{"id":3355,"date":"2026-08-26T07:06:48","date_gmt":"2026-08-26T07:06:48","guid":{"rendered":"https:\/\/www.tejwin.com\/en\/product-services\/uncategorized\/\/"},"modified":"2026-10-02T09:26:43","modified_gmt":"2026-10-02T09:26:43","slug":"tcri-watchdog-2","status":"publish","type":"product","link":"https:\/\/www.tejwin.com\/en\/product-services\/alternative-data\/tcri-watchdog-2\/","title":{"rendered":"TCRI\u2122 Watchdog"},"content":{"rendered":"<h2 class=\"wp-block-heading\">Eliminating\u00a0Credit Noise with Alternative Data<\/h2>\n<p class=\"has-text-align-left wp-block-paragraph\">In the Taiwan stock market, while structured data such as financial reports and price information are complete and highly real-time, short-term stock price fluctuations are often driven by \u201cevents.\u201d From announcements and regulatory news to media reports, this unstructured information rapidly influences\u00a0investor\u2019s\u00a0expectations and capital flows, yet it\u00a0remains\u00a0difficult to capture effectively using traditional quantitative methods.<\/p>\n<p class=\"has-text-align-left wp-block-paragraph\">Identifying\u00a0influential signals from a vast array of events and\u00a0extracting actionable signals from events and\u00a0converting\u00a0them\u00a0into\u00a0backtestable\u00a0investment factors\u00a0has always been a key threshold for quantitative research.\u00a0TEJ developed the\u00a0<strong>TCRI Watchdog (WD)<\/strong>\u00a0database to\u00a0transform\u00a0unstructured\u00a0information\u00a0into\u00a0structured alternative\u00a0data\u00a0through a systematic classification and scoring mechanism,\u00a0assisting\u00a0researchers in effectively capturing alpha and strengthening forward-looking risk judgment.<\/p>\n<h2 class=\"wp-block-heading has-text-align-left\"><span id=\"TCRI_Watchdog_Structuring_Unstructured_Information_into_Alternative_Data\" class=\"ez-toc-section\"><\/span>TCRI Watchdog:\u00a0Structuring Unstructured Information into\u00a0Alternative Data<\/h2>\n<p class=\"wp-block-paragraph\"><strong>TCRI Watchdog (WD)<\/strong>\u00a0processes\u00a0unstructured information\u00a0(such as news and announcements)\u00a0into\u00a0a\u00a0structured\u00a0alternative\u00a0dataset, featuring\u00a0consistent and comparable\u00a0<strong>Event Scores (-3 to +3)<\/strong>\u00a0based on their impact on corporate credit risk. Through systematic event definitions and automated quantitative\u00a0processes,it\u00a0converts raw narratives into quantifiable event signals suitable for\u00a0backtesting\u00a0and alpha generation.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<div aria-hidden=\"true\"><span style=\"font-size: 18pt;color: #333399\">\u2b50<strong>Download our <em>WD Alternative Data Report<\/em> : <a style=\"color: #333399\" href=\"https:\/\/www.tejwin.com\/?wpforms_form_preview=3472\">click me!<\/a>\u00a0<\/strong><\/span><\/div>\n<h3 class=\"wp-block-heading\"><span id=\"Data_Scope\" class=\"ez-toc-section\"><\/span>Data Scope:<\/h3>\n<p class=\"wp-block-paragraph\">Includes historical records\u00a0from 2019\u00a0\u00a0for all listed and OTC companies in the Taiwan market, including delisted companies.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"Data_Sources\" class=\"ez-toc-section\"><\/span>Data Sources:<\/h3>\n<p class=\"wp-block-paragraph\">Data is integrated from three major sources:<\/p>\n<ul class=\"wp-block-list\">\n<li>Material information from the Market Observation Post System (MOPS).<\/li>\n<\/ul>\n<ul class=\"wp-block-list\">\n<li>Official sanctions from regulatory agencies such as the Financial Supervisory Commission (FSC) and the Ministry of Economic Affairs.<\/li>\n<\/ul>\n<ul class=\"wp-block-list\">\n<li>Mainstream financial media reports.