{"id":34900,"date":"2025-05-08T18:57:54","date_gmt":"2025-05-08T10:57:54","guid":{"rendered":"https:\/\/www.tejwin.com\/?post_type=news&#038;p=34900"},"modified":"2025-05-15T18:15:34","modified_gmt":"2025-05-15T10:15:34","slug":"factor-library","status":"publish","type":"news","link":"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/","title":{"rendered":"Factor Library \u2013 Taiwan&#8217;s Factor Dataset for Quantitative Investing"},"content":{"rendered":"\n<figure class=\"wp-block-gallery has-nested-images columns-default is-cropped wp-block-gallery-1 is-layout-flex wp-block-gallery-is-layout-flex\">\n<figure class=\"wp-block-image size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"576\" data-id=\"34868\" src=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-1024x576.jpg\" alt=\"\" class=\"wp-image-34868\" srcset=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-1024x576.jpg 1024w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-300x169.jpg 300w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-150x84.jpg 150w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-768x432.jpg 768w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library-1536x864.jpg 1536w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/TEJ-Factor-Library.jpg 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/figure>\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-6a11333de9e8c\" 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-6a11333de9e8c\"  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:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Introduction\" >Introduction<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Challenges_in_Factor_Investing\" >Challenges in Factor Investing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Introduction_to_the_Factor_Library\" >Introduction to the Factor Library<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Database_Construction_Methodology\" >Database Construction Methodology:<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#New_Development_Directions_2025_Onward\" >New Development Directions (2025 Onward):<\/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:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Factor_Library_%E2%80%93_Use_Cases_and_Applications\" >Factor Library \u2013 Use Cases and Applications<\/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:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Key_Applications\" >Key Applications<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Example_Multi-Factor_Stock_Selection\" >Example: Multi-Factor Stock Selection<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Key_Benefits_of_TEJ_Factor_Library\" >Key Benefits of TEJ Factor Library<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Feature\" >Feature<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Advantage\" >Advantage<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Benefit\" >Benefit<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/news\/factor-library\/#Further_Reading\" >Further Reading:<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span><strong>Introduction<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Over the past decades, <mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>quantitative investing<\/strong><\/mark> has evolved from academic theory into a core pillar of modern investment management. Foundational models such as CAPM, APT, and the Fama-French multifactor framework have shaped how investors identify and quantify systematic return drivers\u2014known as <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">factors<\/mark><\/strong>. These factors have since been embedded into institutional workflows, powering everything from <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">alpha <\/mark><\/strong>generation to portfolio construction and risk management.<\/p>\n\n\n\n<p>However, the proliferation of factors\u2014often inconsistently defined or statistically fragile\u2014has given rise to what researchers call the \u201cfactor zoo.\u201d This phenomenon underscores the urgent need for structured, high-quality data and disciplined implementation frameworks.<\/p>\n\n\n\n<p><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">TEJ\u2019s Factor Library<\/mark><\/strong> was created in response to these challenges. It offers a robust, <mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\"><strong>point-in-time (PIT) <\/strong><\/mark>database featuring more than 100 academically grounded and locally adapted factors across 9 core categories. Built for practical deployment in the <strong>Taiwan stock market<\/strong>, the library empowers investors to accelerate research, build repeatable <strong>quantitative strategies<\/strong>, and generate more reliable <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">alpha signals <\/mark><\/strong>through transparent and consistent data.<\/p>\n\n\n\n<p>Yet even with a well-structured foundation, factor investing remains a complex discipline\u2014especially when moving from theory to execution.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Challenges_in_Factor_Investing\"><\/span>Challenges in Factor Investing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The factor investing process\u2014from data collection to strategy construction\u2014is complex and resource-intensive (see Figure 1). Analysts must source data from multiple providers or crawlers, deal with inconsistent formats, and often face the lack of a <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">point-in-time<\/mark><\/strong> (PIT) structure\u2014introducing risks like <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">look-ahead bias.