An asset manager’s business model is in essence a fiduciary model: all efforts are focused on wealth creation for its clients. Although the output can be measured in physical monetary units, the asset management process itself is highly dependent on data, information and knowledge. Better still, most asset managers claim to exert specific knowledge as a result of which clients will benefit in terms of better performance. This paper raises the question what this actually means. If asset managers have specific knowledge, what does it consists of? And how can this knowledge be transferred into superior results? It will be argued that it is extremely difficult to pinpoint what this specific knowledge really is, and that is often tacit in nature. But as long as the expectation of superior results is kept alive, it seems not too many questions are asked.
During the last decade the focus on intellectual capital has grown significantly. Intellectual capital can stem from different business processes such as engineering, production, marketing, human resources, etc. Many firms spend much time protecting their intellectual assets by means of patents, trademarks and brands. According to the OECD patent filings grew between 1992 and 2002 by 94% in the US and by 76% in Europe. But intellectual capital is in the minds of the employees and is much more fluid than fixed assets. Non-competition and confidentiality agreements in employment contracts are rather meaningless in practice, while stock options and other financial incentives to retain employees with specific skill and/or knowledge can easily be paid off by competing employers.
The growing interest in intellectual capital is triggered by three developments (Prusak, 2001). Firstly, globalization has led to wider markets and a need to bring (innovative) products and services to these markets ever more quickly. The second development is the surge in information technology, which has expanded the access to information dramatically. The last development is the growing interest in a knowledge centric view of the firm rather than a resourcebased view. Traditionally a firm is defined as a collection of physical resources such as plant, equipment, land, materials etc, which sets the boundaries of its activities. A knowledge centric view on the other hand states that a firm is a collection of intellectual resources and capabilities and is in principle unconstrained with regards to products and markets.
The asset management industry is said to depend on the competences and skills of its investment professionals. This implies that knowledge is the crux for being successful. This paper will firstly go into the concept of knowledge management and discuss its meaning in an asset management environment. This will be followed by a comparison between the more traditional asset managers and hedge fund managers in order to detect whether the success of hedge funds can be explained from a knowledge management perspective or whether other factors are at work. The paper will finish with some recommendations for both asset managers and investors.
What is knowledge management?
The epistemological view of knowledge is a scientific, philosophical approach to determine the nature of knowledge itself (Jacubik, 2007). For a long time it was widely accepted that knowledge was defined as justified true belief. Later this was modified by adding the condition that the justification for the belief must be infallible and that there should be no overriding or defeating truths for the reasons that justify one’s belief. According to Wilson (2002):
“‘Knowledge’ is defined as what we know: knowledge involves the mental processes of comprehension, understanding and learning that go on in the mind and only in the mind, however much they involve interaction with the world outside the mind, and interaction with others”
This means that the way information is conceived is very dependent on a person’s knowledge structure, which in itself is dependent on past experiences, training, personal circumstances etc.
Knowledge management has become a popular term which is used for many purposes. However, in a majority of articles knowledge management is just a synonym for information technology and/or data management (Wilson, 2002). But in order to understand what is really meant by knowledge management, it is probably best to distinguish data, information and knowledge. Data can be seen as signals which are embedded in a certain setting, while information is the framing of that data. Subsequently, the difference between information and knowledge is explained by Nonaka and Takeuchi (1995) as:
“First, knowledge, unlike information, is about beliefs and commitment. Knowledge is a function of particular stance, perspective, or intention. Second, knowledge, unlike information, is about action. It is always knowledge “to some end”. And third, knowledge, like information is about meaning. It is context specific and relational.”
Knowledge management is therefore not about creating the same knowledge structure for all people, but about realizing the best possible output resulting from intellectual activities. Important in this respect is the difference between explicit and tacit knowledge. Explicit knowledge is objective and can be acquired, shared and disseminated. Tacit knowledge on the other hand is subjective and based on personal experiences. If tacit knowledge is deemed of value, an important question is whether it can be made explicit. Not everyone is convinced that this is possible. For example what about tacit knowledge that is a fluid mix of experiences, values, insight and contextual information? The process of articulating and codifying this knowledge could be very hard. Knowledge on the verge of intuition and/or beliefs might even be impossible to grasp1 .
