{"id":84105,"date":"2024-08-15T12:50:31","date_gmt":"2024-08-15T16:50:31","guid":{"rendered":"https:\/\/www.bloomberg.com\/professional\/insights\/data\/identifying-uncorrelated-market-returns-using-company-revenue-segments\/"},"modified":"2024-09-13T18:46:09","modified_gmt":"2024-09-13T22:46:09","slug":"identifying-uncorrelated-market-returns-using-company-revenue-segments","status":"publish","type":[3762],"link":"https:\/\/www.bloomberg.com\/professional\/insights\/data\/identifying-uncorrelated-market-returns-using-company-revenue-segments\/","title":{"rendered":"Identifying uncorrelated market returns using company revenue segments"},"content":{"rendered":"<div  class=\"bbg-row-container\">\n    <style>section[data-anchor=row-6a09a630b6b43]::before {\n\t\t\t\tbackground-color: #eeeeee;\n\t\t\t}<\/style>\n    <section class=\"bbg-row bg--custom-color  bg--eeeeee text--black bbg-row--full-bg-bleed\" data-anchor='row-6a09a630b6b43'>\n        \n        \n        <div\n            class=\"bbg-row--content\"\n                    >\n            \n            <p><div\n    class=\"bbg-column bbg-column--width-2\"\n    style=\"\"\n    >\n    \n<\/div><div\n    class=\"bbg-column bbg-column--width-8 bbg-column--valign-bottom\"\n    style=\"\"\n    >\n    <p>    <ul class=\"bbg-categories_list\">\n                    <li>\n                <a href=\"https:\/\/www.bloomberg.com\/professional\/insights\/category\/data\/\" rel=\"category tag\">\n                    Data\n                <\/a>\n            <\/li>\n                    <li>\n                <a href=\"https:\/\/www.bloomberg.com\/professional\/insights\/category\/trading\/\" rel=\"category tag\">\n                    Trading\n                <\/a>\n            <\/li>\n            <\/ul>\n<div\n    class=\"bbg-spacer\"\n        style=\"height: 24px !important\"\n    >\n<\/div>    <h1 class=\"bbg-metadata bbg-metadata--title\">Identifying uncorrelated market returns using company revenue segments<\/h1>\n<\/p>\n\n<\/div>\n\n\n                    <\/div>\n    <\/section>\n<\/div>\n\n<div  class=\"bbg-row-container\">\n    <section class=\"bbg-row  text--black row-padding--top-compact row-padding--bottom-none bbg-row--full-bg-bleed\" data-anchor='row-6a09a630bc361'>\n        \n        \n        <div\n            class=\"bbg-row--content\"\n                    >\n            \n            <p><div\n    class=\"bbg-column bbg-column--width-2\"\n    style=\"\"\n    >\n    \n<\/div><div\n    class=\"bbg-column bbg-column--width-8\"\n    style=\"\"\n    >\n    <p><div\n    class=\"bbg-spacer\"\n        style=\"height: 40px !important\"\n    >\n<\/div><div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><strong>Bloomberg Professional Services<\/strong><\/p>\n\n<\/div>\n    <p class=\"bbg-metadata bbg-metadata--date\">August 15, 2024<\/p>\n<\/p>\n\n<\/div>\n\n\n                    <\/div>\n    <\/section>\n<\/div>\n\n<div  class=\"bbg-row-container\">\n    <section class=\"bbg-row  text--black row-padding--top-none row-padding--bottom-none bbg-row--full-bg-bleed\" data-anchor='row-6a09a630be1c8'>\n        \n        \n        <div\n            class=\"bbg-row--content\"\n                    >\n            \n            <p><div\n    class=\"bbg-column bbg-column--width-2\"\n    style=\"\"\n    >\n    \n<\/div><div\n    class=\"bbg-column bbg-column--width-8\"\n    style=\"\"\n    >\n    <p><div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><span style=\"font-weight: 400\">In quantitative trading, information on the point-in-time revenue segments a business participates in is traditionally used to map relationships across the equity landscape which can be used to augment established trading strategies.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">What these strategies might sometimes overlook is the inherent value in the data as a standalone product. This research report posits and backtests an easy-to-implement long-short investment thesis to show that revenue segmentation data has orthogonal information content on its own.<\/span><\/p>\n\n<\/div>\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Strategy and summary results<\/span><\/h2>\n<p><span style=\"font-weight: 400\">The strategy applied in this report involves investing in businesses that are highly concentrated in a particular revenue segment and selling firms that participate marginally. On each day, we ranked all the firms in our universe by the percentage of revenue they derived from a particular sector, buying the top quantile and selling the bottom.