<\/li>\n<\/ul>\n<h3 class=\"wp-block-heading\"><span id=\"Event_Intensity\" class=\"ez-toc-section\"><\/span>Event Intensity:<\/h3>\n<p class=\"wp-block-paragraph\">Event scores range from\u00a0<strong>-3 to +3<\/strong>. Negative values\u00a0represent\u00a0potential deterioration in credit risk, while positive values\u00a0represent\u00a0risk improvement or operational benefits. The larger the absolute value, the more significant the event\u2019s impact on corporate risk.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"Event_Classification\" class=\"ez-toc-section\"><\/span>Event Classification:<\/h3>\n<p class=\"has-text-align-left wp-block-paragraph\">All events are categorized into the following\u00a0<strong><mark class=\"has-inline-color has-vivid-cyan-blue-color\">5 dimensions<\/mark><\/strong>\u00a0and\u00a0<mark class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>over\u00a0100 subcategories<\/strong><\/mark>, constructing a quantifiable credit event framework. Each event is classified through collaboration between analysts and AI models based on its impact on corporate operations and credit risk:<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<p class=\"wp-block-paragraph\"><strong>Table 1: 5 Dimensions of TCRI Watchdog Events\u00a0\u00a0<\/strong><\/p>\n<figure class=\"wp-block-table\">\n<table>\n<tbody>\n<tr>\n<td><strong>Code<\/strong><\/td>\n<td><strong>Event Category<\/strong><\/td>\n<td><strong>Meaning<\/strong><\/td>\n<td><strong>Sub-classification Examples<\/strong><\/td>\n<\/tr>\n<tr>\n<td><strong>A\u00a0<\/strong><\/td>\n<td><strong>Accounting<\/strong><\/td>\n<td>Events related to financial reporting, accounting treatments, and disclosure practices, reflecting financial transparency and stability.<\/td>\n<td>Alleged Fraud of financial\u00a0report,\u00a0\u00a0Restatement\u00a0of financial report<\/p>\n<p>Total\uff1a13 subcategories<\/td>\n<\/tr>\n<tr>\n<td><strong>I\u00a0<\/strong><\/td>\n<td><strong>Industry<\/strong><\/td>\n<td>Events related to operating environment, capacity, costs, R&amp;D progress, and financing, revealing operating momentum and industry trends.<\/td>\n<td>Issues of suppliers or agency,\u00a0The loss of important talents<\/p>\n<p>Total\uff1a27 subcategories<\/td>\n<\/tr>\n<tr>\n<td><strong>M\u00a0<\/strong><\/td>\n<td><strong>Management<\/strong><\/td>\n<td>Events involving corporate governance,\u00a0board\u00a0and executive changes, internal or external fraud, labor disputes, information security, and internal control deficiencies, reflecting governance and management stability.<\/td>\n<td>Suspicion of embezzlement or hollowing out of assets,\u00a0Executive changes<\/p>\n<p>Total\uff1a41 subcategories<\/td>\n<\/tr>\n<tr>\n<td><strong>F\u00a0<\/strong><\/td>\n<td><strong>Market Trading<\/strong><\/td>\n<td>Events related to capital market trading, rating changes, abnormal price movements, and listing status, reflecting market\u00a0perceptions\u00a0of credit and liquidity.<\/td>\n<td>Stock price manipulation,\u00a0insider trading,\u00a0Cross Shareholding<\/p>\n<p>Total\uff1a12 subcategories<\/td>\n<\/tr>\n<tr>\n<td><strong>R\u00a0<\/strong><\/td>\n<td><strong>Crsis<\/strong><\/td>\n<td>Events involving financial distress, default, delisting, or restructuring,\u00a0representing\u00a0the\u00a0most direct signals of credit risk.<\/td>\n<td>Rumored\u00a0financial crisis,\u00a0Bankruptcy<\/p>\n<p>Total\uff1a22 subcategories<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<p class=\"wp-block-paragraph\">This framework\u00a0establishes\u00a0a unified standard, allowing investors to efficiently evaluate and compare various market events, ranging from individual stock risk monitoring to overall market risk sentiment assessment.