{"id":40931,"date":"2025-11-13T18:00:00","date_gmt":"2025-11-13T10:00:00","guid":{"rendered":"https:\/\/www.tejwin.com\/?post_type=insight&#038;p=40931"},"modified":"2026-01-05T17:11:15","modified_gmt":"2026-01-05T09:11:15","slug":"tcri-watchdog-part-1","status":"publish","type":"insight","link":"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/","title":{"rendered":"How Major Announcements Drive Stock Price Volatility\uff1aEvent Study of the TCRI Watchdog &#8220;P&#8221; Type Event\uff0dPart 1"},"content":{"rendered":"\n<figure class=\"wp-block-image size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-1024x576.png\" alt=\"\" class=\"wp-image-40935\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-1024x576.png 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-300x169.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-150x84.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-768x432.png 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD-1536x864.png 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/The-Power-of-Material-Information-TCRI-WD.png 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_81 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69ebc424f3397\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"ez-toc-cssicon\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69ebc424f3397\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Introduction%EF%BC%9AFrom_Information_Disclosure_to_Market_Behavior\" >Introduction\uff1aFrom Information Disclosure to Market Behavior<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#TCRI_Watchdog%EF%BC%9ATransforming_Unstructured_Information_into_Quantifiable_Risk_Signals\" >TCRI Watchdog\uff1aTransforming Unstructured Information into Quantifiable Risk Signals&nbsp;&nbsp;<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Core_Features_of_TCRI_Watchdog\" >Core Features of TCRI Watchdog<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Research_Motivation_and_Methodology%EF%BC%9ACapturing_Real-Time_Market_Reactions\" >Research Motivation and Methodology\uff1aCapturing Real-Time Market Reactions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Methodology\" >Methodology<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Empirical_Findings_Negative_Events_Have_Far_Greater_Impact\" >Empirical Findings: Negative Events Have Far Greater Impact&nbsp;<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Linear_Relationship_Between_Event_Intensity_and_Market_Performance\" >Linear Relationship Between Event Intensity and Market Performance&nbsp;<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Pre-_and_Post-Announcement_Dynamics_The_Market_Moves_Ahead_of_News\" >Pre- and Post-Announcement Dynamics: The Market Moves Ahead of News<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Overall_Interpretation\" >Overall Interpretation&nbsp;<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part-1\/#Conclusion_What_Event_Intensity_Reveals_About_Market_Behavior\" >Conclusion: What Event Intensity Reveals About Market Behavior<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction%EF%BC%9AFrom_Information_Disclosure_to_Market_Behavior\"><\/span>Introduction\uff1aFrom Information Disclosure to Market Behavior<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"block-879665a9-8254-4bcc-9fba-f246cc9bc7e9\">In Taiwan stock market, structured data such as financial reports and stock prices are easily accessible. However, what truly drives short-term volatilit<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\">y are events. From company announcements and regulatory releases to media reports, <\/mark><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">every piece of information can sway investor sentiment and capital flows.<\/mark><\/strong> Traditional financial data, however, often fails to capture these real-time reactions, making it difficult for investors to determine which events are actually priced in by the market.&nbsp;<\/p>\n\n\n\n<p id=\"block-879665a9-8254-4bcc-9fba-f246cc9bc7e9\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"><strong>TCRI Watchdog (WD) <\/strong><\/mark>database was developed precisely to address this gap. TEJ transforms scattered announcements and news events into quantifiable credit risk signals, enabling investors to systematically grasp the market\u2019s true reactions to events.<\/p>\n\n\n\n<p id=\"block-879665a9-8254-4bcc-9fba-f246cc9bc7e9\">This article focuses o<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\">n <strong>material information events<\/strong> d<\/mark>isclosed via the <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Market Observation Post System (MOPS)<\/mark><\/strong>. Using the<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"> <strong>Event Study Methodology<\/strong><\/mark>, it analyzes how the market responds to events of varying intensity (from \u20133 to +3). The findings reveal that <strong>bad news tends to trigger sharper and longer-lasting price reactions than good news<\/strong>, and further demonstrate how TCRI Watchdog serves as a core <strong>alternative data tool<\/strong> for investment decision-making and risk monitoring.&nbsp;<\/p>\n\n\n\n<p class=\"has-background has-medium-font-size\" style=\"background-color:#ffe9ae\"><em><strong>\u27a1\ufe0f <a href=\"https:\/\/www.tejwin.com\/en\/news\/tcri-watchdog\/\" data-type=\"link\" data-id=\"https:\/\/www.tejwin.com\/en\/insight\/tej-point-in-time-audited-financial-database\/\">Get Detail about alternative data\uff0dTCRI Watchdog Database<\/a>.