<\/span><\/p>\n\n<\/div>\n<div class=\"bbg-interstitial\" aria-label=\"interstitial\" tabindex=\"0\">\n\t<style>\n\t\t.bbg-interstitial #card_1.bbg-card_hasCta{\n\t\t\tbackground:rgba(0,0,0,0);\n\t\t\tpadding: 104px;\n\t\t\t\n\t\t\t\n\t\t}\n\t\t.bbg-interstitial #card_1.bbg-card_hasCta .bbg-card__content, .bbg-interstitial #card_1.bbg-card_hasCta .bbg-card__content p{\n\t\t\tcolor:inherit;\n\t\t}\n\t\t@media (max-width: 768px) {\n\t\t\t.bbg-interstitial #card_1.bbg-card_hasCta{\n\t\t\t\tpadding: 80px 32px;\n\t\t\t}\n\t\t}\n\t\t@media (max-width: 480px) {\n\t\t\t.bbg-interstitial #card_1.bbg-card_hasCta{\n\t\t\t\tpadding: 80px 18px;\n\t\t\t}\n\t\t}\n\t<\/style>\n\t<div class=\"wpb_content_element bbg-card  bbg-card-dark bbg-card_hasCta has_interstitial\" id=\"card_1\" data-card_type=\"no_image\">\n  \n  \n  <div class=\"bbg-card__innerwrapper\">\n    <div class=\"bbg-card__content\">\n      \n      \n                      <h3 class=\"bbg-card__title\">Empower your work with Enterprise Data & Technology monthly insights<\/h3>\n      \n              <div class=\"bbg-card__wysiwyg bb-wysiwyg\"><p>Sign up for the newsletter<\/p>\n<\/div>\n          <\/div>\n\n          \n<div\n  id=\"cta_3563173553758436940\"\n  class=\"wpb_content_element bbg-cta icon icon-arrow\">\n  <style>\n    \n    \n    \n  <\/style>\n  <div\n    class=\"bbg-cta-link link-holder\"\n    data-links-type=\"cta-links\">\n    <p class=\"bbg-cta-p right\">\n      <a\n        class=\"bbg-cta-link link interstitial_cta\"\n        href=\"https:\/\/www.bloomberg.com\/professional\/insights\/newsletter\/enterprise-data-and-tech\/\"\n        target=\"_blank\"\n        rel=\"\"\n        data-section-name=\"\"\n                role=\"button\"\n        aria-label=\"Learn more\"\n        >\n                <\/a>\n    <\/p>\n  <\/div>\n<\/div>\n\n      <\/div>\n\n  <\/div>\n\n<\/div>\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><span style=\"font-weight: 400\">According to our research, the strategy generates positive returns across seven segments (see chart 5). Of these, the best performing is <\/span><i><span style=\"font-weight: 400\">Advertising &amp; Marketing<\/span><\/i><span style=\"font-weight: 400\">. We normalized these returns against common market factors to verify that there is truly orthogonal information content in the data. Accounting for growth, momentum, size and value, four sectors still generated positive annualized returns (chart 7). These were <\/span><i><span style=\"font-weight: 400\">Beverages, Construction Materials, and Electricity &amp; Gas Marketing &amp; Trading<\/span><\/i><span style=\"font-weight: 400\">. Concentration in these sectors can lead to outperformance.<\/span><\/p>\n\n<\/div>\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Company Segment Fundamentals<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Bloomberg\u2019s <\/span><i><span style=\"font-weight: 400\">Company Segment Fundamentals \u2013 Industry Standardized<\/span><\/i><span style=\"font-weight: 400\"> product details Revenue, Total Balance Sheet Assets, Net Revenue and Operating Income for each reported segment a company is involved in is based on the standardized <\/span><i><span style=\"font-weight: 400\">Bloomberg Industry Classification System<\/span><\/i><span style=\"font-weight: 400\">. The dataset has history back to 2006 and covers 53,000 firms.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1806\" height=\"782\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Extract of Revenue Segmentation Dataset\" title=\"Screenshot-2024-08-14-at-4.43.13\u202fPM\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png 1806w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.13%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1806px) 100vw, 1806px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><span style=\"font-weight: 400\">Chart 1 shows an excerpt of the data with select fields for identification (<\/span><i><span style=\"font-weight: 400\">id_bb_global<\/span><\/i><span style=\"font-weight: 400\">, <\/span><i><span style=\"font-weight: 400\">long_comp_name<\/span><\/i><span style=\"font-weight: 400\"> and <\/span><i><span style=\"font-weight: 400\">fundamentals_ticker<\/span><\/i><span style=\"font-weight: 400\">), point-in-time history (<\/span><i><span style=\"font-weight: 400\">fiscal_year_period<\/span><\/i><span style=\"font-weight: 400\">) and values to create a trading signal (<\/span><i><span style=\"font-weight: 400\">sales_rev_turn <\/span><\/i><span style=\"font-weight: 400\">or <\/span><i><span style=\"font-weight: 400\">is_percentage_of_revenue<\/span><\/i><span style=\"font-weight: 400\">). Chart 2 visualizes the evolution of is_percentage_of_revenue back to 2016\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">As shown, many firms derive relatively stable revenues from their Advertising &amp; Marketing segments. Converting this field into a trading signal is a straightforward process since it is expressed as a percentage.