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<h3 class=\"wp-block-heading\"><span id=\"Data_Transmission\" class=\"ez-toc-section\"><\/span><strong>Data Transmission:<\/strong><\/h3>\n<p class=\"wp-block-paragraph\">Data is delivered via\u00a0API\u00a0or\u00a0FTP\u00a0for automated transmission.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<p class=\"wp-block-paragraph\"><strong>Figure1: TCRI WD data sample\u00a0<\/strong><\/p>\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-44757\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/image-820.png\" alt=\"\" width=\"831\" height=\"474\" \/><\/figure>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<p class=\"wp-block-paragraph\">As shown in the data sample, WD precisely defines fragmented market announcements as structured records featuring\u00a0<strong>Event<\/strong><strong>\u00a0<\/strong><strong>date<\/strong>,\u00a0<strong>Event Score<\/strong>, and\u00a0<strong>Event classification<\/strong>.<\/p>\n<p class=\"wp-block-paragraph\">According to Figure 2, the system\u00a0generates an average of over\u00a0<mark class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>3,500 structured credit\u00a0signals\u00a0monthly<\/strong><\/mark>. This steady,\u00a0<strong>high-density data stream<\/strong>\u00a0is ideal for\u00a0<strong>quantitative modeling<\/strong>\u00a0and\u00a0<strong>stress testing<\/strong>\u00a0due to its frequency and depth.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<p class=\"wp-block-paragraph\"><strong>Figure 2: Monthly\u00a0distribution\u00a0of TCRI Watchdog events\u00a0<\/strong><\/p>\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-44762\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/image-822.png\" alt=\"\" width=\"829\" height=\"411\" \/><\/figure>\n<p>&nbsp;<\/p>\n<p><strong>Source\uff1aTEJ\u00a0TCRI WD database\u00a0<\/strong><\/p>\n<p><strong>Period\uff1aJan\u00a02023~ Dec 2025\u00a0<\/strong><\/p>\n<p>&nbsp;<\/p>\n<h2 class=\"wp-block-heading\"><span id=\"3_Reasons_Why_Your_Strategy_Needs_TCRI_WD\" class=\"ez-toc-section\"><\/span>3 Reasons\u00a0Why Your Strategy Needs TCRI WD?<\/h2>\n<p class=\"wp-block-paragraph\">The failure of quantitative strategies often stems from underlying data\u00a0containing\u00a0too much noise unrelated to credit risk, causing true early-warning signals to be diluted or obscured. TCRI Watchdog (WD)\u00a0assists\u00a0research teams in skipping tedious data cleaning to focus on alpha mining, while enabling investment teams to integrate event risks into decision frameworks for better precision and efficiency.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"Unified_Event_Intensity_Grading\" class=\"ez-toc-section\"><\/span>Unified Event Intensity Grading:<\/h3>\n<p class=\"wp-block-paragraph\">\u00a0Provides a standardized scoring system from -3 to +3 for diverse unstructured events. This solves the difficulty of cross-sectional comparisons caused by a lack of quantitative benchmarks in original announcements.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"Qualitative_to_Quantitative_Information\" class=\"ez-toc-section\"><\/span>Qualitative to Quantitative Information:<\/h3>\n<p class=\"wp-block-paragraph\">\u00a0Filters core information relevant to corporate operations through automated algorithms and dual review by the TEJ professional team.\u00a0Unlike generic AI tools, WD strictly removes emotional noise, significantly reducing manual labeling time for analysts.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"Point-in-Time_PIT_Data_Structure\" class=\"ez-toc-section\"><\/span>Point-in-Time (PIT) Data Structure:<\/h3>\n<p class=\"wp-block-paragraph\">Strictly follows the PIT architecture, recording the precise timestamp of every event disclosure and including historical data of delisted companies. This\u00a0eliminates\u00a0<strong>look-ahead bias<\/strong>\u00a0and\u00a0<strong>survivor bias<\/strong>\u00a0in\u00a0backtesting, ensuring model authenticity.