{"id":14298,"date":"2023-05-30T14:43:32","date_gmt":"2023-05-30T18:43:32","guid":{"rendered":"https:\/\/jasonapollovoss.com\/web\/?p=14298"},"modified":"2025-09-05T15:42:13","modified_gmt":"2025-09-05T21:42:13","slug":"use-case-2-identifying-state-changes","status":"publish","type":"post","link":"https:\/\/jasonapollovoss.com\/web\/2023\/05\/30\/use-case-2-identifying-state-changes\/","title":{"rendered":"Use Case 2: Identifying State Changes"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||” theme_builder_area=”post_content”][et_pb_text admin_label=”Text” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n

This is our second article providing an overview of Use Cases for Deception And Truth Analysis. In this article we cover Identifying State Changes to ensure that you are not caught off-guard in your investment research or due-diligence. In other words, D.A.T.A. can help you identify very early when either storm clouds are gathering, or when a company is emerging from a previous stormy period.<\/span><\/p>\n

As a review, there are five major due-diligence steps in almost every investment process. They are:<\/span><\/p>\n

    \n
  1. Establishing your investible universe.<\/a><\/span><\/li>\n
  2. Relying on high-level criteria to identify state changes.<\/strong><\/span><\/li>\n
  3. Deeper dive analyses that establish an investment thesis.<\/a><\/span><\/li>\n
  4. The buy-sell decision.<\/a><\/span><\/li>\n
  5. Ongoing due-diligence of your investments.<\/a><\/span><\/li>\n<\/ol>\n

    Deception And Truth Analysis (D.A.T.A.) provides a powerful assist in each of the above steps.<\/span><\/p>\n

    \n

    <\/strong><\/span><\/h4>\n

    DATA Score Y\/Y Change<\/strong><\/span><\/h3>\n<\/div>\n

    Recall that our\u00a0DATA Scores are predictive of future stock prices<\/a>, on average. Because of this, investors ought to focus on identifying state changes in a company\u2019s documents\u2019 DATA Scores as represented by our year on year change, \u201cDATA Score Y\/Y Change.\u201d<\/span><\/p>\n

    For example, Fair Isaac Corporation (ticker: FICO) recently saw a dramatic change in its DATA Score for its first quarter 10(q). Last year\u2019s 2022 document had a DATA Score of 23.95%; or Truthful by more than one standard deviation. By contrast its 2023 10(q) has a DATA Score of 1.86%, or just barely Truthful.<\/span><\/p>\n

    This change is enough to move it being the most truthful firm in the US midcap space, to being in the bottom quartile. To put this in perspective, at the time of this writing our DATAbase coverage universe includes 4,960 companies and this change is the 15th worst.<\/span><\/p>\n

    Again, because DATA Scores are predictive of future stock prices, on average, if Fair Isaac is in your coverage universe then you have strong evidence that something dramatic has happened. Having identified this state change you should dig deeper.<\/span><\/p>\n

    Our DATAbase REDline premium product allows you to do just that. Because of D.A.T.A.\u2019s ability to rapidly surface actionable investment insights we are a force multiplier for your work. In just two clicks you can easily see that FICO\u2019s most deceptive fragment in its 2023 Q1 10(q) regards the company\u2019s annual recurring revenues (see below).\u00a0<\/span><\/p>\n

    \n
    \n
    \"Use<\/span><\/div>\n<\/div>
    Use Case 2 – Identifying State Changes – FICO<\/span><\/figcaption><\/figure>\n

    \u00a0\u00a0<\/span><\/p>\n

    Equipped with this information you can now dig a little deeper into what is happening at FICO. Furthermore, you can ask better questions of management at the company to ensure that any concerns you have are addressed.<\/span><\/p>\n

    Last, and as an aside, the number of pages in FICO\u2019s 2023 10(q) have significantly dropped from over 90 pages in 2022 to just 51.<\/span><\/p>\n

    <\/strong><\/span><\/p>\n

    Average DATA Score Deceptive\/Truthful<\/strong><\/span><\/h3>\n

    Next up in terms of identifying state changes is looking at several additional D.A.T.A. outputs, namely:<\/span><\/p>\n

      \n
    1. % Deceptive Fragments<\/span><\/li>\n
    2. Average DATA Score Deceptive<\/span><\/li>\n
    3. % Truthful Fragments<\/span><\/li>\n
    4. Average DATA Score Truthful<\/span><\/li>\n<\/ol>\n