<\/strong><\/em><\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-9754109c-8d80-4751-bb26-fb417138bdbd\"><span class=\"ez-toc-section\" id=\"TCRI_Watchdog%EF%BC%9ATransforming_Unstructured_Information_into_Quantifiable_Risk_Signals\"><\/span>TCRI Watchdog\uff1aTransforming Unstructured Information into Quantifiable Risk Signals&nbsp;&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"block-68340029-cfec-41f9-9c3a-ab4e01c699e8\">In a market where information moves rapidly, investors need more than just the knowledge that an event occurred\u2014they need to quantify its market impact. <strong>TCRI Watchdog (WD)<\/strong> converts unstructured textual data\u2014such as company announcements, regulatory disclosures, and news\u2014into <strong>observable, comparable, and traceable event signals<\/strong> known as <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Event Intensity scores<\/mark><\/strong>.&nbsp;<\/p>\n\n\n\n<p>Each day, TCRI WD captures events involving all listed and OTC companies in Taiwan (including<strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\"> delisted firms<\/mark><\/strong>), from sources including:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>MOPS<\/strong>\uff1aMaterial information and official company announcements.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Regulatory agencies<\/strong>\uff1aAnnouncements from bodies such as the FSC, MOEA, and Fair Trade Commission.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Media and online NEWS<\/strong>\uff1aCovering mainstream financial and industrial news.<\/li>\n<\/ul>\n\n\n\n<p id=\"block-6ac01d26-cda0-41f4-9d75-ea466eeec76d\">Each event is reviewed and validated through both <strong>TEJ\u2019s analyst team<\/strong> and <strong>AI-driven modeling<\/strong>, and then assigned an <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">event intensity score from \u20133 to +3<\/mark><\/strong> based on its potential impact on corporate credit risk. Events are further categorized into <strong>5 dimensions<\/strong> and <strong>over 100 subtypes<\/strong>:&nbsp;<\/p>\n\n\n\n<p>Table1\uff1a <strong>5 dimension<\/strong> of TCRI Watchdog event<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-background\" style=\"background-color:#ffe9ae\"><thead><tr><th class=\"has-text-align-center\" data-align=\"center\"><strong>Code<\/strong>&nbsp;<\/th><th><strong>Event Type<\/strong>&nbsp;<\/th><th><strong>Description<\/strong>&nbsp;<\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>A<\/strong>&nbsp;<\/td><td>Accounting \/ Financial Reporting&nbsp;<\/td><td>Events related to accounting, financial disclosures, or restatements, reflecting financial transparency and stability.&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>I<\/strong>&nbsp;<\/td><td>Industry Prospects&nbsp;<\/td><td>Events tied to business operations, capacity, costs, R&amp;D, or fundraising, reflecting industrial trends and business momentum.&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>M<\/strong>&nbsp;<\/td><td>Management \/ Governance&nbsp;<\/td><td>Includes governance issues, director and executive changes, internal control failures, fraud, labor disputes, and cybersecurity incidents.&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>F<\/strong>&nbsp;<\/td><td>Market Transactions&nbsp;<\/td><td>Covers credit rating changes, stock price anomalies, capital market transactions, and listing status changes.&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>R<\/strong>&nbsp;<\/td><td>Crisis Events&nbsp;<\/td><td>Financial distress, defaults, delistings, or bankruptcies\u2014the most direct indicators of credit risk.&nbsp;<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>This structure allows investors to <strong>quantify the nature and direction of market events under a unified framework<\/strong>, enabling consistent comparisons\u2014whether monitoring individual stock risks or assessing overall market sentiment.&nbsp;<\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Core_Features_of_TCRI_Watchdog\"><\/span><strong>Core Features of TCRI Watchdog<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\ud83d\udcca <strong>Systemic Monitoring<\/strong> \u2013 An event-based daily monitoring framework suitable for portfolio surveillance and thematic screening.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\ud83d\udca1 <strong>Quantitative Consistency<\/strong> \u2013 Preserves complete announcement dates and versions to avoid <strong>look-ahead bias<\/strong> and includes delisted firms to remove <strong>survivorship bias<\/strong>.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\ud83e\udded <strong>Sentiment Signal<\/strong> \u2013 Event intensity functions as a <strong>sentiment factor<\/strong>, bridging the timeliness gap left by traditional financial statements.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\ud83d\udd0d <strong>Risk Integration<\/strong> \u2013 Event data can be incorporated into credit risk models and quantitative investment strategies, enhancing real-time analytical capability.&nbsp;<\/li>\n<\/ul>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Research_Motivation_and_Methodology%EF%BC%9ACapturing_Real-Time_Market_Reactions\"><\/span>Research Motivation and Methodology\uff1aCapturing Real-Time Market Reactions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"><strong>MOPS announcements<\/strong><\/mark> are the primary channel for Taiwans listed firms to disclose financial and operational updates. Whether it\u2019s a new investment, board change, bond issuance, or restated financial report, such events often trigger significant market responses.&nbsp;<\/p>\n\n\n\n<p>This study uses<strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"> TCRI Watchdog database<\/mark><\/strong>, analyzing over <strong>33,000 MOPS-based events<\/strong> from <strong>2018 to 2025<\/strong> to examine the relationship between event intensity and abnormal returns (AR), as well as the asymmetry in market reactions to positive and negative news.