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\n<h2 class=\"wp-block-heading\"><span id=\"Empirical_Research_Leading_Market_Warning_Signals\" class=\"ez-toc-section\"><\/span>Empirical Research: Leading Market Warning Signals<\/h2>\n<p class=\"wp-block-paragraph\">According to TEJ\u2019s ten-year\u00a0backtest, market reactions to non-financial information depend on the event\u2019s\u00a0<strong>category<\/strong>\u00a0and\u00a0<strong>intensity<\/strong>\u00a0rather than news volume.<\/p>\n<h3 class=\"wp-block-heading\"><span id=\"News_Events_Category_N\" class=\"ez-toc-section\"><\/span>1. News Events (Category N):<\/h3>\n<p class=\"wp-block-paragraph\">Empirical evidence shows a significant \u201cadvance reaction\u201d to strongly negative news (e.g., -3 points). Stock prices often show abnormal declines before the news is officially reported, with the downward trend expanding further after disclosure.<\/p>\n<p><span style=\"font-size: 14pt\"><a href=\"https:\/\/www.tejwin.com\/en\/insights\/from-news-to-markets-investment-signals-from-media-coverage-part-ii-an-empirical-analysis-of-tcri-watchdog-n-news-media-events\/\">\ud83d\udc49<strong>Category\u00a0\u201cN\u201d\u00a0full version:\u00a0TCRI Watchdog \u201cN News Media\u201d Events Part1<\/strong><\/a><\/span><\/p>\n<div class=\"wp-block-buttons has-custom-font-size has-medium-font-size is-layout-flex wp-block-buttons-is-layout-flex\"><\/div>\n<h3 class=\"wp-block-heading\"><span id=\"Announcement_Events_Category_P\" class=\"ez-toc-section\"><\/span>2. Announcement Events (Category P):<\/h3>\n<p class=\"wp-block-paragraph\">Market reactions to management and governance announcements are not instantaneous. Even if news leaks beforehand, stock prices continue to fall following the official announcement.<\/p>\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><span style=\"font-size: 14pt\"><a href=\"https:\/\/www.tejwin.com\/en\/insights\/tcri-watchdog-part-1\/\">\ud83d\udc49<strong>Category \u201cN\u201d full version: TCRI Watchdog \u201cP\u201d\u00a0 Type Events Part1\u00a0<\/strong><\/a><\/span><\/div>\n<p>&nbsp;<\/p>\n<p><em><b>Turning Alternative Data into Alpha Signals!<\/b>\u00a0<\/em><\/p>\n<p><span data-contrast=\"auto\">\u00a0WD transforms events into structured data and quantitative factors, allowing alternative data to be integrated into models and\u00a0backtests. Investors can adjust positions before the market fully reflects the information, turning event signals into forward-looking alpha.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;134245417&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559740&quot;:360}\">\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>TCRI Watchdog (WD)\u00a0processes\u00a0unstructured information\u00a0(such as news and announcements)\u00a0into\u00a0a\u00a0structured\u00a0alternative\u00a0dataset, featuring\u00a0consistent and comparable\u00a0Event Scores (-3 to +3)\u00a0based on their impact on corporate credit risk. Through systematic event definitions and automated quantitative\u00a0processes,it\u00a0converts raw narratives into quantifiable event signals suitable for\u00a0backtesting\u00a0and alpha generation.<\/p>\n","protected":false},"featured_media":0,"template":"","tags":[57,58],"product_category":[135],"class_list":["post-3355","product","type-product","status-publish","hentry","tag-alternative-data","tag-tcri-watchdog","product_category-alternative-data"],"acf":{"p_introduction":"<h2 class=\"wp-block-heading\">Eliminating\u00a0Credit Noise with Alternative Data<\/h2>\r\n<p class=\"has-text-align-left wp-block-paragraph\">In the Taiwan stock market, while structured data such as financial reports and price information are complete and highly real-time, short-term stock price fluctuations are often driven by \u201cevents.