<\/mark><\/strong><\/p>\n\n\n\n<figure class=\"wp-block-gallery has-nested-images columns-default is-cropped wp-block-gallery-2 is-layout-flex wp-block-gallery-is-layout-flex\">\n<figure class=\"wp-block-image size-large is-style-default\"><img decoding=\"async\" width=\"1024\" height=\"418\" data-id=\"34875\" src=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-1024x418.jpg\" alt=\"Factor research workflow\" class=\"wp-image-34875\" srcset=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-1024x418.jpg 1024w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-300x122.jpg 300w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-150x61.jpg 150w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-768x313.jpg 768w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2-1536x626.jpg 1536w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Factor-research-workflow-2.jpg 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/figure>\n\n\n\n<p><em>Figure1\uff1aTraditional Factor Research Workflow<\/em><\/p>\n\n\n\n<p>Preprocessing involves missing value handling, outlier detection, and aligning data by release timing\u2014all technically demanding tasks. Designing factor logic requires extensive literature review, adapting definitions for local markets, and ensuring statistical validity. These challenges consume significant time and resources and introduce errors that can hinder research and replication.<\/p>\n\n\n\n<p>A well-structured factor database that incorporates PIT processing, academic rigor, and transparent methodology can greatly streamline the process and help investors focus on strategy innovation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction_to_the_Factor_Library\"><\/span>Introduction to the Factor Library<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>TEJ&#8217;s Factor Library is a structured, point-in-time database designed to explain asset risks and returns through factor characteristics. It currently covers nine major factor categories: Momentum, Dividend Yield, Value, Growth, Quality, Liquidity, Volatility, Size, and Sentiment. All data are processed with complete PIT alignment and traceability to eliminate forward-looking bias.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-1024x576.png\" alt=\"\" class=\"wp-image-35060\" style=\"width:840px;height:auto\" srcset=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-1024x576.png 1024w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-300x169.png 300w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-150x84.png 150w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-768x432.png 768w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library-1536x864.png 1536w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/59-Factor-library.png 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p><em>Figure 2\uff1aTEJ Factor Library \uff0d9 Factor Categories<\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Database_Construction_Methodology\"><\/span>Database Construction Methodology:<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Academic Foundations:<\/strong> Derived from global academic journals and institutional research, supplemented by TEJ&#8217;s proprietary analysis.<\/li>\n\n\n\n<li><strong>Data Source:<\/strong> Built on TEJ&#8217;s investment-grade database, fully <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-vivid-cyan-blue-color\">point-in-time.<\/mark><\/strong><\/li>\n\n\n\n<li><strong>Localization:<\/strong> Adjusted from academic definitions for <strong>relevance to Taiwan&#8217;s stock market<\/strong>.<\/li>\n\n\n\n<li><strong>Factor Count:<\/strong> Over 100 factors will be built by 2025, including academic and machine-learning-based factors.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"New_Development_Directions_2025_Onward\"><\/span>New Development Directions (2025 Onward):<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Machine Learning Factors:<\/strong> Combining supervised and unsupervised algorithms to improve predictive power and local market fit.<\/li>\n\n\n\n<li><strong>Alternative Data Factors:<\/strong> Transforming non-traditional sources like news and ESG disclosures into investment-grade factors to diversify strategies and manage risk. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\" style=\"font-style:normal;font-weight:400;text-decoration:none\"><table class=\"has-pale-cyan-blue-background-color has-background\"><thead><tr><th><strong>Category<\/strong><\/th><th><strong>Description<\/strong><\/th><\/tr><\/thead><tbody><tr><td><strong>Momentum<\/strong><\/td><td>Reflects the continuation of a company\u2019s stock price and fundamental performance. Includes two subcategories: <strong>Price Momentum<\/strong> and <strong>Fundamental Momentum<\/strong>.<\/td><\/tr><tr><td><strong>Dividend Yield<\/strong><\/td><td>Reflects a company\u2019s dividend policy.<\/td><\/tr><tr><td><strong>Value<\/strong><\/td><td>Reflects market valuation of the company. Includes two subcategories: <strong>Book-to-Price<\/strong> and <strong>Earnings Yield<\/strong>.<\/td><\/tr><tr><td><strong>Growth<\/strong><\/td><td>Reflects a company\u2019s earnings growth potential.