      As an example, let\u2019s focus in on Deep Green Waste & Recycling, Inc. (ticker: DGWR). First, its DATA Score Y\/Y Change for its Q1 2023 10(q) is -16.93%, while its DATA Score is -6.29%. In other words, DGWR has switched from being a truthful company to a deceptive company in just one year\u2019s time. But let\u2019s dig in a little deeper.<\/span><\/p>\n

      \n
      \n
      \"Use<\/span><\/div>\n<\/div>
      Use Case 2 – Identifying State Changes – DGWR<\/span><\/figcaption><\/figure>\n

      \u00a0\u00a0<\/span><\/p>\n

      For DGWR it has the following D.A.T.A. outputs for its first quarter 2023 10(q):<\/span><\/p>\n

        \n
      1. % Deceptive Fragments = 44.44%<\/span><\/li>\n
      2. Average DATA Score Deceptive = -45.99%<\/span><\/li>\n
      3. % Truthful Fragments = 55.56%<\/span><\/li>\n
      4. Average DATA Score Truthful = +22.17%<\/span><\/li>\n<\/ol>\n

        As you can see DGWR is being truthful more than half of the time in its document, or 55.56% of the time. While this assessment may be comforting, as you can see from the figures above, when DGWR is being deceptive their deception is twice the magnitude (-45.99%) as when they are being truthful (+22.17%).<\/span><\/p>\n

        When these D.A.T.A. outputs are coupled with the DATA Score Y\/Y Change, a picture rapidly emerges that helps investors to rapidly identify state changes in companies, and to identify actionable investment insights. If you are curious about DGWR, DATAbase REDline reveals that the company appears to have had a change in CEO and the fragments in which they are being most deceptive have to do with a raft of equity issuance at the company.<\/span><\/p>\n

        Perhaps the equity issuance is in response to these change in the C-suite. But maybe they are not. Deception And Truth Analysis is a screening tool and not a diagnostic. In other words, equipped with our analytics you now have a force multiplier effect that allows you to rapidly surface actional investment insights.<\/span><\/p>\n

        \n

        <\/strong><\/span><\/h4>\n

        Getting Creative<\/strong><\/span><\/h3>\n<\/div>\n

        As a Client of D.A.T.A.\u2019s you can access our analytics via API or .csv export among multiple methods. It is entirely possible that you can set up a screen for yourself in which you set a pain threshold in terms of the DATA Score Y\/Y Change that you are looking for. These could include:<\/span><\/p>\n

        \u00b7 Any change that moves a company from a truthful\/positive DATA Score to a deceptive\/negative DATA Score.<\/span><\/p>\n

        \u00b7 Any absolute % change that is greater than |10%|.<\/span><\/p>\n

        \u00b7 And so on.<\/span><\/p>\n

        Furthermore, you could also set up your own ratios that relate our analytics to one another in a meaningful way. For example, you could set up a ratio that is something like: (% Truthful Fragments x Average DATA Score Truthful) dived by (% Deceptive Fragments x Average DATA Score Deceptive). You may conduct your own tests of the predictability of this ratio and find that any ratio greater than 1.2 is strongly predictive of future stock price returns.<\/span><\/p>\n

        The possibilities are numerous, and we encourage you to have some fun!<\/span><\/p>\n

        \n

        <\/strong><\/span><\/h4>\n

        Conclusion<\/strong><\/span><\/h3>\n<\/div>\n

        Deception And Truth Analysis\u2019 analytics, including \u2018DATA Score Y\/Y Change,\u2019 \u2018% Deceptive Fragments,\u2019 \u2018Average DATA Score Deceptive,\u2019 \u2018% Truthful Fragments,\u2019 and \u2018Average DATA Score Truthful\u2019 all provide valuable means of identifying state changes in companies\u2019 documents. Using these D.A.T.A. analytics is a force multiplier that allows you to rapidly surface actionable investment insights. This is true because DATA Scores are predictive of future business outcomes, and usually stock prices, too.<\/span><\/p>\n