\u201d From announcements and regulatory news to media reports, this unstructured information rapidly influences\u00a0investor\u2019s\u00a0expectations and capital flows, yet it\u00a0remains\u00a0difficult to capture effectively using traditional quantitative methods.<\/p>\r\n<p class=\"has-text-align-left wp-block-paragraph\">Identifying\u00a0influential signals from a vast array of events and\u00a0extracting actionable signals from events and\u00a0converting\u00a0them\u00a0into\u00a0backtestable\u00a0investment factors\u00a0has always been a key threshold for quantitative research.\u00a0TEJ developed the\u00a0<strong>TCRI Watchdog (WD)<\/strong>\u00a0database to\u00a0transform\u00a0unstructured\u00a0information\u00a0into\u00a0structured alternative\u00a0data\u00a0through a systematic classification and scoring mechanism,\u00a0assisting\u00a0researchers in effectively capturing alpha and strengthening forward-looking risk judgment.<\/p>\r\n\r\n<h2 class=\"wp-block-heading has-text-align-left\"><span id=\"TCRI_Watchdog_Structuring_Unstructured_Information_into_Alternative_Data\" class=\"ez-toc-section\"><\/span>TCRI Watchdog:\u00a0Structuring Unstructured Information into\u00a0Alternative Data<\/h2>\r\n<p class=\"wp-block-paragraph\"><strong>TCRI Watchdog (WD)<\/strong>\u00a0processes\u00a0unstructured information\u00a0(such as news and announcements)\u00a0into\u00a0a\u00a0structured\u00a0alternative\u00a0dataset, featuring\u00a0consistent and comparable\u00a0<strong>Event Scores (-3 to +3)<\/strong>\u00a0based on their impact on corporate credit risk. Through systematic event definitions and automated quantitative\u00a0processes,it\u00a0converts raw narratives into quantifiable event signals suitable for\u00a0backtesting\u00a0and alpha generation.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<div aria-hidden=\"true\"><span style=\"font-size: 18pt;color: #333399\">\u2b50<strong>Download our <em>WD Alternative Data Report<\/em> : <a style=\"color: #333399\" href=\"https:\/\/www.tejwin.com\/?wpforms_form_preview=3472\">click me!<\/a>\u00a0<\/strong><\/span><\/div>\r\n<h3 class=\"wp-block-heading\"><span id=\"Data_Scope\" class=\"ez-toc-section\"><\/span>Data Scope:<\/h3>\r\n<p class=\"wp-block-paragraph\">Includes historical records\u00a0from 2019\u00a0\u00a0for all listed and OTC companies in the Taiwan market, including delisted companies.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"Data_Sources\" class=\"ez-toc-section\"><\/span>Data Sources:<\/h3>\r\n<p class=\"wp-block-paragraph\">Data is integrated from three major sources:<\/p>\r\n\r\n<ul class=\"wp-block-list\">\r\n \t<li>Material information from the Market Observation Post System (MOPS).<\/li>\r\n<\/ul>\r\n<ul class=\"wp-block-list\">\r\n \t<li>Official sanctions from regulatory agencies such as the Financial Supervisory Commission (FSC) and the Ministry of Economic Affairs.<\/li>\r\n<\/ul>\r\n<ul class=\"wp-block-list\">\r\n \t<li>Mainstream financial media reports.<\/li>\r\n<\/ul>\r\n<h3 class=\"wp-block-heading\"><span id=\"Event_Intensity\" class=\"ez-toc-section\"><\/span>Event Intensity:<\/h3>\r\n<p class=\"wp-block-paragraph\">Event scores range from\u00a0<strong>-3 to +3<\/strong>. Negative values\u00a0represent\u00a0potential deterioration in credit risk, while positive values\u00a0represent\u00a0risk improvement or operational benefits. The larger the absolute value, the more significant the event\u2019s impact on corporate risk.