From Data to Wisdom: The Path of the Most Successful Investors

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(Published originally in Spanish by Ángel Martín Oro at Bonsai Capital blog, a new fintech start-up based in Spain aimed at facilitating investment in the best actively managed funds). Follow him on Twitter @a_martinoro and connect on Linkedin

 

These are two academic economists walking down the street, teacher and disciple. The former is a loyal supporter of efficient markets. His disciple stands for a moment, touches his arm and points him to the ground.

– Look, a € 100 banknote that some absent-minded will have lost.

– No, it can not be??he answers . If so, somebody would already have picked it up. It will be a trap.

At the wisdom of his master, he nods in wonder, and they continue the walk as if nothing had happened.

This well-known joke caricatures the position of defenders of the strong efficiency of financial markets. But it is also applicable to non-financial areas. Leading political economist Mancur Olson, for example, used this metaphor for the field of economic development in a conference titled Big Bills Left on the Sidewalk: Why Some Nations Are Rich, and Others Poor (1996). Olson put the poor countries as an example of the fact that there are wasted big bills left on the sidewalk, not so much because of the lack of individual rationality, but because of the problems of the existing institutions that make picking them up difficult. He ends his talk by warning about what he calls a sad and all-too-general reality: “as the literature on collective action demonstrates, individual rationality is very far indeed from being sufficient for social rationality”.

The underlying idea of the joke, which forms an essential part of the dominant paradigm in economic and financial theory, is that markets perfectly and frictionlessly adjust to new realities and changing information. Resources are always allocated and valued correctly due to the efficiency of the market. Therefore, profit opportunities (those big bills left on the sidewalk), which are a reflection of inefficiency, are non-existent.

But the truth is that in economic life, whether in markets where financial assets are frantically exchanged every millisecond, or markets in which goods and services are exchanged, there are inefficiencies that can persist over time. These generate profit opportunities for those investors and entrepreneurs who know how to identify and exploit them. Markets are not perfect, simply because those who form them, people of flesh and blood with both their rational part and their emotional part subject to bias, are imperfect.

There are also frictions and difficulties in adapting from one phase to another. Sometimes it happens almost instantly, others takes a lot of time, pain and tears. The brilliant Raghuram Rajan, until recently Governor of the Central Bank of India, said recently that in developed countries there is a deep problem of adaptation to the remarkable forces of technological change and globalization. While recognizing that these trends have very positive overall effects, they negatively affect certain segments of society, who are easy prey to populism.

The reality is much more complex than it has been painted by the most simplistic economic models. These transition costs, as Rajan points out, have been undervalued by most economists, who used to assume a type of economic agent different from the real one.

This also happens in the theoretical models in finance that support the Efficient Market Hypothesis (EMH). Starting with the notion of information, which is key in this area. Recall that EMH means, in essence, that asset prices reflect at all times all available information. But what about the interpretation of this information? Is information objective? Do all agents interpret it the same way?

In this regard, it is necessary to distinguish between the different levels that represent data, information, knowledge and wisdom, according to the DIKW pyramid (the intelligence hierarchy, in terms of Barry Ritholtz). Data are the objective and raw facts or numbers about an event that can not be disputed. Information uses data as inputs, but applies conceptual tools (models that establish relationships between some variables and others) to get something from them. Knowledge shapes and contextualizes that information, which through understanding and practice, can become wisdom.

 

clostThe DIKW Pyramid (Data, Information, Knowledge, Wisdom). Source: Climate-Eval.org

This, which might seem like mere theoretical digressions, was set out by Fernando del Pino (now private investor and former member of the board of Ferrovial) in a brilliant interview about his investment style:

Information is the lowest use of man’s intellectual capacities; then higher up you find knowledge; and at the summit there is wisdom. You have to aim at the latter. Too much information hinders knowledge, and very often, too much knowledge hinders wisdom—because of hubris. Today we live in a world with overwhelming loads of stupid information and very little wisdom, I’m afraid.

Let’s use a simple example. A company we are invested in because of attractive potential returns, releases its earnings quarterly report. The data are the raw numbers presented: revenues, earnings per share, guidance for the next quarter, and so on. But this does not tell us anything in itself. In order to become information, these data should be interpreted by making some connections, for example, which were the consensus estimates, our own or those of the managers of the company. However, for a correct interpretation of these numbers, we must delve into questions such as: are there any unique (one-off) elements that complicate their comparison with previous quarters, or the previous year? For instance, exceptionally strong demand, or accounting issues. Do these numbers support our positive investment thesis in the business? Should we adjust our hypotheses for the future? Has the management strategy changed? If so, in what? And a long etcetera. To do this, it is necessary to have previously analyzed the busyness thoroughly and have a model where to fit this data and information. We could already be talking about knowledge. At this point, what do we do? Do we buy more, sell our whole position or only partially, hold? Here it would enter wisdom, which mixes knowledge with the point of intuition or judgment that experience gives.

What seems quite difficult already is further complicated by the fact that, as Bill Miller frequently reminds his analysts, 100% of the information available to a company represents the past, but 100% of a stock’s valuation depends on the future. A future that is, by definition, uncertain, where expectations about it are fragile, volatile, heterogeneous and subjective (each agent may have a different idea of how the future will be).

But this does not mean that we can not have certain notions of how several companies will perform in the coming years—of course, without certainties, always from a probabilistic perspective. But for that goal history is studied, and sometimes certain empirical regularities are obtained. For that goal the management is studied, its track-record, how the company makes decisions and extrapolate to the future (assuming that, e.g. if in the past it has acted in favor of shareholders, it will continue to do so). To reach that goal, the most qualitative fundamental investors analyze the business in depth, in order to know if they have advantages that will defend them from the competition (economic moats), in the present but especially in the future.

In short, while from the perspective of market efficiency both valuing assets according to available information and adjusting to the new information seems somewhat mechanical and instantaneous, it really entails a great complexity because of the subtlety of the “information” concept.

 

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