A cool friend of mine on Twitter, Drew Dickson at Albert Bridge Capital, joined in the latest exchange between behavioral finance and EMH with a nice post titled “Behavioral Finance Is Finance.” Drew is kind enough to cite my first blog post titled “Fama Is Right” in his article. Thank you Drew. I very much appreciate your kindness, seriousness, and thoughtfulness that permeate your writing. I find many of your points to be quite reasonable. And I take them very seriously.
In this blog I argue that the newly developed investment literature has provided (or at least started to provide) answers to many of the important questions that Drew has raised. In no way I think my answers are complete or perfect. I am keenly aware of several remaining issues and I am actively working to resolve them. Most important, I value the opportunities to learn about others’ perspectives, especially those from asset managers with whom I don’t interact daily. I am fully capable of admitting mistakes when proven wrong. I am not very good at listening but I am trying.
In what follows, I first quote directly from Drew's article and then provide point-by-point responses.
“Does behavioral finance need to figure out a model of market equilibrium that makes markets efficient? Isn’t that a bit of a diversion? Hasn’t behavioral finance actually provided a theoretical underpinning for many of the most successful ‘factors’? Hasn’t behavioral finance made relevant these theory-less multi-factor models of market equilibrium?”
Please let me clarify my perspective. Start with the accounting identity:
Realized returns = expected returns + abnormal returns.
When an anomaly variable forecasts realized returns, there are automatically two parallel interpretations. One, which is the behavioral view, says that the variable is forecasting abnormal returns. As such, pricing errors are forecastable, yielding a violation of EMH. The other, which is the EMH view, says that the anomaly variable is related to expected returns but the errors are unpredictable. The consumption CAPM and the investment CAPM are both about expected returns. Both are consistent with EMH.
When I say no behavioral theory since 1985, I meant no theory of “abnormal returns.” If behavioral finance is to become a competing paradigm with EMH, the burden seems to be on its proponents to develop a theory of abnormal returns. Such a model doesn’t make markets efficient. It would be a theory of inefficient markets, a theory of pricing errors. And it’s not a diversion. It's the essence of behavioral finance. Why do investors make the same mistakes repeatedly year after year?
When I say “equilibrium,” I don’t mean fancy math. I just meant prices being jointly determined by supply and demand. Like gravity, there is no escape from this law. How much you pay for your new house depends on whether the seller has a competing offer and whether you have in mind a backup house that you and your family like.
There are indeed behavioral theories that link value and momentum to different psychological biases. However, these models all assume a constant discount rate (expected return). While a useful first stab, these models basically assume that all the return predictability in the data arises from predictable pricing errors. This is why many economists feel that the existing behavioral models just relabel things. More on this point later.
“And it’s provided plenty of evidence that markets don’t always get things right. And frankly, there is very little supporting evidence of the risk story behind many of Fama and French’s proposed factors. Size? Maybe (big maybe). But why is value riskier than growth? Why are firms with better gross profitability riskier than those that are less profitable? Why are firms that efficiently invest capex more risky?”
“And perhaps a more important, and bigger, question: why didn’t Fama and French include momentum in either their three or five factor models? They know it’s there. They know it’s a thing.”
“The answer, because there is almost no possible risk explanation for momentum. The behavioral guys have plenty of reasons. They have common sense, intuitive reasons; motives like loss aversion, confirmation bias, anchoring and herding. Even Fama himself has admitted that momentum ‘is an embarrassment to the theory.’ Momentum isn’t embarrassing for Narasimhan Jegadeesh, Sheridan Titman, Cliff Asness, or Mark Carhart. Momentum isn’t embarrassing for those who know that behavioral finance hasn’t been a failure. For those guys, momentum is beautiful.”
Very cool questions. Thank you. I respect and appreciate your frank communication. It is only through frank communication will I learn where my arguments fall short.
I’ve been thinking about the same questions for 20 years ever since I started to do research in 1999 as a second-year Ph.D. student at Wharton. In what follows, I summarize my current, still evolving thoughts. I think I have reasonable answers. Again, in no way I think my answers are perfect. Please feel free to let me know where I screw up. So I can try to improve going forward.
Momentum is a success story for the investment CAPM. As shown in the table below, UMD can be explained by the q-factor model in Hou, Xue, and Zhang (2015). The average return of UMD is 0.64% per month in the 1967-2018 sample, but its q-factor alpha is only 0.14%, with an insignificant t-value of 0.61. The return on equity (Roe) factor plays a major role in explaining UMD. The evidence shows that momentum is a noisy version of our Roe factor.
Intuitively, the Net Present Value rule in capital budgeting says that high expected Roe relative to low current investment should imply high costs of capital (expected returns). And current Roe is a proxy for the expected Roe. That’s it.