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"Event_Classification\" class=\"ez-toc-section\"><\/span>Event Classification:<\/h3>\r\n<p class=\"has-text-align-left wp-block-paragraph\">All events are categorized into the following\u00a0<strong><mark class=\"has-inline-color has-vivid-cyan-blue-color\">5 dimensions<\/mark><\/strong>\u00a0and\u00a0<mark class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>over\u00a0100 subcategories<\/strong><\/mark>, constructing a quantifiable credit event framework. Each event is classified through collaboration between analysts and AI models based on its impact on corporate operations and credit risk:<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<p class=\"wp-block-paragraph\"><strong>Table 1: 5 Dimensions of TCRI Watchdog Events\u00a0\u00a0<\/strong><\/p>\r\n\r\n<figure class=\"wp-block-table\">\r\n<table>\r\n<tbody>\r\n<tr>\r\n<td><strong>Code<\/strong><\/td>\r\n<td><strong>Event Category<\/strong><\/td>\r\n<td><strong>Meaning<\/strong><\/td>\r\n<td><strong>Sub-classification Examples<\/strong><\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>A\u00a0<\/strong><\/td>\r\n<td><strong>Accounting<\/strong><\/td>\r\n<td>Events related to financial reporting, accounting treatments, and disclosure practices, reflecting financial transparency and stability.<\/td>\r\n<td>Alleged Fraud of financial\u00a0report,\u00a0\u00a0Restatement\u00a0of financial report\r\n\r\nTotal\uff1a13 subcategories<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>I\u00a0<\/strong><\/td>\r\n<td><strong>Industry<\/strong><\/td>\r\n<td>Events related to operating environment, capacity, costs, R&amp;D progress, and financing, revealing operating momentum and industry trends.<\/td>\r\n<td>Issues of suppliers or agency,\u00a0The loss of important talents\r\n\r\nTotal\uff1a27 subcategories<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>M\u00a0<\/strong><\/td>\r\n<td><strong>Management<\/strong><\/td>\r\n<td>Events involving corporate governance,\u00a0board\u00a0and executive changes, internal or external fraud, labor disputes, information security, and internal control deficiencies, reflecting governance and management stability.<\/td>\r\n<td>Suspicion of embezzlement or hollowing out of assets,\u00a0Executive changes\r\n\r\nTotal\uff1a41 subcategories<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>F\u00a0<\/strong><\/td>\r\n<td><strong>Market Trading<\/strong><\/td>\r\n<td>Events related to capital market trading, rating changes, abnormal price movements, and listing status, reflecting market\u00a0perceptions\u00a0of credit and liquidity.<\/td>\r\n<td>Stock price manipulation,\u00a0insider trading,\u00a0Cross Shareholding\r\n\r\nTotal\uff1a12 subcategories<\/td>\r\n<\/tr>\r\n<tr>\r\n<td><strong>R\u00a0<\/strong><\/td>\r\n<td><strong>Crsis<\/strong><\/td>\r\n<td>Events involving financial distress, default, delisting, or restructuring,\u00a0representing\u00a0the\u00a0most direct signals of credit risk.<\/td>\r\n<td>Rumored\u00a0financial crisis,\u00a0Bankruptcy\r\n\r\nTotal\uff1a22 subcategories<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/figure>\r\n<p class=\"wp-block-paragraph\">This framework\u00a0establishes\u00a0a unified standard, allowing investors to efficiently evaluate and compare various market events, ranging from individual stock risk monitoring to overall market risk sentiment assessment.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<h3 class=\"wp-block-heading\"><span id=\"Data_Transmission\" class=\"ez-toc-section\"><\/span><strong>Data Transmission:<\/strong><\/h3>\r\n<p class=\"wp-block-paragraph\">Data is delivered via\u00a0API\u00a0or\u00a0FTP\u00a0for automated transmission.