<\/td><\/tr><tr><td><strong>Quality<\/strong><\/td><td>Reflects the fundamental characteristics of a company. Includes subcategories such as <strong>Profitability<\/strong>, <strong>Earnings Quality<\/strong>, <strong>Investment Quality<\/strong>, <strong>Earnings Variability<\/strong>, and <strong>Solvency<\/strong>.<\/td><\/tr><tr><td><strong>Liquidity<\/strong><\/td><td>Reflects the activeness of stock trading.<\/td><\/tr><tr><td><strong>Volatility<\/strong><\/td><td>Reflects the uncertainty in stock prices or returns. Includes two subcategories: <strong>Beta<\/strong> and <strong>Residual Volatility<\/strong>.<\/td><\/tr><tr><td><strong>Size<\/strong><\/td><td>Reflects the market capitalization of a company.<\/td><\/tr><tr><td><strong>Sentiment<\/strong><\/td><td>Reflects investor perception and market sentiment toward a stock. Includes subcategories such as <strong>Fund Flow<\/strong>, <strong>Holdings<\/strong>, <strong>News-based Information<\/strong>, and <strong>Behavioral Factors<\/strong>.<\/td><\/tr><\/tbody><\/table><figcaption class=\"wp-element-caption\"><strong><em>Table 1: Description of the 9 Categories in the Factor Library<\/em><\/strong><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Factor_Library_%E2%80%93_Use_Cases_and_Applications\"><\/span>Factor Library \u2013 Use Cases and Applications<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The value of the Factor Library extends beyond data provision\u2014it enables diverse applications across the investment lifecycle. Depending on the strategy, investors can deploy single or multiple factors for stock selection, risk assessment, and model construction.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Key_Applications\"><\/span>Key Applications<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Factor-Based Stock Selection:<\/strong> By filtering stocks based on one or multiple factor metrics, investors can identify equities with specific desired characteristics. This helps narrow down the investable universe and improves the precision and efficiency of the stock selection process.<\/li>\n\n\n\n<li><strong>Quantitative Investing:<\/strong> Researchers can use factor data to develop entirely new investment strategies or refine existing ones. By integrating selected factors into systematic models, they can better capture specific risk premia and <strong>alpha signals<\/strong>\u2014ultimately enhancing portfolio return potential.<\/li>\n\n\n\n<li><strong>Risk Analysis:<\/strong> Factor data can be used to assess the underlying risk profile of individual securities or entire portfolios. This enables investors to strengthen their risk control frameworks and make more informed asset allocation decisions.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Example_Multi-Factor_Stock_Selection\"><\/span>Example: Multi-Factor Stock Selection<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Stock Universe Definition: <\/strong>Based on liquidity and size.<\/li>\n\n\n\n<li><strong>Factor Testing &amp; Selection<\/strong>: Identify effective factors.<\/li>\n\n\n\n<li><strong>Model Construction<\/strong>: Standardize and weight selected factors (e.g., Z-score method).<\/li>\n\n\n\n<li><strong>Strategy Execution<\/strong>: Define rebalancing and portfolio rules; execute trades accordingly.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-gallery has-nested-images columns-default is-cropped wp-block-gallery-3 is-layout-flex wp-block-gallery-is-layout-flex\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"457\" data-id=\"34885\" src=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-1024x457.png\" alt=\"\" class=\"wp-image-34885\" srcset=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-1024x457.png 1024w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-300x134.png 300w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-150x67.png 150w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-768x343.png 768w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy-1536x686.png 1536w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/Cumulative-Return-of-a-Factor-Strategy.png 1964w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/figure>\n\n\n\n<p><em>Figure 3: Cumulative Return of a Factor Strategy \u2013 highlighting how factor data supports performance backtesting to discover alpha-generating strategies.<\/em><\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Key_Benefits_of_TEJ_Factor_Library\"><\/span>Key Benefits of TEJ Factor Library<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In today&#8217;s market environment\u2014characterized by an explosion of factors and widening information gaps\u2014researchers often find themselves bogged down by labor-intensive processes such as data preparation, validation, and ongoing maintenance. These challenges make it difficult to focus on strategic optimization and backtesting. The TEJ Factor Library was explicitly designed to solve these pain points. Its data service emphasizes academic rigor, practical relevance, and completeness in update frequency, data structure, and usability. It also serves as a high-quality <strong>market data service<\/strong> that facilitates advanced <strong>quantitative data analysis<\/strong>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Feature\"><\/span>Feature<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Delivers daily updated factor data<\/li>\n\n\n\n<li>Built on a full Point-in-Time (PIT) architecture, covering a wide range of factor categories<\/li>\n\n\n\n<li>All factor