{"id":1986,"date":"2024-06-26T09:23:01","date_gmt":"2024-06-26T01:23:01","guid":{"rendered":"\/math\/?post_type=tkuisotope&#038;p=1986"},"modified":"2024-06-26T09:23:01","modified_gmt":"2024-06-26T01:23:01","slug":"113-3-20-%e5%8f%b8%e9%a6%ac-%e5%bf%b5%e9%ba%9f-%e6%95%99%e6%8e%88%e6%97%a5%e6%9c%ac%e6%9d%b1%e4%ba%ac%e7%90%86%e7%a7%91%e5%a4%a7%e5%ad%b8","status":"publish","type":"tkuisotope","link":"\/math\/?tkuisotope=113-3-20-%e5%8f%b8%e9%a6%ac-%e5%bf%b5%e9%ba%9f-%e6%95%99%e6%8e%88%e6%97%a5%e6%9c%ac%e6%9d%b1%e4%ba%ac%e7%90%86%e7%a7%91%e5%a4%a7%e5%ad%b8","title":{"rendered":"113\/3\/20 \u53f8\u99ac \u5ff5\u9e9f \u6559\u6388(\u65e5\u672c\u6771\u4eac\u7406\u79d1\u5927\u5b78)"},"content":{"rendered":"<p><strong>\u984c \u00a0\u76ee<\/strong><strong>\uff1a<\/strong><strong>Spot covariance estimation with synchronous high-frequency finance data<\/strong><\/p>\n<p>\u65e5\u00a0 \u671f\uff1a113\u5e742\u670820\u65e5\uff08\u661f\u671f\u4e8c\uff09<\/p>\n<p><strong>\u6642\u00a0 \u9593\uff1a\u4e0b\u534814:10\u958b\u59cb<\/strong><\/p>\n<p><strong>\u5730\u00a0 \u9ede\uff1a\u79d1\u5b78\u9928S433<\/strong><strong>\u00a0<\/strong><\/p>\n<p><strong>\u6458\u8981<\/strong><strong>Abstract: <\/strong><\/p>\n<p><strong>Empirical studies have pointed out the importance of considering different temporal variations in correlations between asset prices. Currently, high-frequency profiles sampled asynchronously across different assets have mainly applied for integrated covariance estimation but less so for spot covariance estimation. Based on the seminal works of Malliavin and Mancino [1,2] in conjunction with the principle component analysis approach, \u00a0in this talk, we try to propose a novel spot covariance estimation with synchronous high-frequency finance data. We will point out which kind of high-frequency data we are interested in and briefly explain why we apply the Malliavin-Mancino method to these data.<\/strong><strong><br \/>\nReferences<br \/>\n[1] P. Malliavin and M. E. Mancino. Fourier series method for measurement of multivariate volatilities. Finance Stoch., 6(1):49\u201361, 2002.<br \/>\n[2] P. Malliavin and M. E. Mancino. A Fourier transform method for nonparametric estimation of multivariate volatility. Ann. Statist., 37(4):1983\u20132010, 2009.<\/strong><\/p>\n<p><strong>\u00a0<\/strong><strong>\u5099 \u00a0\u8a3b\uff1a<\/strong><strong>\u672c\u696d\u52d9\u8207\u806f\u5408\u570b\u6c38\u7e8c\u767c\u5c55\u76ee\u6a19SDG4\u512a\u8cea\u6559\u80b2\u9023\u7d50<\/strong><\/p>\n<p><strong>ESG+AI=<\/strong><strong>\u221e\u00a0 AI+SDGs=\u221e<\/strong><\/p>\n","protected":false},"template":"","meta":[],"categories":[9],"tags":[],"featured_image_urls":{"full":"","thumbnail":"","medium":"","medium_large":"","large":"","1536x1536":"","2048x2048":""},"post_excerpt_stackable":"<p>\u984c \u00a0\u76ee\uff1aSpot covariance estimation with synchronous high-frequency finance data \u65e5\u00a0 \u671f\uff1a113\u5e742\u670820\u65e5\uff08\u661f\u671f\u4e8c\uff09 \u6642\u00a0 \u9593\uff1a\u4e0b\u534814:10\u958b\u59cb \u5730\u00a0 \u9ede\uff1a\u79d1\u5b78\u9928S433\u00a0 \u6458\u8981Abstract: Empirical studies have pointed out the importance of considering different temporal variations in correlations between asset prices. Currently, high-frequency profiles sampled asynchronously across different assets have mainly applied for integrated covariance estimation but less so for spot covariance estimation. Based on the seminal works of Malliavin and Mancino [1,2] in conjunction with the principle component analysis approach, \u00a0in this talk, we try to propose a novel spot covariance estimation with synchronous high-frequency finance data. We will point out which kind of high-frequency data we&hellip;<\/p>\n","category_list":"<a href=\"\/math\/?cat=9\" rel=\"category\">News<\/a>","author_info":{"name":"","url":""},"comments_num":"0 comments","acf":[],"_links":{"self":[{"href":"\/math\/index.php?rest_route=\/wp\/v2\/tkuisotope\/1986"}],"collection":[{"href":"\/math\/index.php?rest_route=\/wp\/v2\/tkuisotope"}],"about":[{"href":"\/math\/index.php?rest_route=\/wp\/v2\/types\/tkuisotope"}],"wp:attachment":[{"href":"\/math\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1986"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"\/math\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1986"},{"taxonomy":"post_tag","embeddable":true,"href":"\/math\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1986"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}