{"id":38600,"date":"2025-07-30T14:00:00","date_gmt":"2025-07-30T06:00:00","guid":{"rendered":"https:\/\/www.tejwin.com\/?post_type=insight&#038;p=38600"},"modified":"2025-09-08T15:14:15","modified_gmt":"2025-09-08T07:14:15","slug":"industry-rotation-shipping-semiconductors","status":"publish","type":"insight","link":"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/","title":{"rendered":"Shipping Leads, Semiconductors Follow? A Data-Driven View on Taiwan\u2019s Sector Rotation"},"content":{"rendered":"\n<figure class=\"wp-block-image aligncenter size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"660\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/\/dominik-luckmann-SInhLTQouEk-unsplash-1024x660.jpg\" alt=\"\" class=\"wp-image-35134\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-1024x660.jpg 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-300x193.jpg 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-150x97.jpg 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-768x495.jpg 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-1536x990.jpg 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/dominik-luckmann-SInhLTQouEk-unsplash-2048x1319.jpg 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Photo by <a href=\"https:\/\/unsplash.com\/@exdigy?utm_content=creditCopyText&amp;utm_medium=referral&amp;utm_source=unsplash\" target=\"_blank\" rel=\"noopener\">Dominik L\u00fcckmann<\/a> on <a href=\"https:\/\/unsplash.com\/photos\/blue-and-red-cargo-ship-on-dock-during-daytime-SInhLTQouEk?utm_content=creditCopyText&amp;utm_medium=referral&amp;utm_source=unsplash\" target=\"_blank\" rel=\"noopener\">Unsplash<\/a><\/figcaption><\/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-69f10aaf5e910\" 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-69f10aaf5e910\"  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\/industry-rotation-shipping-semiconductors\/#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:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Macroeconomic_Background\" >Macroeconomic Background<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Industry_Data_Analysis_Methodology\" >Industry Data Analysis Methodology<\/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:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Visualizing_the_RSI_Values_of_Major_Industries\" >Visualizing the RSI Values of Major Industries<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Industry_Data_Charts_and_Analysis\" >Industry Data Charts and Analysis<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Lagged_Correlation_Analysis\" >Lagged Correlation Analysis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Transfer_Entropy_Analysis\" >Transfer Entropy Analysis<\/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\/industry-rotation-shipping-semiconductors\/#Conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.tejwin.com\/en\/insight\/industry-rotation-shipping-semiconductors\/#Explore_TEJs_database_for_quantitative_investing_and_sector_modeling\" >Explore TEJ\u2019s database for quantitative investing and sector modeling:<\/a><\/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\/industry-rotation-shipping-semiconductors\/#Further_Reading\" >Further Reading<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading has-text-align-left\"><span class=\"ez-toc-section\" id=\"Introduction\"><\/span>Introduction<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In investment practice,\u00a0<em><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">industry rotation<\/mark><\/em>\u00a0has long been a key basis for capital allocation and stock selection. As the economic cycle progresses, market capital often shifts gradually from leading industries to lagging ones, forming a structural sector rotation. For instance, during the early stage of economic recovery, cyclical sectors such as shipping and steel often react first. As the economy continues to expand and corporate capital expenditures increase, growth-oriented sectors like semiconductors and technology stocks may take the lead.<\/p>\n\n\n\n<p>Although this type of rotation logic is widely referenced in macroeconomic analysis, accurately identifying its&nbsp;<em>starting and ending points<\/em>&nbsp;still requires the support of quantitative tools and empirical data. This article focuses on historical data from various industry indices and utilizes statistical tools such as&nbsp;Transfer Entropy&nbsp;and&nbsp;rolling correlation coefficients to examine whether stable lead-lag relationships exist between different sectors. It also explores the potential role of economic indicators, such as the business cycle signal lights, in these inter-sector dynamics.<\/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=\"Macroeconomic_Background\"><\/span><strong>Macroeconomic Background<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Taiwan\u2019s economic structure is heavily reliant on technology manufacturing and export-oriented industries, with the <mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">semiconductor sector<\/mark> at its core. According to data from the Ministry of Economic Affairs, Taiwan holds a leading global market share in semiconductors, encompassing a complete supply chain from upstream <a href=\"https:\/\/www.tejwin.com\/en\/insight\/ic-design-firms-trends-part1\/\" data-type=\"link\" data-id=\"https:\/\/www.tejwin.com\/en\/insight\/ic-design-firms-trends-part1\/\"><strong>IC design<\/strong><\/a>, to midstream wafer fabrication, and downstream packaging and testing. The semiconductor industry serves as a major driver of Taiwan\u2019s GDP and exports, making its business cycle and capital flows a key indicator not only for the domestic stock market but also for the broader economy.