&nbsp;<\/p>\n\n\n\n<p>Scope and Parameters:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sample\uff1aTaiwan listed and OTC companies&nbsp;<\/li>\n\n\n\n<li>Source\uff1a\u201cP Source\u201d (MOPS announcements)<\/li>\n\n\n\n<li>Period\uff1aJan 1, 2018 \u2013 Aug 31, 2025&nbsp;<\/li>\n\n\n\n<li>Events\uff1a33,000 material announcements&nbsp;<\/li>\n\n\n\n<li>Categories\uff1aA, I, M, F, R&nbsp;<\/li>\n\n\n\n<li>Intensity Range\uff1a\u20133 to +3&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>Grouping events by intensity allows us to examine whether the market exhibits systematic reaction patterns\u2014such as <strong>pre-event drift, delayed reaction<\/strong>, or <strong>post-announcement adjustment<\/strong>\u2014depending on the nature of the information.<\/p>\n\n\n\n<p>Table2\uff1aDefinition of Event Intensity Groups&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-background has-fixed-layout\" style=\"background-color:#ffe9ae\"><thead><tr><th class=\"has-text-align-center\" data-align=\"center\"><strong>Group<\/strong>&nbsp;<\/th><th class=\"has-text-align-center\" data-align=\"center\">Event Intensity Condition&nbsp;<\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>negative<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>&lt;0<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>-1<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=-1<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>-2<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=-2<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>-3<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=-3<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>positive<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>&gt;0<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>1<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=1<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>2<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=2<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>3<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=3<\/strong>&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\"><strong>neutral<\/strong>&nbsp;<\/td><td class=\"has-text-align-center\" data-align=\"center\"><strong>=0<\/strong>&nbsp;<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Methodology\"><\/span><strong>Methodology<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>This study applies the Event Study Methodology to evaluate abnormal stock performance before and after the announcement date, relative to an expected normal return. The research settings are as follows:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Estimation Window<\/strong>: 250 trading days, using the Fama\u2013French Three-Factor Model to estimate normal returns.&nbsp;<\/li>\n\n\n\n<li><strong>Gap Days:<\/strong> 10 (to avoid overlap between estimation and event windows)<\/li>\n\n\n\n<li><strong>Event Window:<\/strong> (\u201310, +10) days, for calculating AR and CAR<\/li>\n\n\n\n<li><strong>Aggregated Measures:<\/strong> AAR and CAAR across all events<\/li>\n\n\n\n<li><strong>Statistical Tests:<\/strong> t-tests conducted on AAR and CAAR to determine significance<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Performance Analysis : <\/strong>This analysis evaluates the average direction and magnitude of market reactions across different event intensity groups. The primary indicators include:&nbsp;\n<ul class=\"wp-block-list\">\n<li>Mean AAR (%): Average daily AAR over the event window<\/li>\n\n\n\n<li>Final CAAR (%): Cumulative abnormal return at t+10<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Event Window Analysis\uff1a<\/strong>This analysis examines the structural patterns around event dates for each event intensity group. CAAR serves as the primary metric, supported by changes in daily AAR before and after the event. The goal is to evaluate market behavior across different phases\u2014pre-event, event day, and post-event\u2014as well as related strategic implications.&nbsp;\n<ul class=\"wp-block-list\">\n<li>Pre-event Ratio\uff1aCAAR(t-1) \/ CAAR(t+10) \u00d7 100%&nbsp;<\/li>\n\n\n\n<li>t=0 Ratio\uff1aAAR(t=0) \/ CAAR(t+10) \u00d7 100%&nbsp;<\/li>\n\n\n\n<li>Post-event Ratio\uff1a [CAAR(t+10) &#8211; CAAR(t=0)] \/ CAAR(t+10) \u00d7 100%&nbsp;<\/li>\n\n\n\n<li>Marginal Effect\uff1a [AAR(t=0) \/ AAR(t-1) &#8211; 1] \u00d7 100%&nbsp;<\/li>\n\n\n\n<li>Post-Event Return\uff08\uff1aCAAR(t+10) &#8211; CAAR(t=0)&nbsp;<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p class=\"has-background\" style=\"background-color:#ffe9ae\"><em>\ud83d\udccc&nbsp;You may intetesting\uff1a<\/em><a href=\"https:\/\/www.tejwin.com\/en\/insight\/discovering-investment-factors-through-point-in-time-audited-financial-database\/\">Discovering Investment Factors through PIT Audited Financial Database<\/a><\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Empirical_Findings_Negative_Events_Have_Far_Greater_Impact\"><\/span><strong>Empirical Findings: Negative Events Have Far Greater Impact<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The analysis shows a clear and asymmetric pattern: negative news leads to significantly larger and longer-lasting declines than the gains produced by positive news.<br><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Linear_Relationship_Between_Event_Intensity_and_Market_Performance\"><\/span><strong>Linear Relationship Between Event Intensity and Market Performance<\/strong>&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>As shown in Figure 4-1, most announcements are neutral (score 0) or mildly negative (\u20131), with \u20131 to \u20133 events accounting for roughly one-fourth of all samples. While the majority of information is normal, <strong>extreme events hold significant market insight<\/strong>.