Campbell R. Harvey, Liu and Zhu present an analysis where they find that academic papers on cross sectional stock market factors are apparently about as untrustworthy as a large portion of medical literature. (HT: MR) Published papers in medical literature and on stock market factors suffer from data mining and publication bias issues where only positive results are analyzed and published. Not finding something is rarely seen as an accomplishment in the academic world. So after thousands of analysis are run, the paper that finds something that is only 1% likely to be a misinterpretation of random noise if you only did the study once - is likely to be exactly that - random noise.
However, it's interesting that even with this bias there are still some very significant results to be found in cross sectional analysis of stocks. The stand out stock market cross sectional factors are value and momentum, which work well enough that even if they have been found by an explicit data mining processes the returns are good enough to suggest that they aren't just random noise.
The explanation behind value working is simple. Stocks trading at the largest premium to their book values are overvalued by overconfident market participants on average while stocks trading at lower book values are a bargain more often than not. The value approach is well known, with Warren Buffett being the prime example of a successful investor who utlizes the value approach.
Momentum is more interesting because it is less popular among the public. Adherents to momentum have often been denigrated as rash speculators, in contrast to the more stable and patient value investors. Momentum is the idea that prior price movements are preditive of relative future returns. This seems to be a violation of the weakest form of the efficient market hypothesis. Adherants to the EMH call momentum (and value for that matter) a "risk factor" - implying that stocks with higher momentum have a higher risk than low momentum stocks which keeps their theories from completely falling apart.
But the actual mechanism behind momentum is more subtle- a fast growing company doesn't become a sensation overnight. It takes time for a company to overtake and replace its rivals even if the new company is better in almost every way. Along the way, small pieces of information will come out regarding the increasing success of the company and the well performing stock will be bought by more managers. The extra risk is that a market shock could induce aggressive managers to all sell their holdings at once or worse, change the environment that was making the company so succesful in the first place.
Momentum, value and small stocks are three of the classic cross sectional explanatory factors, with data on their performance available for download at Ken French's database - so the lack of significance of the small stock outperformance as determined by Harvey et al is notable. I've touched before on how public stock market size premium is likely to be lower than it has been in the past due to high valuations in the pre-IPO environment, but this suggests that looking to small stocks as a significant explanatory factor of performance might have always been a mistake.
Size shouldn't be ignored - many people have found that value works much better among smaller stocks.
The table above from Cliff Asness's white paper shows that momentum works slightly better among small cap stocks, though this result may occur more because small cap stocks are more volatile in general and not because momentum works any worse in the large cap world after adjusting for volatility.
Momentum works in multiple asset classes, and should be of interest to those who are pre-IPO investors. Everyone knows to invest in fast growing companies and to avoid companies who have had to take down rounds. An explicitly systematic momentum approach in pre-IPO companies is likely to generate significant alpha - particuarly in our current investment environment.
So when the value perspective of the 17 billion dollar pre-money Uber valuation can make the deal look ridiculous*, the investor who respects the momentum factor should be paying closer attention. After all, it seems far more likely that the dynamics of investors demand will have the company trading at a 30 billion dollar valuation before it trades at an 11 billion dollar valuation.
*The analysis underweights the increasing utilization of taxi-cab like services that the presence of Uber encourages, but apart from that it appears to be about as close to accurate as a valuation expert can be with the available information.