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<p class=\"wp-block-paragraph\"><strong>Figure1: TCRI WD data sample\u00a0<\/strong><\/p>\r\n\r\n<figure class=\"wp-block-image size-full\"><img class=\"wp-image-44757\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/image-820.png\" alt=\"\" width=\"831\" height=\"474\" \/><\/figure>\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<p class=\"wp-block-paragraph\">As shown in the data sample, WD precisely defines fragmented market announcements as structured records featuring\u00a0<strong>Event<\/strong><strong>\u00a0<\/strong><strong>date<\/strong>,\u00a0<strong>Event Score<\/strong>, and\u00a0<strong>Event classification<\/strong>.<\/p>\r\n<p class=\"wp-block-paragraph\">According to Figure 2, the system\u00a0generates an average of over\u00a0<mark class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>3,500 structured credit\u00a0signals\u00a0monthly<\/strong><\/mark>. This steady,\u00a0<strong>high-density data stream<\/strong>\u00a0is ideal for\u00a0<strong>quantitative modeling<\/strong>\u00a0and\u00a0<strong>stress testing<\/strong>\u00a0due to its frequency and depth.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<p class=\"wp-block-paragraph\"><strong>Figure 2: Monthly\u00a0distribution\u00a0of TCRI Watchdog events\u00a0<\/strong><\/p>\r\n\r\n<figure class=\"wp-block-image size-full\"><img class=\"wp-image-44762\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/image-822.png\" alt=\"\" width=\"829\" height=\"411\" \/><\/figure>\r\n&nbsp;\r\n\r\n<strong>Source\uff1aTEJ\u00a0TCRI WD database\u00a0<\/strong>\r\n\r\n<strong>Period\uff1aJan\u00a02023~ Dec 2025\u00a0<\/strong>\r\n\r\n&nbsp;\r\n<h2 class=\"wp-block-heading\"><span id=\"3_Reasons_Why_Your_Strategy_Needs_TCRI_WD\" class=\"ez-toc-section\"><\/span>3 Reasons\u00a0Why Your Strategy Needs TCRI WD?<\/h2>\r\n<p class=\"wp-block-paragraph\">The failure of quantitative strategies often stems from underlying data\u00a0containing\u00a0too much noise unrelated to credit risk, causing true early-warning signals to be diluted or obscured. TCRI Watchdog (WD)\u00a0assists\u00a0research teams in skipping tedious data cleaning to focus on alpha mining, while enabling investment teams to integrate event risks into decision frameworks for better precision and efficiency.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"Unified_Event_Intensity_Grading\" class=\"ez-toc-section\"><\/span>Unified Event Intensity Grading:<\/h3>\r\n<p class=\"wp-block-paragraph\">\u00a0Provides a standardized scoring system from -3 to +3 for diverse unstructured events. This solves the difficulty of cross-sectional comparisons caused by a lack of quantitative benchmarks in original announcements.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"Qualitative_to_Quantitative_Information\" class=\"ez-toc-section\"><\/span>Qualitative to Quantitative Information:<\/h3>\r\n<p class=\"wp-block-paragraph\">\u00a0Filters core information relevant to corporate operations through automated algorithms and dual review by the TEJ professional team.\u00a0Unlike generic AI tools, WD strictly removes emotional noise, significantly reducing manual labeling time for analysts.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"Point-in-Time_PIT_Data_Structure\" class=\"ez-toc-section\"><\/span>Point-in-Time (PIT) Data Structure:<\/h3>\r\n<p class=\"wp-block-paragraph\">Strictly follows the PIT architecture, recording the precise timestamp of every event disclosure and including historical data of delisted companies. This\u00a0eliminates\u00a0<strong>look-ahead bias<\/strong>\u00a0and\u00a0<strong>survivor bias<\/strong>\u00a0in\u00a0backtesting, ensuring model authenticity.