday\u00a0June\u00a04<span style=\"font-size: 12px; line-height: 0px;\">\u00a0<\/span>\u00a02013<\/span><br \/>\n13.00<br \/>\nScuola Normale Superiore<br \/>\nAula\u00a0Bianchi<\/p>\n<p style=\"text-align: center;\"><strong>Ying Chen<br \/>\n<\/strong>Department of Statistics &amp; Applied Probability &#8211;\u00a0National University of Singapore<\/p>\n<p style=\"text-align: center;\" align=\"center\"><strong><span lang=\"EN-GB\">Abstract<br \/>\n<\/span><\/strong><\/p>\n<p style=\"text-align: center;\">We develop a synchronizing technique for irregularly spaced and asynchronous high frequency data. The technique learns from the dependence structure of raw data and iteratively recovers the unobserved values of the synchronous series at high sampling frequency.<br \/>\nThe numerical results illustrate the performance of the proposed technique and compared to the conventional techniques &#8212; Previous Tick technique and Refresh Time technique. The proposed technique provides good performance in terms of accuracy and feature.<br \/>\nMoreover, a realized covariance estimator is constructed by incorporating the synchronized technique. We compare the feature of the estimator with several alternative estimators.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tuesday\u00a0June\u00a04\u00a0\u00a02013 13.00 Scuola Normale Superiore Aula\u00a0Bianchi Ying Chen Department of Statistics &amp; Applied Probability &#8211;\u00a0National University of Singapore Abstract We develop a synchronizing technique for irregularly spaced and asynchronous high frequency data. The technique learns from the dependence structure of raw data and iteratively recovers the unobserved values of the synchronous series at high sampling [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[13],"tags":[],"_links":{"self":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/664"}],"collection":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/comments?post=664"}],"version-history":[{"count":1,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/664\/revisions"}],"predecessor-version":[{"id":666,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/664\/revisions\/666"}],"wp:attachment":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/media?parent=664"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/categories?post=664"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/tags?post=664"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}