&nbsp;<\/p>\n\n\n\n<p><strong>Figure 1\uff1aEvent Distribution Chart<\/strong>&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img decoding=\"async\" width=\"1024\" height=\"600\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-1024x600.png\" alt=\"\" class=\"wp-image-41050\" style=\"width:572px;height:auto\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-1024x600.png 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-300x176.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-150x88.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-768x450.png 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-1536x900.png 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-1-2048x1200.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Further analysis shows a <strong>negative correlation between event intensity and returns<\/strong>, meaning the stronger the negative intensity, the sharper the price decline.&nbsp;<\/p>\n\n\n\n<p><strong>Table3<\/strong>\uff1a<strong>Detailed Statistical Results<\/strong>&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-background has-fixed-layout\" style=\"background-color:#ffe9ae\"><thead><tr><th class=\"has-text-align-center\" data-align=\"center\">Group&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Event Count&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Mean AAR (%)&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Final CAAR(%)&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Significance&nbsp;<\/th><\/tr><\/thead><tbody><tr><td class=\"has-text-align-center\" data-align=\"center\">-1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">6741&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.09%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.90%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">-2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1233&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.23%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-5.12%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">-3&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">340&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.54%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-11.40%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">3729&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.06%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.34%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">19&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.06%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.19%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">negative&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">8314&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.10%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-2.12%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">neutral&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">21594&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.00%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.05%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">&nbsp;<\/td><\/tr><tr><td class=\"has-text-align-center\" data-align=\"center\">positive&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">3748&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.06%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.34%&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">***&nbsp;<\/td><\/tr><\/tbody><\/table><figcaption class=\"wp-element-caption\"><em>Statistical significance indicators\uff1a*, **, and *** denote significance at the 10% (\u03b1 = 0.10), 5% (\u03b1 = 0.05), and 1% (\u03b1 = 0.01) levels, respectively.<\/em><\/figcaption><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Pre-_and_Post-Announcement_Dynamics_The_Market_Moves_Ahead_of_News\"><\/span><strong>Pre- and Post-Announcement Dynamics: The Market Moves Ahead of News<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Market behavior indicates that <strong>prices often react before the official announcement<\/strong>. In \u20133 (strongly negative) events, around <strong>56% of the total drop<\/strong> occurred before the disclosure date (t\u20131).&nbsp;<\/p>\n\n\n\n<p><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"><strong>Event-Day Reaction (t=0)<\/strong>\uff1a<br><\/mark>Score -3 events on the announcement day (t=0), abnormal returns (AAR) averaged \u20131.7%, signaling new negative information but slightly easing compared to the pre-event decline.<\/p>\n\n\n\n<p><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"><strong>Post-event Drift<\/strong>\uff1a<br><\/mark>Post-announcement drift persisted, with continued declines over the following 10 days\u2014an additional <strong>\u20133.35%<\/strong> for \u20133 events.&nbsp;<\/p>\n\n\n\n<p>Conversely, positive news(+1 and +2)&nbsp; often saw pre-event rallies followed by mild corrections after announcements, suggesting that the market anticipates good news but reverts afterward.