{"id":7237,"date":"2025-12-09T16:19:54","date_gmt":"2025-12-09T22:19:54","guid":{"rendered":"https:\/\/librarytestdev.wpenginepowered.com\/?post_type=doc&#038;p=7237"},"modified":"2025-12-16T19:03:23","modified_gmt":"2025-12-17T01:03:23","slug":"session-dominance","status":"publish","type":"doc","link":"https:\/\/library-staging.tradingtechnologies.com\/tt-trade-surveillance\/core-models\/miscellaneous-models\/session-dominance\/","title":{"rendered":"Session Dominance"},"content":{"rendered":"\n<p>Session dominance is when a user trades a high percentage of the total volume for an instrument over an entire trading session. The Session Dominance Model in TT Trade Surveillance analyzes and scores clusters that may indicate when a single trader is dominating the filled volume of an instrument for the entire session.<\/p>\n\n\n\n<h2>Scoring methodology<\/h2>\n\n\n  <p>TT Trade Surveillance computes a <a href=\"ovw-how-tt-score-works.html#cluster\">cluster<\/a> score based on how similar the activity in the cluster matches trading activity that has drawn regulatory attention in other situations.<\/p>\n\n<p>Higher scores indicate the trading activity within a cluster is more likely to risk regulatory concern. A company&#8217;s risk monitors can use these scores to prioritize resources for investing which users&#8217; trading activity poses the most regulatory risk.<\/p>\n\n\n<h2>Session Dominance score interpretation<\/h2>\n<p>Each cluster is assigned a risk score on a sliding scale between 0-100. This score represents the probability that session dominance occurred during the duration of the cluster&#8217;s trading activity.<\/p>\n\n<p>Based on TT Trade Surveillance best practices, clusters that score over 75 are deemed to be \u201chigh risk\u201d and should be the primary focus of users during their compliance reviews.<\/p>\n\n\n\n\n<h2>Session Dominance scorecard metrics<\/h2>\n<p>The Scorecard Metrics section measures the following statistics related to session dominance:<\/p>\n<ul>\n            <li><b>Session Vol<\/b> \u2014 Total traded volume for the instrument during the entire session.<\/li>\n\n            <li><b>Trader Buy Filled Vol<\/b> \u2014 Total Buy orders filled.<\/li>\n            <li><b>Trader Sell Filled Vol<\/b> \u2014 Total Sell orders filled.<\/li>\n            <li><b>Trader Session Fill Vol<\/b> \u2014 Total Buy and Sell orders filled for the session.<\/li>\n         <li><b>Trader Vs Session<\/b> \u2014 Ratio of the trader&#8217;s session fill volume and total traded volume.<\/li>\n<li><b>Trader Buy Vs Total Fill Vol<\/b> \u2014 Percentage of total session volume that are Buy orders.\n<\/li><li><b>Trader Sell Vs Total Fill Vol<\/b> \u2014 Percentage of total session volume that are Sell orders.\n  <\/li><li><b>Min Session Vol<\/b> \u2014 Minimum traded volume for the session.\n  <\/li><li><b>Max Session Vol<\/b> \u2014 Minimum traded volume for the session.\n  <\/li><li><b>LTP Session<\/b> \u2014 Session Last traded price for the instrument.\n  <\/li><li><b>OpenPrice Session<\/b> \u2014 Session opening price for the instrument.\n  <\/li><li><b>ClosePrice Previous Session<\/b> \u2014 Previous closing price for the instrument.<\/li>\n<\/ul>\n\n\n\n<h2>Identifying Session Dominance<\/h2>\n\n<p>Use the <a href=\"cv-cluster-view-cluster-scorecard.html\">Cluster Scorecard<\/a> to get a closer look at the activity that triggered the session dominance score. The audit trail at the bottom of the scorecard can provide an indication of a trader dominating the volume traded for an instrument.<\/p>\n\n\n  <p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/library-staging.tradingtechnologies.com\/wp-content\/uploads\/2025\/12\/dom-session-scorecard.png\" alt=\"\"><\/p>\n\n\n  <p>In this example:<\/p>\n  <ol>\n    <li>\n      The trader added volume on the Sell side to create the appearance of Sell-side pressure.\n    <\/li>\n    <li>\n      The same trader submits Buy orders, which immediately fill.<\/li>\n    <\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Session dominance is when a user trades a high percentage of the total volume for an instrument over an entire [&hellip;]<\/p>\n","protected":false},"author":2,"template":"","meta":{"_acf_changed":false,"footnotes":""},"docs-category":[957],"class_list":["post-7237","doc","type-doc","status-publish","hentry","docs-category-miscellaneous-models"],"acf":[],"_links":{"self":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc\/7237","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc"}],"about":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/types\/doc"}],"author":[{"embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/users\/2"}],"version-history":[{"count":0,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/doc\/7237\/revisions"}],"wp:attachment":[{"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/media?parent=7237"}],"wp:term":[{"taxonomy":"docs-category","embeddable":true,"href":"https:\/\/library-staging.tradingtechnologies.com\/ja\/wp-json\/wp\/v2\/docs-category?post=7237"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}