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1910\" height=\"966\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Evolution of IS_PERCENTAGE_OF_REVENUE for Advertising \u000b&amp; Marketing Segment\" title=\"Evolution of IS_PERCENTAGE_OF_REVENUE for Advertising &amp; Marketing Segment\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png 1910w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.39%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1910px) 100vw, 1910px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Backtest details<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Understanding all the revenue segments a company participates in is useful for a few reasons, these include: universe identification for investing in a specific sector or trend, understanding the competitive landscape or isolating growth drivers within a firms business.<\/span><\/p>\n<p><span style=\"font-weight: 400\">These use cases are particularly important for fundamental analysis. But what about more quantitative approaches? To this end, we ran systematic backtests that attempt to unearth uncorrelated market returns that are native to the dataset. The details are as follows:<\/span><\/p>\n<p><b>Thesis<\/b><span style=\"font-weight: 400\">: <\/span><i><span style=\"font-weight: 400\">Companies that are more highly concentrated in a sector outperform those that participate but are less concentrated in terms of revenue<\/span><\/i><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Factor<\/b><span style=\"font-weight: 400\">: <\/span><i><span style=\"font-weight: 400\">IS_PERCENTAGE_OF_REVENUE from each sector<\/span><\/i><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Time Range: <\/b><i><span style=\"font-weight: 400\">2016-2023<\/span><\/i><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Universe<\/b><span style=\"font-weight: 400\">: <\/span><i><span style=\"font-weight: 400\">Russell 2000<\/span><\/i><span style=\"font-weight: 400\"><br \/>\n<\/span><b>Rebalance<\/b><span style=\"font-weight: 400\">: <\/span><i><span style=\"font-weight: 400\">Quarterly<\/span><\/i><\/p>\n<p><span style=\"font-weight: 400\">In each calendar quarter, we split the companies in our universe into quantiles based on the <\/span><i><span style=\"font-weight: 400\">IS_PERCENTAGE_OF_REVENUE <\/span><\/i><span style=\"font-weight: 400\">they derive from the segment in question. If a company has high revenue from the sector, it goes into the top quantile and vice versa. Within each quantile, we are equiweighted and long-only. An example of this, wth five quantiles, is shown in chart 3.<\/span><\/p>\n<p><span style=\"font-weight: 400\">The final output below is a 50:50 long-short based on going long on the quantile with the highest signal and short on the quantile with the lowest signal. In chart 3, the long would be on <\/span><i><span style=\"font-weight: 400\">05 Very High<\/span><\/i><span style=\"font-weight: 400\"> and the short on <\/span><i><span style=\"font-weight: 400\">01 Very Low<\/span><\/i><span style=\"font-weight: 400\">. Bear in mind that some segments have less than 5 quantiles because there isn\u2019t enough diversity of signal to split into 5 evenly sized buckets.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1674\" height=\"1038\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Chart 3: Results of Backtest for Advertising &amp; Marketing Segment\" title=\"Chart 3: Results of Backtest for Advertising &amp; Marketing Segment\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png 1674w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.43.51%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1674px) 100vw, 1674px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1652\" height=\"1084\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Annualized Returns for Each Segment Across Analyzed Universe\" title=\"Annualized Returns for Each Segment Across Analyzed Universe\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png 1652w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.13%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1652px) 100vw, 1652px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><span style=\"font-weight: 400\">The results for each segment are shown in chart 4. With most segments generating sizable absolute annualized returns (&gt;10%), we can conclude that there is orthogonal information content in this dataset. The goal with this type of analysis is to derive a differentiable signal, the fact that most returns are negative does not matter as much since we can simply flip our thesis and therefore our long-short.<\/span><\/p>\n<p><span style=\"font-weight: 400\">For the purposes of this report, we will focus on the sectors that generated positive returns as we want to better understand the benefits (or lack thereof) of revenue concentration within a segment.<\/span><\/p>\n\n<\/div>\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Segments with positive returns<\/span><\/h2>\n<p><span style=\"font-weight: 400\">Chart 5 shows the best segments for concentration.. As these industries tend to be capital intensive (high CapEx),, concentration is required to achieve the economies of scale necessary for high performance. Note that a full investigation of this finding is beyond the scope of this report.