The difficulty arises as for what risks lurk behind momentum. I could follow Fama and French (1993) and call the q-factor loadings risk measures. And it will be correct from a statistical standpoint such as APT. But from an economic standpoint, I feel that a more precise interpretation of the q-factor model should be a linear factor approximation of the nonlinear characteristic model of the investment CAPM (Lin and Zhang 2013; Zhang 2017).
However, I acknowledge that the investor-side CAPM and the supplier-side CAPM should be internally consistent. While the supplier-side CAPM is worked out in theory and in the data, it would be better if it can be demonstrated what exactly the risks are lurking behind the investor-side CAPM, at least conceptually.
There are a few rational models floating around at this point, such as Johnson’s (2002) expected growth and Sagi and Seasholes’s (2004) growth options. And I have done a few econometric studies that link momentum to expected investment growth (Liu and Zhang 2014; Goncalves, Xue, and Zhang 2019). Intuitively, momentum winners have higher expected growth than momentum losers. And the expected growth is risky (to the extent that it might not be materialized).
However, an important weakness of the current theoretical literature is that it lacks a unified equilibrium theory of value and momentum together. Li (2018) is the only example I can think of. We should work more to figure out the exact sources of risks behind expected growth (and momentum and Roe factors).
In short, momentum is not a problem per se from the supply-side investment CAPM. Alas, a significant gap in our knowledge exists in terms of exactly how momentum can be consistent with the consumption CAPM in a fully specified model. As challenging as it is, I don't view it as insurmountable, however.
Finally, as an economist, I have some preferences over an optimization-based model. Gene said in his latest interview that behavioral economists reply on investors being “stupid, repeatedly stupid.” Gene is right, in my view. Regardless of how sensible, intuitive the underreaction explanation might appear at a first glance, it’s hard to believe, for me at least, that investors would be confused for more than 50 years about post-earnings-announcement drift since Ball and Brown (1968). Once the horizon is that long, the biases explanation no longer feels sensible or intuitive. The fact that the drift persists for so long indicates to me that it is in fact part of the expected returns.
“Behavioral economics is no longer the domain of rogue traitors attacking efficient market theory. Behavioral economists are the patriots of finance.”
Bravo. I totally agree. I feel sorry that you even felt the need to make this statement. There is no question whatsoever in my mind that behavioral economists are patriots of finance. Thaler, Bernard, Thomas, Jegadeesh, Titman, Lakonishok, Sloan, and Ritter are heroes in my book. Reconciling their enormous contributions with what I learned in school has been my life’s endeavor. I’m very much indebted to them.
I am very familiar with the role of a “traitor.” I am just doing my “betraying” in a different way. Alas, challenging the status quo is the essence of research. I feel that I have something new and important to say. And that’s the source of all my “treachery.”
Behavioral finance is no longer a fringe field. It’s mainstream. Just like EMH before the rise of behavioral finance, a mainstream school of thoughts provides a ready target for the next generation of “traitors.” So get ready for more.
I agree with behavioral finance on the facts (barring Hou, Xue, and Zhang 2019, "Replicating anomalies") but disagree on their interpretation. I know this is exactly what Gene said. But unlike Gene, I have theory, in addition to evidence, to back me up.
I challenge my professional colleagues to prove me wrong, scientifically.
Ball, Ray, and Philip Brown, 1968, An empirical evaluation of accounting income numbers, Journal of Accounting Research 6, 159-178.
Fama, Eugene F., and Kenneth R. French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, 3–56.
Goncalves, Andrei S., Chen Xue, and Lu Zhang, 2019, Aggregation, capital heterogeneity, and the investment CAPM, forthcoming, Review of Financial Studies.
Hou, Kewei, Chen Xue, and Lu Zhang, 2015, Digesting anomalies: An investment approach, Review of Financial Studies 28, 650-705.
Hou, Kewei, Chen Xue, and Lu Zhang, 2019, Replicating anomalies, forthcoming, Review of Financial Studies.
Johnson, Timothy C., 2002, Rational momentum effects, Journal of Finance 57, 585-608.
Li, Jun, 2018, Explaining momentum and value simultaneously, Management Science 64, 4239-4260.
Lin, Xiaoji, and Lu Zhang, 2013, The investment manifesto, Journal of Monetary Economics 60, 351-366.
Liu, Laura X. L., and Lu Zhang, 2014, A neoclassical interpretation of momentum, Journal of Monetary Economics 67, 109-128.
Sagi, Jacob S., and Mark S. Seasholes, 2007, Firm-specific attributes and the cross-section of momentum, Journal of Financial Economics 84, 389-434.
Zhang, Lu, 2017, The investment CAPM, European Financial Management 23, 545-603.