<\/p>\n\n\n\n<p>However, across different phases of the economic cycle, market capital does not always concentrate in a single sector. Instead, it rotates among various segments depending on prevailing macroeconomic conditions. This rotation may be influenced by multiple factors, such as fluctuations in global trade, inflationary pressure, interest rate policies, and capital expenditure cycles. Therefore, understanding the relative dynamics between the semiconductor sector and other industries can help investors make more forward-looking decisions in sector allocation.<\/p>\n\n\n\n<p>In light of this, the semiconductor industry is selected as the core observation target in this study. We further examine whether it exhibits clear lead-lag or rotational relationships with other sectors\u2014such as finance and insurance, shipping, and biotechnology\u2014and attempt to construct a practical framework for predicting sector rotation.<\/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=\"Industry_Data_Analysis_Methodology\"><\/span><strong>Industry Data Analysis Methodology<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>For the purpose of conducting empirical analysis on industry rotation, this study utilizes historical industry index data provided by\u00a0<strong><a href=\"https:\/\/www.tejwin.com\/en\/news\/quantitative-investment\/\" data-type=\"link\" data-id=\"https:\/\/www.tejwin.com\/en\/news\/quantitative-investment\/\">TEJ Quantitative Investment Database<\/a><\/strong>. The database covers major sector classifications in Taiwan stock market, including semiconductors, electronics, finance &amp; insurance, shipping, and biotechnology. It offers long-term, daily historical data, making it well-suited for analyzing rotation behavior over time.<\/p>\n\n\n\n<p class=\"has-background has-medium-font-size\" style=\"background-color:#ffe9ae\"><em><strong>\ud83d\udc49 <a href=\"https:\/\/www.tejwin.com\/en\/news\/quantitative-investment\/\" data-type=\"link\" data-id=\"https:\/\/www.tejwin.com\/en\/news\/quantitative-investment\/\">Start your Quantitative Strategy from TEJ Quantitative Investment Database<\/a><\/strong><\/em><\/p>\n\n\n\n<p>Since industry indices are price-based and typically show a gradual upward trend over the long run, they do not fluctuate within a fixed range. As a result, directly analyzing raw price data makes it difficult to detect relative strength changes across sectors. To address this issue, the study applies the\u00a0<strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Relative Strength Index (RSI)<\/mark><\/strong>\u00a0to each industry index. RSI, a momentum-based indicator, reflects the proportion of gains versus losses over a given time window, allowing us to identify periods of relative strength or weakness among sectors.<\/p>\n\n\n\n<p>After computing the RSI time series for each sector, the following three analyses are performed:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Rolling Correlation Visualization<\/mark><\/strong>: This method visualizes the time-varying correlation between each sector\u2019s RSI and that of the semiconductor sector, helping to reveal whether rotation patterns exhibit periodicity, repeatability, or structural shifts.<\/li>\n\n\n\n<li><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Lagged Correlation Analysis<\/mark><\/strong>: This step calculates the correlation between each sector\u2019s RSI and the semiconductor RSI at various lag intervals, identifying the lag with the highest correlation. This helps infer the sequence in which rotation may occur.<\/li>\n\n\n\n<li><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Transfer Entropy (TE) Analysis<\/mark><\/strong>: Using tools from information theory, this analysis measures whether one sector\u2019s RSI provides additional predictive power over the semiconductor RSI. By comparing the directional strength of information flow, we can assess the existence of potential rotation relationships and leading sectors.<\/li>\n<\/ol>\n\n\n\n<p>Through these methods, the study aims to quantify and verify whether time-shifted rotational logic exists among industries, thereby providing practical insights for investment strategy decisions. The analysis uses data from&nbsp;<strong>early 2012 to the end of 2019<\/strong>&nbsp;for model development, while the period from&nbsp;<strong>early 2020 onward<\/strong>&nbsp;is reserved for strategy backtesting to avoid overfitting.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Visualizing_the_RSI_Values_of_Major_Industries\"><\/span>Visualizing the RSI Values of Major Industries<br><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"438\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/\/ss-1024x438.png\" alt=\"\" class=\"wp-image-35128\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/ss-1024x438.png 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ss-300x128.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ss-150x64.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ss-768x328.png 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ss-1536x657.png 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ss.png 1597w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>Visual analysis of RSI trends suggests the presence of rotational behavior among sectors, with some leading or lagging at different phases. The RSI, as a momentum indicator, highlights relative strength shifts across industries over time. However, visual patterns alone are insufficient to confirm statistical validity. To address this, we apply quantitative techniques in the following sections to verify whether these observed dynamics reflect consistent, data-driven relationships.