{"id":8909,"date":"2017-03-13T15:40:16","date_gmt":"2017-03-13T15:40:16","guid":{"rendered":"http:\/\/www.t3live.com\/blog\/?p=8909"},"modified":"2017-03-13T15:40:16","modified_gmt":"2017-03-13T15:40:16","slug":"qa-how-to-judge-an-economic-data-point","status":"publish","type":"post","link":"https:\/\/blog.t3live.com\/2017\/03\/13\/qa-how-to-judge-an-economic-data-point\/","title":{"rendered":"Q&A: How to Judge an Economic Data Point"},"content":{"rendered":"

Dear Michael,<\/em><\/p>\n

How can you call the jobs report ‘Meh'?<\/a><\/strong><\/span><\/em><\/p>\n

NFP came in at +235K and beat the street expectations.<\/em><\/p>\n

How is that meh?<\/em><\/p>\n

-Randy<\/em><\/p>\n

Dear Randy,<\/p>\n

The 235K headline number was fine, but that's not the totality of the report.<\/p>\n

Average hourly earnings grew by just 0.2% vs. the 0.3% consensus, which offset the impact of the headline number beat.<\/p>\n

Plus, you have the remember that expectations were running very high headed into the report.<\/p>\n

On Wednesday, the ADP employment number beat by a mile<\/a>.<\/strong><\/span><\/p>\n

In addition, bonds have been sinking while the US dollar has been rising, indicating that traders have been anticipating the type of strong economic data that has bolstered the Fed's case for rate hikes.<\/p>\n

How to Look at Economic Data Points<\/strong><\/p>\n

In isolation, economic data points are completely useless.<\/p>\n

To properly understand them, you must bring them into context by doing 2 things:<\/p>\n

    \n
  1. Measure them against expectations as set by economists and the market itself.<\/li>\n
  2. Measure them against expectations as set by the market itself.<\/li>\n<\/ol>\n

    First, let's look at expectations as set by economists.<\/p>\n

    News and data providers like Bloomberg and Reuters collect forecasts from various economists to determine a consensus\u00a0forecast, which is a rough approximation of the market's expectations.<\/p>\n

    With economic statistics, the consensus forecast is determined by taking a median of the data set.<\/p>\n

    Now, for last Friday's jobs report, the consensus forecast (the median) was 190K.<\/p>\n

    So 235K was a beat.<\/p>\n

    Had the consensus forecast been 300K, 235K would have been disappointment.<\/p>\n

     <\/p>\n

    However, we must also take the actual market's behavior, because they also play into expectations.<\/p>\n

    As I stated earlier, bonds were falling headed into the report.<\/p>\n

    This is because a strong report would support the case for more Fed rate hikes, which would push down bonds.<\/p>\n

    But what if bonds rallied ahead of the jobs numbers?<\/p>\n

    That would indicate that\u00a0traders expected a miss in the jobs number.<\/p>\n

    Admittedly, this is more art than science, and it's generally only applicable to major economic data points like NFP, GDP, CPI, etc.<\/p>\n

    But by focusing on how economic data is reported relative to expectations, you can get a sense of just how ‘good' that data actually is.<\/p>\n

    And just so you don't forget, I'll say it again:<\/p>\n

    In isolation, economic data points are completely useless.<\/p>\n

    To properly understand them, you must bring them into context by doing 2 things:<\/p>\n

      \n
    1. Measure them against expectations as set by economists and the market itself.<\/li>\n
    2. Measure them against expectations as set by the market itself.<\/li>\n<\/ol>\n

       <\/p>\n

       <\/p>\n","protected":false},"excerpt":{"rendered":"

      Dear Michael, How can you call the jobs report ‘Meh’? NFP came in at +235K and beat the street expectations. How is that meh? -Randy Dear Randy, The 235K headline number was fine, but that’s not the totality of the report. Average hourly earnings grew by just 0.2% vs. the 0.3% consensus, which offset the impact of the headline number beat. Plus, you have the remember that expectations were running very high headed into the report. On Wednesday, the ADP employment number beat by a mile. In addition, bonds have been sinking while the US dollar has been rising, indicating that traders have been anticipating the type of strong economic data that has bolstered the Fed’s case for rate hikes. How to Look at Economic Data Points In isolation, economic data points are completely useless. To properly understand them, you must bring them into context by doing 2 things: Measure them against expectations as set by economists and the market itself. Measure them against expectations as set by the market itself. First, let’s look at expectations as set by economists. News and data providers like Bloomberg and Reuters collect forecasts from various economists to determine a consensus\u00a0forecast, which is a rough approximation of the market’s expectations. With economic statistics, the consensus forecast is determined by taking a median of the data set. Now, for last Friday’s jobs report, the consensus forecast (the median) was 190K. So 235K was a beat. Had the consensus forecast been 300K, 235K would have been disappointment.   However, we must also take the actual market’s behavior, because they also play into expectations. As I stated earlier, bonds were falling headed into the report. This is because a strong report would support the case for more Fed rate hikes, which would push down bonds. But what if bonds rallied ahead of the jobs numbers? That would indicate that\u00a0traders expected a miss in the jobs number. Admittedly, this is more art than science, and it’s generally only applicable to major economic data points like NFP, GDP, CPI, etc. But by focusing on how economic data is reported relative to expectations, you can get a sense of just how ‘good’ that data actually is. And just so you don’t forget, I’ll say it again: In isolation, economic data points are completely useless. To properly understand them, you must bring them into context by doing 2 things: Measure them against expectations as set by economists and the market itself. Measure them against expectations as set by the market itself.    <\/p>\n","protected":false},"author":2,"featured_media":4094,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[564,142,566,565],"class_list":["post-8909","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","tag-economic-data-points","tag-nfp","tag-nonfarm-payrolls-report","tag-statistics"],"_links":{"self":[{"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/posts\/8909","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/comments?post=8909"}],"version-history":[{"count":1,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/posts\/8909\/revisions"}],"predecessor-version":[{"id":8911,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/posts\/8909\/revisions\/8911"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/media\/4094"}],"wp:attachment":[{"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/media?parent=8909"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/categories?post=8909"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.t3live.com\/wp-json\/wp\/v2\/tags?post=8909"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}