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><\/div>\r\n<h2 class=\"wp-block-heading\"><span id=\"Empirical_Research_Leading_Market_Warning_Signals\" class=\"ez-toc-section\"><\/span>Empirical Research: Leading Market Warning Signals<\/h2>\r\n<p class=\"wp-block-paragraph\">According to TEJ\u2019s ten-year\u00a0backtest, market reactions to non-financial information depend on the event\u2019s\u00a0<strong>category<\/strong>\u00a0and\u00a0<strong>intensity<\/strong>\u00a0rather than news volume.<\/p>\r\n\r\n<h3 class=\"wp-block-heading\"><span id=\"News_Events_Category_N\" class=\"ez-toc-section\"><\/span>1. News Events (Category N):<\/h3>\r\n<p class=\"wp-block-paragraph\">Empirical evidence shows a significant \u201cadvance reaction\u201d to strongly negative news (e.g., -3 points). Stock prices often show abnormal declines before the news is officially reported, with the downward trend expanding further after disclosure.<\/p>\r\n<span style=\"font-size: 14pt\"><a href=\"https:\/\/www.tejwin.com\/en\/insights\/from-news-to-markets-investment-signals-from-media-coverage-part-ii-an-empirical-analysis-of-tcri-watchdog-n-news-media-events\/\">\ud83d\udc49<strong>Category\u00a0\u201cN\u201d\u00a0full version:\u00a0TCRI Watchdog \u201cN News Media\u201d Events Part1<\/strong><\/a><\/span>\r\n<div class=\"wp-block-buttons has-custom-font-size has-medium-font-size is-layout-flex wp-block-buttons-is-layout-flex\"><\/div>\r\n<h3 class=\"wp-block-heading\"><span id=\"Announcement_Events_Category_P\" class=\"ez-toc-section\"><\/span>2. Announcement Events (Category P):<\/h3>\r\n<p class=\"wp-block-paragraph\">Market reactions to management and governance announcements are not instantaneous. Even if news leaks beforehand, stock prices continue to fall following the official announcement.<\/p>\r\n\r\n<div class=\"wp-block-spacer\" aria-hidden=\"true\"><span style=\"font-size: 14pt\"><a href=\"https:\/\/www.tejwin.com\/en\/insights\/tcri-watchdog-part-1\/\">\ud83d\udc49<strong>Category \u201cN\u201d full version: TCRI Watchdog \u201cP\u201d\u00a0 Type Events Part1\u00a0<\/strong><\/a><\/span><\/div>\r\n&nbsp;\r\n\r\n<em><b>Turning Alternative Data into Alpha Signals!<\/b>\u00a0<\/em>\r\n\r\n<span data-contrast=\"auto\">\u00a0WD transforms events into structured data and quantitative factors, allowing alternative data to be integrated into models and\u00a0backtests. Investors can adjust positions before the market fully reflects the information, turning event signals into forward-looking alpha.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-ccp-props=\"{&quot;134245417&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:2,&quot;335551620&quot;:2,&quot;335559740&quot;:360}\">\u00a0<\/span>","card_icon":"","card_summary":"","key_data_metrics":[{"metric_label":"Frequency","metric_value":"Daily"},{"metric_label":"Source","metric_value":"MOPS and news events from media"},{"metric_label":"Historical Period","metric_value":"From 2019"},{"metric_label":"Delivery Methods","metric_value":"FTP\/SFTP"}],"data_information":"TEJ TCRI Watchdog collects announcement events of listed companies on mops and news events from media, classified events into over 100 categories and score the events( from -3 to +3) to understand the impact of events on company's operation","delivery_methods":null,"doc_file":"","related_products":"","related_more_text":"View all","related_more_url":"\/en\/product-services\/"},"_links":{"self":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/product\/3355","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/types\/product"}],"wp:attachment":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/media?parent=3355"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/tags?post=3355"},{"taxonomy":"product_category","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/product_category?post=3355"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}