This year’s annual financial research “geekfest,” officially known as the American Finance Association Annual Meeting, assembles the world’s top-tier academic researchers to discuss their latest financial research.
If you are looking to get a glimpse at “hot off the press” research, you can find no better place (although, our Democratize Quant Conference is arguably a lot more fun!).
This year there were 246 papers discussed across 73 sessions. We spared you the countless hours required to peruse every paper to synthesize some of the more interesting research projects coming out of the Ivory Tower. We went with my “top 5,” to maintain consistency with my top 5 podcasts post and my top 5 investment blogs post, but to be fair, it would have been easy to create a top 50, given the caliber of the research being produced.
In no particular order:
Stock Market Anomalies and Baseball Cards by Joey Engelberg, Linh Le and Jared Williams
An open question in finance is whether or not the studies on so-called, “anomalies,” or market mispricing, are a result of data-mining or represent genuine market phenomena. We’ve discussed the argument (here and here) that anomalies are possibly “fake news.” The authors take the other side of the argument. The professors look for out of sample evidence for anomalous market behavior in the baseball card market. If mispricing is driven by human behavioral issues, we should see mispricing in all markets, not just financial markets. The authors confirm that the baseball card market suffers from many of the inefficiencies identified in financial markets. The lessons for investors in the baseball card market are the same lessons they should have learned in the financial markets.
Bottom line: Stick with winners (i.e., players with trending fundamentals are relatively undervalued) and avoid Initial Public Offerings (i.e. hot rookie cards).
Competition and Momentum Profits by Gerard Hoberg, Nitin Kumar, and N.R. Prabhala
In 2017, momentum, as measured by the relative performance of the largest Momentum factor fund, the iShares Edge Momentum Factor fund (ticker: MTUM), was clearly in favor. But what happens to the abnormal profits of a strategy when there is more competition to exploit that specific strategy? Intuitively, more competition should decrease the abnormal profits of a strategy. But this question is actually more difficult to address than people think. Historically, researchers have focused on analyzing how much of the smart money is buying momentum stocks. But the results from these sorts of analysis are mixed. The researchers in this paper, reframe the problem a bit and look at how many smart money investors are avoiding momentum stocks, which also reveals information, albeit in an indirect way. Using their clever approach, the authors confirm our intuition — more competition causes momentum profits to decay. And along the way, they identify a cleaner way in which investors can monitor competitive pressures, and thus predict future momentum profits.
Bottom line: Monitor what the competition is doing when deciding whether or not to deploy capital into a strategy. You may avoid a crowded trade!
FinTechs and the Market for Financial Analysis by Jillian Grennan and Roni Michaely
Thanks to the power of the internet, smartphones, and other modern technology, we have access to more information (and faster access to that deluge of information) than we’ve ever had before. Due to this information overload, financial technology companies have attempted to assist us in aggregating the information in order to make our processing of the information more efficient. In theory, aggregating data on equities should enable investors to more quickly understand all publicly available information about a stock. The market should get more efficient, right? Not exactly: The aggregation of information can lead to some unintended consequences. The authors find that fintech can actually reduce market efficiency, by reducing the incentives for investors to identify original ideas, and by reducing the incentives of market participants to produce original financial information. Both of these outcomes don’t improve market price accuracy.
Bottom line: If fintech is making your life easy, it is also making everyone’s life easier. But complacency kills. On net, you have no edge, and by relying exclusively on technology to make your investment decisions, you may be sweeping important details under the rug.
The Impact of Internet Postings on Individual Investors by Manuel Ammann and Nic Schaub
Our parents all teach us a basic lesson when we’re little: Don’t take candy from a stranger. In the investing world, this age-old advice rings true, but with a twist: Don’t take investment tips from a stranger. This study looked at the results of individuals who post investment advice in an online forum, and how the individuals who followed that advice subsequently performed upon acting on the advice. The authors found investors reading the comments in the forum are more affected by comments from those who appear to be more sophisticated, and from commenters that have done well recently (i.e. good old fashioned performance chasing). Not surprisingly, the authors conclude that investing based on advice from message boards probably isn’t a great idea…d’uh.
Bottom line: Do your own research. Don’t assume that because someone has done well recently, they are likely to continue doing well, and don’t be wooed by someone who seems sophisticated when giving investment advice.
From the Horse’s Mouth: What Matters to Individual Investors? By James Choi and Adriana Robertson
Yogi Berra is attributed as saying, “In theory, there is no difference between theory and practice. In practice, there is.” Plenty of ink has spilled outlining optimal investment approaches and how portfolios should be constructed. A fair amount has also been written on theories of investor motivations and beliefs. But the authors of this paper take a different tact: instead of pontificating about how investors think about the market, why not ask them directly? Upon doing so, the authors gleam some great insights about how investors actually think about markets. The good news is that how academics model investor behavior is roughly consistent with actual investor behavior. For example, investors care about tail risks, their ability to maintain their life style in the future, and avoiding uncertain outcomes. But there is some bad news in the findings. The most striking element is investor reliance on past performance as a predictor of future performance. The evidence supporting this premise is weak at best, but investors continue to belief in the merits of past returns.
Bottom line: The difference between theory and practice, when it comes to investor behavior, is fairly narrow. This is good news for academic researchers. However, despite best efforts by academics to compel investors to avoid focusing on past returns to predict future returns, investors can’t kick the habit.
The research above is cutting edge and caught the attention of academic researchers. Many of the insights discussed, and the insights buried in the 241 other papers not discussed, might stimulate an innovation in your own thinking.
We encourage all investors to get a sneak peek into these new research pieces. Good luck.
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