<\/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=\"Industry_Data_Charts_and_Analysis\"><\/span><strong>Industry Data Charts and Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"439\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/\/\u310b-1024x439.png\" alt=\"\" class=\"wp-image-35130\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b-1024x439.png 1024w, https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b-300x129.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b-150x64.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b-768x330.png 768w, https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b-1536x659.png 1536w, https:\/\/www.tejwin.com\/wp-content\/uploads\/\u310b.png 1645w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>The 60-day rolling correlation chart captures how industry RSI values co-move with the semiconductor sector over time. Electronics show persistently high correlation with semiconductors, suggesting a structurally aligned trend. In contrast, <strong>the shipping sector exhibits cyclical swings in correlation, indicating a potential lagged relationship<\/strong>. Financials and biotechnology display more volatile or inverse patterns, implying weaker alignment. These findings support the hypothesis that certain industries, particularly shipping, may demonstrate rotational behavior relative to semiconductors\u2014offering practical signals for sector allocation strategies.<\/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=\"Lagged_Correlation_Analysis\"><\/span>Lagged Correlation Analysis<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"1016\" height=\"552\" src=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/ff.png\" alt=\"\" class=\"wp-image-35132\" srcset=\"https:\/\/www.tejwin.com\/wp-content\/uploads\/ff.png 1016w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ff-300x163.png 300w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ff-150x81.png 150w, https:\/\/www.tejwin.com\/wp-content\/uploads\/ff-768x417.png 768w\" sizes=\"(max-width: 1016px) 100vw, 1016px\" \/><\/figure>\n\n\n\n<p>This section explores lagged correlations between each sector and the semiconductor index over a \u00b160-day window. The shipping sector shows the strongest correlation at +30 days, suggesting it may lead semiconductors by about one month. In contrast, financials peak at -50 days, implying they tend to lag behind semiconductors. Electronics and biotech exhibit flatter correlation curves, lacking clear lead-lag structure. <\/p>\n\n\n\n<p>These results support the hypothesis of a <strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">\u201cShipping \u2192 Semiconductors\u201d <\/mark><\/strong>rotation sequence, while the reverse holds for finance\u2014offering insight into potential timing windows for inter-sector allocation.<\/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=\"Transfer_Entropy_Analysis\"><\/span><strong>Transfer Entropy Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\">Transfer Entropy (TE) <\/mark><\/strong>quantifies the directional strength of information flow between two time series, capturing asymmetric and nonlinear relationships that traditional correlation may overlook. In simple terms, if the TE from Industry A to Industry B is consistently greater than the reverse, it suggests that changes in A offer stronger predictive value for B.<\/p>\n\n\n\n<p>The tables below summarize TE values across different lag settings (3, 5, and 7 trading days) between the semiconductor sector and other key industries. Importantly, <strong>only when a consistent directional flow is observed across multiple lags do we consider the result statistically reliable and indicative of a meaningful sector rotation pattern.<\/strong><\/p>\n\n\n\n<p class=\"has-text-align-center\">Shipping Sector vs. Semiconductor Sector<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Lag Period<\/strong><br><strong> (Trading Days)<\/strong><\/td><td><strong>TE: Shipping \u2192 Semiconductor<\/strong><\/td><td><strong>TE: Semiconductor \u2192 Shipping<\/strong><\/td><td><strong>Information Flow Direction<\/strong><\/td><\/tr><tr><td>3<\/td><td>0.0177<\/td><td>0.0155<\/td><td>Shipping \u2192 Semiconductor<\/td><\/tr><tr><td>5<\/td><td>0.0539<\/td><td>0.0376<\/td><td>Shipping \u2192 Semiconductor<\/td><\/tr><tr><td>7<\/td><td>0.0866<\/td><td>0.0589<\/td><td>Shipping \u2192 Semiconductor<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>TE values from shipping to semiconductors are consistently higher across all lags and increase with longer lag periods. This suggests strong directional stability and <strong>positions shipping as a potential leading indicator<\/strong>.<\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-center\">Finance and Insurance Sector vs. Semiconductor Sector<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Lag Period<\/strong><\/td><td><strong>TE: Finance \u2192 Semiconductor<\/strong><\/td><td><strong>TE: Semiconductor \u2192 Finance<\/strong><\/td><td><strong>Information Flow Direction<\/strong><\/td><\/tr><tr><td>3<\/td><td>0.0188<\/td><td>0.0164<\/td><td>Finance \u2192 Semiconductor<\/td><\/tr><tr><td>5<\/td><td>0.0469<\/td><td>0.0538<\/td><td>Semiconductor \u2192 Finance<\/td><\/tr><tr><td>7<\/td><td>0.078<\/td><td>0.0811<\/td><td>Semiconductor \u2192 Finance<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>The direction of information flow varies across lags. While finance appears to lead at shorter lags, semiconductors lead at longer ones. This inconsistency reduces its predictive reliability.