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TL;DR (ChatGPT) The article discusses a 2016 paper published by investment firm Research Affiliates (RA) on "smart beta" investing, which claimed that several

TL;DR (ChatGPT) The article discusses a 2016 paper published by investment firm Research Affiliates (RA) on "smart beta" investing, which claimed that several factors such as size, quality, momentum, and low beta had low value characteristics relative to history and would likely underperform in the near future. However, a recent victory claim by RA is based on a chart that is entirely driven by the low beta factor, and the lowest performance is from the value factor, which RA suggested investors overweight. The article also compares RA's factors with Fama-French factors and factors published by AQR Capital Management, showing that details in factor construction make a great difference in analysis. The author argues that factors are not meant to be held in isolation but to be added to market portfolios and that their value is as much in reducing risk as in increasing return.

helsinki 4y ago
From Bard: The text is about the 2016 paper "How Can 'Smart Beta' Go Horribly Wrong?" by Rob Arnott and his colleagues at Research Affiliates, or RA. The paper argued that four specific factors - size, quality, momentum and low beta - had very low value characteristics relative to history. In other words, to get exposure to those factors you had to buy stocks with poor value characteristics, such as high price to book value ratios, and that in similar periods in the past those factors had underperformed. The paper's title and some of its rhetoric was that factors would crash in the near future, but the actual recommendations were more modest: investors should readjust expectations for lower factor returns from non-value factors and increase emphasis on value. In 2022, RA published a follow-up paper, "Revisiting Our 'Horribly Wrong' Paper: That Was Then, This Is Now." In this paper, they claimed victory, arguing that their 2016 predictions had come true. However, the evidence they presented was not convincing. The chart they used to support their claim was entirely driven by the low beta factor. When that factor was removed, there was no obvious trend. Moreover, the lowest performance was from the value factor - the one that RA suggested investors overweight. Finally, while some factors in some markets would have disappointed investors over the period, none can be described as horribly wrong. In conclusion, the 2016 paper by RA was not as prescient as its authors claimed. Their follow-up paper did not provide convincing evidence that their 2016 predictions had come true.

helsinki 4y ago

From Bard: The text is about the 2016 paper "How Can 'Smart Beta' Go Horribly Wrong?" by Rob Arnott and his colleagues at Research Affiliates, or RA. The paper argued that four specific factors - size, quality, momentum and low beta - had very low value characteristics relative to history. In other words, to get exposure to those factors you had to buy stocks with poor value characteristics, such as high price to book value ratios, and that in similar periods in the past those factors had underperformed. The paper's title and some of its rhetoric was that factors would crash in the near future, but the actual recommendations were more modest: investors should readjust expectations for lower factor returns from non-value factors and increase emphasis on value. In 2022, RA published a follow-up paper, "Revisiting Our 'Horribly Wrong' Paper: That Was Then, This Is Now." In this paper, they claimed victory, arguing that their 2016 predictions had come true. However, the evidence they presented was not convincing. The chart they used to support their claim was entirely driven by the low beta factor. When that factor was removed, there was no obvious trend. Moreover, the lowest performance was from the value factor - the one that RA suggested investors overweight. Finally, while some factors in some markets would have disappointed investors over the period, none can be described as horribly wrong. In conclusion, the 2016 paper by RA was not as prescient as its authors claimed. Their follow-up paper did not provide convincing evidence that their 2016 predictions had come true.