And momentum.
And equity risk premium. But that's argument by definition.
And...
From Matt Levine at Bloomberg:
...Moneyball, but for money.
Did you know that you can use statistics to pick stocks? Hmm, you did? Well, did you know that you can sort of squint at those statistics and pretend that they're baseball statistics? Why would you want to do that, you ask? I don't know. Baseball! Sports metaphor! Just buy some stocks. That seems to be the thesis of a Goldman Sachs equity research note, and good lord. Elsewhere, Gawker's giving stock tips.
Here, on the other hand (via Tyler Cowen), is a new NBER paper (ungated PDF here) about research into the cross-section of expected stock market returns, finding that "most claimed research findings are likely false." The intuitive idea is that hundreds of academics (and hedge funds) write hundreds of papers trying to find factors that explain stock market returns and that can be used to outperform the broad market:Sorry, no footnotes.
We observe a dramatic increase in factor discoveries during the last decade. In the early period from 1980 to 1991, only about one factor is discovered per year. This number has grown to around five in the 1991-2003 period, during which a number of papers, such as Fama and French (1992), Carhart (1997) and Pastor and Stambaugh (2003), spurred interest in studying cross-sectional return patterns. In the last nine years, the annual factor discovery rate has increased sharply to around 18. In total, 162 factors were discovered in the past 9 years, roughly doubling the 90 factors discovered in all previous years.But since they keep mining the same data for the same sorts of factors, their statistical thresholds for significance are probably too low. If you use a t-ratio of 3, as the authors advocate, rather than the more popular 2, you find that most of the factors that have been identified don't actually work, for some value of "actually."...MORE
