By Rafiq Raji
Why are analysts reluctant to make bold calls? In hindsight, recent negative market surprises could have been predicted based on the data. So the question is asked as to why analysts did not make the right calls a priori for events that were discernible from the data. A crude oil producers’ fight for market share is now palpable with hindsight. The costs of a Euro peg post-ECB QE are now clearer with hindsight. It leaves one wondering what other black swans lay in plain sight that may become conveniently obvious with hindsight. What are our current assumptions? We have to question them otherwise these negative surprises would continue to confound us; before hindsight provides clarity of course. It is unbelievably amazing how intelligent everyone seems to be – without exception – with the benefit of hindsight. After the events, the analysts are articulate and the reports? Very elegant! What then is the utility of analysts if all we do is tell people what they already know? Surely, if they wanted just news, they could simply switch on the television or read the papers.
So, why do analysts get it wrong when it really matters? A major factor is the fear of being wrong when the consensus turns out to be right; which often is the case until the rare negative surprise occurs. Group-think is a well-researched psychological phenomenon. In light of the recurring failure of analysts to get it right when it really matters the most, it is clearly a continuing problem. Analysts achieve prestige based on the number of calls they get right. So naturally, they are reluctant to make “risky” calls the higher the likelihood they might be wrong. Also, there is comfort in numbers. Bold calls are extremely lonely. When you start hearing colleagues telling you: “That is a very bold view!”, it is not a compliment. Resentment and jealousy usually follow when you get it right; especially if you turn out to be more than just a “one right call wonder”. And when you do get it wrong – as you would and must – the derision is monumental. Thus, it is a dilemma. Another factor is how analysts are compensated. Analysts are paid by the month. As a call discernible from the data may take a long time to instigate a market-impacting event, it could be career-limiting to stick your neck out too early. So, most analysts are forced to strike a balancing act. That way, they keep their jobs. The real losers in all of these are their employers.
There is also a tendency to overly focus on the elegance of a report at the expense of utility. What market participants really want are answers; what you discern from the data, what you can infer from comments made by officials, et cetera. Sometimes, the data trend and official commentary are at variance. The data suggests one thing and the official commentary suggests another. The one commonality amongst all these is the human factor. Officials and analysts are human beings. We dither and procrastinate. We look for evidence to confirm our views. We seek comfort in the majority. We try to manage worsening situations. We try to avoid facing reality. Until of course, the costs become too overwhelming and we are forced to do the sensible thing. This problem applies to fund managers as well. The successful ones have been those with permanent capital. Because if you are relying on proper research to make investment decisions, then what you can be reasonably sure of, is the event and its likely triggers. No one, however, knows when such events would happen. That is the major constraint. If your compensation – whether you are an analyst or fund manager – is not aligned with the lead times it takes for a research-based view to be vindicated or proved wrong, it is unlikely the analyst would be willing to make the kind of bold calls that could potentially be hugely rewarding for both parties: the analyst and his or her employers. Companies have to produce annual financial statements, however. The only financial institutions that have been able to get around this problem are probably private equity firms. Even they are now becoming increasingly constrained as some have gone public with the attendant short-term financial reporting requirements.
So what should an analyst do? Follow the data. And for the potential timing of an event, look to history. Yes, there would be wrong calls. But if an analyst objectively interprets the data, questions the motivations behind statements by officials and looks to history for how long it took before events vindicated trends discernible from the data, it is not likely the analyst would be wrong most of the time. Employers may also need to place a higher priority on utility over elegance. Research reports are not decorations and opportunities to show-off erudition. They are meant to provide answers and direction when it matters, before the fact. Not after. So even though the consensus is comforting, the analyst cannot afford such luxuries. Ironically, the personality traits of analysts with such independent streaks tend to be converse to the expectations of most corporate cultures. Thus, the analyst may find following the consensus to be quite rewarding and career-advancing. Well, that may not continue for long. Machines are replacing humans on trading floors. They may make inroads into research as well if analysts and institutions continue to be blind-sighted by their biases. Machines may actually not be immune from these biases as well. After all, they’d be analyzing the data as well; which includes statements made by human beings. For instance, how would a machine be able to discern a misleading statement from a human being, say an official? As the analyst who would succeed requires cognitive intelligence to analyze the data correctly, emotional intelligence to discern deception from actors within the respective eco-systems and the ability to manage his or her own biases, a machine invasion of the research profession is still way off. But even when the human analyst succeeds in doing all these, his or her employers must structure compensation and working conditions to make it conducive for such bold but evidence-based calls to be made. Thus, research houses may need to take a cue from Silicon Valley. In any case, the analyst should follow the data to wherever it leads, investigate the motivations of the various actors when their comments are at variance with what the data is saying, and make the call. In so far as the analyst follows this process to make an objective call, bold or otherwise, it should matter little whether his or her call is vindicated (actually it does matter; promotions and bonuses dah!). But then only God can see the future.
Opinions expressed are mine and not that of any institution I may be affiliated with.