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1612\" height=\"976\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Backtests with Positive Annualized Returns\" title=\"Screenshot-2024-08-14-at-4.44.22\u202fPM\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 1612w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 100w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.22%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1612px) 100vw, 1612px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<p><span style=\"font-weight: 400\">Chart 6 shows the cumulative returns of the long-short strategy over time for each of the sectors shown in chart 5. <\/span><i><span style=\"font-weight: 400\">Construction Materials <\/span><\/i><span style=\"font-weight: 400\">and <\/span><i><span style=\"font-weight: 400\">Electricity &amp; Gas Marketing &amp; Trading <\/span><\/i><span style=\"font-weight: 400\">show similar returns as the S&amp;P 500 over this period, <\/span><i><span style=\"font-weight: 400\">Advertising &amp; Marketing<\/span><\/i><span style=\"font-weight: 400\"> far outstrips the index.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-center\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1716\" height=\"1012\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Cumulative Returns Over Time\" title=\"Cumulative Returns Over Time\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 1716w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 100w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.44.34%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1716px) 100vw, 1716px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Factor exposure analysis<\/span><\/h2>\n<p><span style=\"font-weight: 400\">On the whole, returns are positive. But how can we be sure that these profiles are a direct result of the signal we chose and not because of high factor exposure to something like momentum or growth? To verify that our strategy cannot be explained by exposure to common market factors, we normalized against momentum, growth, value and size.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">Chart 7 shows the final results. In sum, the four sectors below all generated positive annualized returns even after accounting for these common market factors.<\/span><\/p>\n\n<\/div>\n<div id=\"\" class=\"wpb_content_element bbg-single-image align-left\">\n    <figure class=\"bbg-single-image__figure\" style=\"max-width:100%\">\n                <img loading=\"lazy\" decoding=\"async\" width=\"1676\" height=\"1074\" src=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png\" class=\"bbg-single-image__image attachment-full\" alt=\"Best Performing Backtests That Still Have Positive Returns After \u000bNormalizing for Style Factors\" title=\"Best Performing Backtests That Still Have Positive Returns After Normalizing for Style Factors\" srcset=\"https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png 1676w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png 552w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png 800w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png 768w, https:\/\/assets.bbhub.io\/image\/v1\/resize?width=auto&amp;type=webp&amp;url=https:\/\/assets.bbhub.io\/professional\/sites\/41\/Screenshot-2024-08-14-at-4.45.21%E2%80%AFPM.png 1536w\" sizes=\"auto, (max-width: 1676px) 100vw, 1676px\" \/>\n        \n            <\/figure>\n<\/div>\n\n<div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2><span style=\"font-weight: 400\">Conclusion<\/span><\/h2>\n<p><span style=\"font-weight: 400\">As demonstrated, point-in-time revenue segmentation data can provide orthogonal information content. This is an additional benefit to the more common use cases of fundamental business analysis and building knowledge graphs. This dataset is available for trial through data.bloomberg.com.<\/span><\/p>\n\n<\/div>\n\n<\/div>\n\n\n                    <\/div>\n    <\/section>\n<\/div>\n\n<div  class=\"bbg-row-container\">\n    <style>section[data-anchor=row-6a09a630d1d75]::before {\n\t\t\t\tbackground-color: #eeeeee;\n\t\t\t}<\/style>\n    <section class=\"bbg-row bg--custom-color  bg--eeeeee text--black bbg-row--full-bg-bleed\" data-anchor='row-6a09a630d1d75'>\n        \n        \n        <div\n            class=\"bbg-row--content\"\n                    >\n            \n            <div\n    class=\"bbg-column\"\n    style=\"\"\n    >\n    <div\n\tclass=\"bb-wysiwyg\"\n\t\t>\n\t<h2>Recommended for you<\/h2>\n\n<\/div>\n<div\n    class=\"bbg-spacer\"\n        style=\"height: 24px !important\"\n    >\n<\/div><script>\n    window.feed = window.feed || {};\n    window.feed['6a09a630d4939'] = 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