        [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

        This is our second article providing an overview of Use Cases for Deception And Truth Analysis. In this article we cover Identifying State Changes to ensure that you are not caught off-guard in your investment research or due-diligence. In other words, D.A.T.A. can help you identify very early when either storm clouds are gathering, or […]<\/p>\n","protected":false},"author":2,"featured_media":14299,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"\r\n\r\nBy Jason A. Voss, CFA<\/em><\/span>\r\n\r\nThis is our second article providing an overview of Use Cases for Deception And Truth Analysis. In this article we cover Identifying State Changes to ensure that you are not caught off-guard in your investment research or due-diligence. In other words, D.A.T.A. can help you identify very early when either storm clouds are gathering, or when a company is emerging from a previous stormy period.<\/span>\r\n\r\nAs a review, there are five major due-diligence steps in almost every investment process. They are:<\/span>\r\n

          \r\n \t
        1. Establishing your investible universe.<\/a><\/span><\/li>\r\n \t
        2. Relying on high-level criteria to identify state changes.<\/strong><\/span><\/li>\r\n \t
        3. Deeper dive analyses that establish an investment thesis.<\/a><\/span><\/li>\r\n \t
        4. The buy-sell decision.<\/a><\/span><\/li>\r\n \t
        5. Ongoing due-diligence of your investments.<\/a><\/span><\/li>\r\n<\/ol>\r\nDeception And Truth Analysis (D.A.T.A.) provides a powerful assist in each of the above steps.<\/span>\r\n
          \r\n

          DATA Score Y\/Y Change<\/strong><\/span><\/h4>\r\n<\/div>\r\nRecall that our\u00a0DATA Scores are predictive of future stock prices<\/a>, on average. Because of this, investors ought to focus on identifying state changes in a company\u2019s documents\u2019 DATA Scores as represented by our year on year change, \u201cDATA Score Y\/Y Change.\u201d<\/span>\r\n\r\nFor example, Fair Isaac Corporation (ticker: FICO) recently saw a dramatic change in its DATA Score for its first quarter 10(q). Last year\u2019s 2022 document had a DATA Score of 23.95%; or Truthful by more than one standard deviation. By contrast its 2023 10(q) has a DATA Score of 1.86%, or just barely Truthful.<\/span>\r\n\r\nThis change is enough to move it being the most truthful firm in the US midcap space, to being in the bottom quartile. To put this in perspective, at the time of this writing our DATAbase coverage universe includes 4,960 companies and this change is the 15th worst.<\/span>\r\n\r\nAgain, because DATA Scores are predictive of future stock prices, on average, if Fair Isaac is in your coverage universe then you have strong evidence that something dramatic has happened. Having identified this state change you should dig deeper.<\/span>\r\n\r\nOur DATAbase REDline premium product allows you to do just that. Because of D.A.T.A.\u2019s ability to rapidly surface actionable investment insights we are a force multiplier for your work. In just two clicks you can easily see that FICO\u2019s most deceptive fragment in its 2023 Q1 10(q) regards the company\u2019s annual recurring revenues (see below).\u00a0<\/span>\r\n
          \r\n
          \r\n
          \"Use<\/span><\/div>\r\n<\/div>\r\n
          Use Case 2 - Identifying State Changes - FICO<\/span><\/figcaption><\/figure>\r\n\u00a0\u00a0<\/span>\r\n\r\nEquipped with this information you can now dig a little deeper into what is happening at FICO. Furthermore, you can ask better questions of management at the company to ensure that any concerns you have are addressed.<\/span>\r\n\r\nLast, and as an aside, the number of pages in FICO\u2019s 2023 10(q) have significantly dropped from over 90 pages in 2022 to just 51.<\/span>\r\n\r\nAverage DATA Score Deceptive\/Truthful<\/strong><\/span>\r\n\r\nNext up in terms of identifying state changes is looking at several additional D.A.T.A. outputs, namely:<\/span>\r\n
            \r\n \t
          1. % Deceptive Fragments<\/span><\/li>\r\n \t
          2. Average DATA Score Deceptive<\/span><\/li>\r\n \t
          3. % Truthful Fragments<\/span><\/li>\r\n \t
          4. Average DATA Score Truthful<\/span><\/li>\r\n<\/ol>\r\nAs an example, let\u2019s focus in on Deep Green Waste & Recycling, Inc. (ticker: DGWR). First, its DATA Score Y\/Y Change for its Q1 2023 10(q) is -16.93%, while its DATA Score is -6.29%. In other words, DGWR has switched from being a truthful company to a deceptive company in just one year\u2019s time. But let\u2019s dig in a little deeper.<\/span>\r\n
            \r\n
            \r\n
            \"Use<\/span><\/div>\r\n<\/div>\r\n
            Use Case 2 - Identifying State Changes - DGWR<\/span><\/figcaption><\/figure>\r\n\u00a0\u00a0<\/span>\r\n\r\nFor DGWR it has the following D.A.T.A. outputs for its first quarter 2023 10(q):<\/span>\r\n
              \r\n \t
            1. % Deceptive Fragments = 44.44%<\/span><\/li>\r\n \t
            2. Average DATA Score Deceptive = -45.99%<\/span><\/li>\r\n \t
            3. % Truthful Fragments = 55.56%<\/span><\/li>\r\n \t
            4. Average DATA Score Truthful = +22.17%<\/span><\/li>\r\n<\/ol>\r\nAs you can see DGWR is being truthful more than half of the time in its document, or 55.56% of the time. While this assessment may be comforting, as you can see from the figures above, when DGWR is being deceptive their deception is twice the magnitude (-45.99%) as when they are being truthful (+22.17%).<\/span>\r\n\r\nWhen these D.A.T.A. outputs are coupled with the DATA Score Y\/Y Change, a picture rapidly emerges that helps investors to rapidly identify state changes in companies, and to identify actionable investment insights. If you are curious about DGWR, DATAbase REDline reveals that the company appears to have had a change in CEO and the fragments in which they are being most deceptive have to do with a raft of equity issuance at the company.<\/span>\r\n\r\nPerhaps the equity issuance is in response to these change in the C-suite. But maybe they are not. Deception And Truth Analysis is a screening tool and not a diagnostic. In other words, equipped with our analytics you now have a force multiplier effect that allows you to rapidly surface actional investment insights.<\/span>\r\n
              \r\n