&nbsp;<\/p>\n\n\n\n<p><strong>Table 4<\/strong>\uff1a<strong>Effect Distribution Table<\/strong>&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-background\" style=\"background-color:#ffe9ae\"><thead><tr><th><strong>Group<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>CAAR<\/strong><br><strong>(t-1)%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong><strong>CAAR<\/strong><\/strong><br><strong><strong>(t=0)%<\/strong>&nbsp;<\/strong><\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>CAAR<\/strong><br><strong>(t+10)%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>AAR<\/strong><br><strong>(t-1)%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>AAR<\/strong><br><strong>(t=0)%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>Pre%<\/strong> Pre-event Ratio&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\"><strong>t=0 Ratio<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Post-event Ratio <strong>%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Marginal Effect <strong>%<\/strong>&nbsp;<\/th><th class=\"has-text-align-right\" data-align=\"right\">Post-Event Return\uff05&nbsp;<\/th><\/tr><\/thead><tbody><tr><td>-1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.32&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.41&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.90&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.41&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.09&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">69.7&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">4.7&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">25.6&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-78.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.48&nbsp;<\/td><\/tr><tr><td>-2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-2.65&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-3.31&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-5.12&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.19&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.67&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">51.8&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">13.0&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">35.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-44.1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.80&nbsp;<\/td><\/tr><tr><td>-3&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-6.35&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-8.05&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-11.40&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-2.13&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.70&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">55.7&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">14.9&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">29.4&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-20.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-3.35&nbsp;<\/td><\/tr><tr><td>1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.53&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.63&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.34&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.89&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.10&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">114.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">7.4&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-21.6&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-88.8&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.29&nbsp;<\/td><\/tr><tr><td>2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">3.35&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">4.06&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.19&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">2.75&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.71&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">281.9&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">60.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-242.1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-74.0&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-2.87&nbsp;<\/td><\/tr><tr><td>negative&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.43&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-1.65&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-2.12&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.57&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.21&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">67.5&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">10.1&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">22.4&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-62.3&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.48&nbsp;<\/td><\/tr><tr><td>neutral&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.30&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.33&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.05&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.21&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.02&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">555.8&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">42.9&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-498.7&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-89.0&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.27&nbsp;<\/td><\/tr><tr><td>positive&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.53&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.63&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">1.34&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.89&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">0.11&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">113.5&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">7.8&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-21.4&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-88.2&nbsp;<\/td><td class=\"has-text-align-right\" data-align=\"right\">-0.29&nbsp;<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><strong>Figure 2<\/strong>\uff1a<strong>Group Comparison Chart<\/strong>&nbsp;<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"991\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-1024x991.png\" alt=\"\" class=\"wp-image-41067\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-1024x991.png 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-300x290.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-150x145.