calculations are academically grounded, accompanied by clear documentation (Table 2)<\/li>\n\n\n\n<li>Offers transparent and traceable data processing workflows<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Advantage\"><\/span>Advantage<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Reduces research time and lowers the risk of data-related errors<\/li>\n\n\n\n<li>Enhances the robustness of strategies and the credibility of backtest results<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Benefit\"><\/span>Benefit<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Accelerates research cycles and improves development productivity<\/li>\n\n\n\n<li>Effectively supports the deployment of <strong>quantitative strategies<\/strong> in real-world applications<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-table is-style-regular has-medium-font-size\"><table class=\"has-background\" style=\"background:linear-gradient(135deg,rgb(255,245,203) 0%,rgba(51,168,181,0) 100%)\"><tbody><tr><td><strong>Factor Code<\/strong><\/td><td>mom52wh<\/td><\/tr><tr><td><strong>Factor Name<\/strong><\/td><td>Momentum Factor (52-Week High)<\/td><\/tr><tr><td><strong>English Name<\/strong><\/td><td>52-Week High Momentum (MOM52WH)<\/td><\/tr><tr><td><strong>Category<\/strong><\/td><td>Momentum<\/td><\/tr><tr><td><strong>Subcategory<\/strong><\/td><td>Price Momentum<\/td><\/tr><tr><td><strong>Expected Direction<\/strong><\/td><td>Positive<\/td><\/tr><tr><td><strong>Reference<\/strong><\/td><td>George, T.J., &amp; Hwang, C. (2004). <em>The 52-Week High and Momentum Investing<\/em>. Journal of Finance, 59(5), 2145\u20132176.<\/td><\/tr><tr><td><strong>Calculation Method<\/strong><\/td><td>Adjusted closing price of the day divided by the highest adjusted price over the past 252 trading days.<\/td><\/tr><\/tbody><\/table><figcaption class=\"wp-element-caption\"><em>Table 2: Sample Factor Description<\/em><\/figcaption><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>TEJ&#8217;s Factor Library empowers investment teams with high-quality, standardized, and traceable factor data, bridging the gap from data acquisition to live strategy execution. It&#8217;s not just a research tool, but a strategic asset\u2014enabling alpha discovery, model backtesting, and risk management.<\/p>\n\n\n\n<p>By combining academic insights with local market practices, and supporting over 100 factors across nine categories with PIT structure and daily updates, TEJ provides the robust infrastructure required to navigate the expanding world of <strong>factor investing<\/strong>. In an era of market uncertainty and data explosion, only those with access to verifiable and flexible factor systems can stay ahead in the quant investing landscape.<\/p>\n\n\n\n<p>TEJ&#8217;s commitment to innovation, accuracy, and usability positions the Factor Library as an indispensable resource for investors aiming to transform data into performance.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Further_Reading\"><\/span><strong>Further Reading:<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/insight\/how-dividend-policy-affects-investment-an-event-study-analysis-of-key-factors\/\" data-type=\"link\" data-id=\"https:\/\/tejwin20260323.j.webweb.today\/en\/insight\/how-dividend-policy-affects-investment-an-event-study-analysis-of-key-factors\/\">How Dividend Policy Affects Investment: An Event Study Analysis of Key Factors<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/insight\/affiliated-companies-disclosures\/\">Unlocking Market Insights: Comparing Three Strategies Based on Directors&#8217; Shareholding Data<\/a><\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/tejwin20260323.j.webweb.today\/en\/meet-tej-at-neudata-hk-data-summit\/\" target=\"_blank\" rel=\"noreferrer noopener\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"107\" src=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-1024x107.png\" alt=\"\" class=\"wp-image-34896\" srcset=\"https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-1024x107.png 1024w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-300x31.png 300w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-150x16.png 150w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-768x80.png 768w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit-1536x160.png 1536w, https:\/\/tejwin20260323.j.webweb.today\/wp-content\/uploads\/NeudataSummit.png 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Factor Library \u2013 TEJ&#8217;s Factor Database for Quantitative Investing<\/p>\n","protected":false},"featured_media":34868,"parent":0,"menu_order":0,"template":"","tags":[3442,2962,2988,3421],"news-category":[764,688],"class_list":["post-34900","news","type-news","status-publish","has-post-thumbnail","hentry","tag-alpha-2","tag-market-data","tag-quantitative-analysis","tag-quantitative-strategy","news-category-product-introduction-en","news-category-product-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/news\/34900","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/types\/news"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/media\/34868"}],"wp:attachment":[{"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/media?parent=34900"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/tags?post=34900"},{"taxonomy":"news-category","embeddable":true,"href":"https:\/\/tejwin20260323.j.webweb.today\/en\/wp-json\/wp\/v2\/news-category?post=34900"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}