              Getting Creative<\/strong><\/span><\/h4>\r\n<\/div>\r\nAs a Client of D.A.T.A.\u2019s you can access our analytics via API or .csv export among multiple methods. It is entirely possible that you can set up a screen for yourself in which you set a pain threshold in terms of the DATA Score Y\/Y Change that you are looking for. These could include:<\/span>\r\n\r\n\u00b7 Any change that moves a company from a truthful\/positive DATA Score to a deceptive\/negative DATA Score.<\/span>\r\n\r\n\u00b7 Any absolute % change that is greater than |10%|.<\/span>\r\n\r\n\u00b7 And so on.<\/span>\r\n\r\nFurthermore, you could also set up your own ratios that relate our analytics to one another in a meaningful way. For example, you could set up a ratio that is something like: (% Truthful Fragments x Average DATA Score Truthful) dived by (% Deceptive Fragments x Average DATA Score Deceptive). You may conduct your own tests of the predictability of this ratio and find that any ratio greater than 1.2 is strongly predictive of future stock price returns.<\/span>\r\n\r\nThe possibilities are numerous, and we encourage you to have some fun!<\/span>\r\n
              \r\n

              Conclusion<\/strong><\/span><\/h4>\r\n<\/div>\r\nDeception And Truth Analysis\u2019 analytics, including \u2018DATA Score Y\/Y Change,\u2019 \u2018% Deceptive Fragments,\u2019 \u2018Average DATA Score Deceptive,\u2019 \u2018% Truthful Fragments,\u2019 and \u2018Average DATA Score Truthful\u2019 all provide valuable means of identifying state changes in companies\u2019 documents. Using these D.A.T.A. analytics is a force multiplier that allows you to rapidly surface actionable investment insights. This is true because DATA Scores are predictive of future business outcomes, and usually stock prices, too.<\/span>","_et_gb_content_width":"","footnotes":""},"categories":[3,465],"tags":[463],"class_list":["post-14298","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-the-blog","category-d-a-t-a","tag-use-cases"],"_links":{"self":[{"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/posts\/14298","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/comments?post=14298"}],"version-history":[{"count":0,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/posts\/14298\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/media\/14299"}],"wp:attachment":[{"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/media?parent=14298"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/categories?post=14298"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jasonapollovoss.com\/web\/wp-json\/wp\/v2\/tags?post=14298"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}