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-768x743.png 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-1536x1486.png 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/2511_WD_4-2-2048x1982.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Overall_Interpretation\"><\/span>Overall Interpretation&nbsp;<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Negative news \u2192 Although the market tends to react ahead of the announcement, the impact lasts longer, and the downward trend deepens progressively.&nbsp;<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Positive news \u2192 Markets often price in the good news beforehand, but subsequently correct after the announcement.&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>These findings clearly illustrate the behavioral characteristics of Taiwan\u2019s equity market: investors respond to bad news more quickly and persistently, while reactions to good news are more emotional and short-lived.&nbsp;<\/p>\n\n\n\n<p>This asymmetry highlights the value of TCRI Watchdog\u2019s event intensity data\u2014not only does it reveal the surface-level content of announcements, but it also quantifies how quickly and in what structure the market absorbs information. This enables investors to detect potential risks earlier or leverage delayed reactions to design more precise trading strategies.&nbsp;<\/p>\n\n\n\n<p><em>\ud83d\udccc&nbsp;You may intetesting\uff1a<\/em><a href=\"https:\/\/www.tejwin.com\/en\/insight\/discovering-investment-factors-through-point-in-time-audited-financial-database\/\">Discovering Investment Factors through PIT Audited Financial Database<\/a><\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"block-4b5de2c8-3387-4286-8175-557e2ae137ee\"><span class=\"ez-toc-section\" id=\"Conclusion_What_Event_Intensity_Reveals_About_Market_Behavior\"><\/span><strong>Conclusion: What Event Intensity Reveals About Market Behavior<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p id=\"block-a3601df1-9911-4478-a3ff-d220f358d892\">The first part of our analysis highlights a clear and asymmetrical pattern in Taiwan\u2019s equity market: negative events carry stronger and more persistent impacts than positive ones, and a significant portion of this reaction occurs even before the announcement becomes public. By quantifying these dynamics through TCRI Watchdog\u2019s Event Intensity framework, investors gain a more objective and timely understanding of how information is absorbed and priced by the market.<\/p>\n\n\n\n<p>This allows market participants to identify risks earlier, monitor behavioral signals more effectively, and design strategies that account for both pre-event movements and post-event drift.<\/p>\n\n\n\n<p id=\"block-a3601df1-9911-4478-a3ff-d220f358d892\">To deepen this understanding, the next part of our study classifies announcement events into five major categories. By examining how each category influences stock prices differently, investors can more precisely capture the market\u2019s reaction structure and better distinguish which types of information truly drive risk and return.<\/p>\n\n\n\n<p class=\"has-background has-medium-font-size\" style=\"background-color:#ffe9ae\">\ud83d\udc49 <strong><a href=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part2\/\" data-type=\"link\" data-id=\"https:\/\/www.tejwin.com\/en\/insight\/tcri-watchdog-part2\/\">Continue to Part 2 \u2014 How the 5 Event Categories Shape Market Reactions<\/a><\/strong><\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-wp-embed is-provider-tej wp-block-embed-tej\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"3Y1VanufJ7\"><a href=\"https:\/\/www.tejwin.com\/en\/news\/tcri-watchdog\/\">TCRI\u2122 Watchdog<\/a><\/blockquote><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; visibility: hidden;\" title=\"&#8220;TCRI\u2122 Watchdog&#8221; &#8212; TEJ\" src=\"https:\/\/www.tejwin.com\/en\/news\/tcri-watchdog\/embed\/#?secret=ZasynhFn5M#?secret=3Y1VanufJ7\" data-secret=\"3Y1VanufJ7\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Discover how TCRI Watchdog quantifies material announcements and reveals the asymmetric market impact of event intensity. Learn why negative events drive deeper, longer price reactions and how investors can use event-based signals to enhance risk monitoring and strategy design.<br \/>\nWe find that higher-ranked portfolios deliver significant short-term excess returns, while predictive power weakens over longer horizons. The results highlight the practical value of Point-in-Time financial data for quantitative factor investing and underscore its role in building replicable, data-driven investment strategies.<\/p>\n","protected":false},"featured_media":40935,"template":"","tags":[3264,3536,3505,3476],"insight-category":[690],"class_list":["post-40931","insight","type-insight","status-publish","has-post-thumbnail","hentry","tag-alternative-data","tag-eventstudy","tag-point-in-time-2","tag-tcri-watchdog","insight-category-data-analysis"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/40931","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight"}],"about":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/types\/insight"}],"version-history":[{"count":23,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/40931\/revisions"}],"predecessor-version":[{"id":42760,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/40931\/revisions\/42760"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/media\/40935"}],"wp:attachment":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/media?parent=40931"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/tags?post=40931"},{"taxonomy":"insight-category","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight-category?post=40931"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}