{"id":14213,"date":"2022-08-24T13:14:02","date_gmt":"2022-08-24T17:14:02","guid":{"rendered":"https:\/\/jasonapollovoss.com\/web\/?p=14213"},"modified":"2025-09-05T13:56:06","modified_gmt":"2025-09-05T19:56:06","slug":"data-beats-the-sp-500-decision-rule-i","status":"publish","type":"post","link":"https:\/\/jasonapollovoss.com\/web\/2022\/08\/24\/data-beats-the-sp-500-decision-rule-i\/","title":{"rendered":"DATA BEATS THE S&P 500 – Decision Rule I"},"content":{"rendered":"

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Deception And Truth Analysis (D.A.T.A.), Inc. has spent almost a decade working with deception scientists<\/span>[1]<\/a>and studying multiple methods of deception and truth detection. Based on this knowledge we developed Deception And Truth Analysis, a proprietary algorithm based on scientific research and making use of textual data to rapidly identify deceptiveness and truthfulness in business communications.<\/span><\/span><\/p>\n

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Our Methodology<\/strong><\/span><\/h3>\n<\/div>\n

A practical demonstration of its power is our recent work where use of D.A.T.A.\u2019s algorithm was able to best the performance of the Standard & Poor\u2019s 500 Index. Using the 500 components of the S&P 500 we created a simple decision rule: at the start of each new year simply\u00a0do not buy<\/em>\u00a0the 50 firms (10% of firms) whose level of deception was assessed as highest in the previous year. More specifically the methodology is, as follows:<\/span><\/p>\n

1. Starting with 2008 and continuing through 2021 each of the 500 S&P 500 components\u2019 10(k)s were assessed by D.A.T.A. to create a D.A.T.A. Score for each firm. DATA Scores range between -100% and +100% with any negative score indicating a level of deceptiveness and any positive score indicating a level of truthfulness, in the aggregate.<\/span><\/p>\n

2. Then, on the first trading day of the subsequent year we purchase the 450 S&P 500 components with the highest D.A.T.A. Score (i.e. those assessed as most truthful), and do not purchase the 50 S&P 500 components with the lowest D.A.T.A. Score (i.e. those assessed as most deceptive). Each of the 450 purchased companies is equal weighted in a portfolio and held for the entire year. The average lag from assessment by a D.A.T.A. Score to purchase is 9.08 months.<\/span><\/p>\n

3. During 2009 each of the 500 S&P 500 companies issue annual 10(k) reports again which are assessed by D.A.T.A. Scores.<\/span><\/p>\n

4. On 31 December 2009 the portfolio of most the truthful 450 equal-weighted S&P 500 components from 2008 is sold.<\/span><\/p>\n

5. On the first trading day of 2010, we purchase the 450 S&P 500 components with the highest 2009 D.A.T.A. Scores (i.e. the most truthful), and do not purchase the 50 S&P 500 components with the lowest D.A.T.A. Scores (i.e. the most deceptive). Each of the 450 purchased companies is equal weighted in a portfolio. This is the same as in step 2, above.<\/span><\/p>\n

6. This technique of D.A.T.A. Scores being generated for each S&P 500 components’ 10(k) documents, then waiting until the start of the next year to buy the prior year\u2019s 450 firms assessed as most truthful\/having the highest D.A.T.A. Scores, is repeated through until 31 December 2021.<\/span><\/p>\n

Note: A separate analysis was done where instead of selling the portfolio of 450 names on 31 December each year, they are held for 5 years. But the methodology is identical otherwise.<\/span><\/p>\n

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Results of Decision Rule I<\/strong><\/span><\/h3>\n<\/div>\n

Here are the results of our simple decision rule just described:<\/span><\/p>\n

1. Where the strategy is to not buy the 50 firms with the lowest D.A.T.A. Scores\/those assessed as most deceptive during the year:<\/span><\/h4>\n