<\/p>\n\n\n\n<div style=\"height:25px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-center\">Biotechnology Sector vs. Semiconductor Sector<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Lag Period<\/strong><\/td><td><strong>TE: Biotech \u2192 Semiconducto<\/strong>r<\/td><td><strong>TE: Semiconductor \u2192 Finance<\/strong><\/td><td><strong>Information Flow Direction<\/strong><\/td><\/tr><tr><td>3<\/td><td>0.0139<\/td><td>0.0169<\/td><td>Semiconductor \u2192 Biotech<\/td><\/tr><tr><td>5<\/td><td>0.0487<\/td><td>0.0333<\/td><td>Biotech \u2192 Semiconductor<\/td><\/tr><tr><td>7<\/td><td>0.0779<\/td><td>0.0494<\/td><td>Biotech \u2192 Semiconductor<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Biotech shows a similarly unstable relationship. The flow direction reverses depending on the lag setting, indicating weak and inconsistent influence.<\/p>\n\n\n\n<p>These results suggest that the <strong>shipping sector may serve as a robust input for rotation-based models<\/strong>, while finance and biotech are more prone to instability and parameter sensitivity.<\/p>\n\n\n\n<p><em><strong>Disclaimer:<\/strong>\u00a0This analysis is for informational purposes only and does not constitute any investment advice or recommendation on specific financial products.<\/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\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>This study presents empirical evidence that Taiwan\u2019s shipping sector can serve as a leading indicator for semiconductor performance, supported by consistent signals from rolling correlation, lagged correlation, and Transfer Entropy analyses. These findings offer a quantitative foundation for developing timing strategies and inter-sector rotation models within Taiwan stock market.<\/p>\n\n\n\n<p>For investors seeking to build such strategies, <mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"><strong>TEJ provides comprehensive Point-in-time databases tailored for quantitative research<\/strong>.<\/mark> These resources include historical sector indices, industry-level classifications, and both<strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-luminous-vivid-orange-color\"> market and fundamental data<\/mark><\/strong>\u2014critical for accurately distinguishing sector behavior and analyzing stock performance over time.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Explore_TEJs_database_for_quantitative_investing_and_sector_modeling\"><\/span>Explore TEJ\u2019s database for quantitative investing and sector modeling:<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li class=\"has-medium-font-size\"><a href=\"https:\/\/www.tejwin.com\/en\/news\/quantitative-investment\/\">Quantitative Investment Overview \u00bb<\/a><\/li>\n\n\n\n<li class=\"has-medium-font-size\"><a href=\"https:\/\/www.tejwin.com\/en\/solution\/fundamental-data\/\">Taiwan Stock Fundamental Data \u00bb<\/a><\/li>\n\n\n\n<li class=\"has-medium-font-size\"><a href=\"https:\/\/www.tejwin.com\/en\/solution\/market-data\/\">Taiwan Stock Market and Sector Index Data \u00bb<\/a><\/li>\n<\/ul>\n\n\n\n<p><br><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Further_Reading\"><\/span>Further Reading<span class=\"ez-toc-section-end\"><\/span><\/h2>\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=\"b6I6xWfTo5\"><a href=\"https:\/\/www.tejwin.com\/en\/insight\/turning-sector-rotation-into-strategy-applying-industry-sequencing-to-build-a-quantitative-backtesting-model\/\">Turning sector rotation into strategy: Applying industry sequencing to build a quantitative backtesting model<\/a><\/blockquote><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; visibility: hidden;\" title=\"&#8220;Turning sector rotation into strategy: Applying industry sequencing to build a quantitative backtesting model&#8221; &#8212; TEJ\" src=\"https:\/\/www.tejwin.com\/en\/insight\/turning-sector-rotation-into-strategy-applying-industry-sequencing-to-build-a-quantitative-backtesting-model\/embed\/#?secret=uKmYopCW8w#?secret=b6I6xWfTo5\" data-secret=\"b6I6xWfTo5\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Analyze industry rotation between Taiwan\u2019s shipping and semiconductor sectors using momentum and valuation factors. This study reveals how factor-based strategies capture cyclical shifts\u2014and why semiconductors ultimately outperformed over time.<\/p>\n","protected":false},"featured_media":35135,"template":"","tags":[2962,3176,2371,3007,3008,3166],"insight-category":[690,885],"class_list":["post-38600","insight","type-insight","status-publish","has-post-thumbnail","hentry","tag-market-data","tag-python-2","tag-python","tag-tejapi-data-analysis","tag-tejapi-quant","tag-tquant-lab-2","insight-category-data-analysis","insight-category-tquant-lab"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/38600","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":12,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/38600\/revisions"}],"predecessor-version":[{"id":39085,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight\/38600\/revisions\/39085"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/media\/35135"}],"wp:attachment":[{"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/media?parent=38600"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/tags?post=38600"},{"taxonomy":"insight-category","embeddable":true,"href":"https:\/\/www.tejwin.com\/en\/wp-json\/wp\/v2\/insight-category?post=38600"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}