Based on the firm’s strategy, so-called knowledge assets can be created. This is the knowledge regarding markets, products, technologies and organizations that a business owns or needs to own and which enable its business processes to generate profits (Collison & Parcell, 2005). Dependent on the specific business model, knowledge management should distinguish three levels (Zack, 1999):
- core knowledge is the minimum scope and level of knowledge required just to “play the game”;
- advanced knowledge enables a firm to be competitively viable;
- innovative knowledge enables a firm to lead its industry and competitors and to significantly differentiate itself from its competitors.
Core knowledge depends the most on explicit knowledge. Advanced knowledge can be seen as a hybrid form of explicit and tacit knowledge, while innovative knowledge leans the most towards tacit knowledge. Advanced and innovative knowledge, given its scarcity, are important drivers of a firm’s value. It is therefore important to share this knowledge in order to realize economies of scale and to be able to fully benefit from the strategic knowledge advantage. Knowledge sharing is however not a straight forward process: it can neither be supervised nor forced out of people and voluntary cooperation is needed (Kim & Mauborgne, 1998). This happens for example in communities of practice2. These efforts can be explained by feelings of belonging, loyalty to the firm, respect and trust. Self interest on the other hand is the main reason for an individual not to share his knowledge. The person might have doubts whether he will adequately be compensated for sharing his knowledge. Or he might fear that by sharing knowledge his own position can be jeopardized. Or even that he feels that the decision making process in which his knowledge is used, is unfair. These feelings of unfairness can be triggered by a lack of engagement, a lack of explanation by senior management and/or ambiguous expectations. It could also be that the transfer of knowledge does not occur, simply because people place little value on each other’s knowledge. This is certainly true for tacit knowledge. If the person possessing the tacit knowledge can only refer to it in vague terms, the other person is likely to label it as trivial and irrelevant.
The ever-present promise of excess return
What can be said about knowledge management in asset management firms? An asset manager can be typified by its fiduciary role related to its clients by managing the client’s wealth as good as possible. Given the framing of the investment mandate, an asset manager’s success is almost always directly associated with its investment results. Most asset managers’ marketing efforts emphasize this by claiming that active management will generate excess returns for their clients which are more attractive than a risk-free deposit or an investment in a market index3. In general terms excess returns can be achieved in three ways: fraud, luck or skill. Unfortunately fraud still pops up regularly despite all forms of controls, separation of duties and regulatory oversight. But fortunately fraud is typically shortlived. Luck on the other hand is perfectly legitimate, but random4. Therefore, generating excess returns in a consistent way can only be realized by means of skill. Knowledge management starts to enter the picture here, because it is all about the sequence of data, information and the subsequent decisions investment managers make. The task of knowledge management within asset management firms is to clearly pinpoint whether excess returns can be generated in the first place, and if so, what investment strategy should be followed. Many asset managers have established knowledge assets in terms of specialized and dedicated investment teams for specific asset classes and/or investment strategies, which would imply that knowledge management is properly applied. Every single team should have a clear view on market dynamics, the data and information available and the required skills and knowledge to generate excess returns.
But the question is whether this really is in place. Already for many decades, the concept of efficient markets has been discussed and tested. If markets are efficient, investment returns follow a random walk and no additional risk adjusted return could be realized. A strong case can be made that for many markets this is indeed true. The rapid development of information technology has led to no scarcity of data and information, and also the speed in which new data is disseminated globally is phenomenal. In many asset classes, the competition is fierce with equal access to the same sources of data and information and low transaction costs. Moreover, the training investment professionals receive is very standard5, valuation and risk models are based on common principles and a relatively open exchange of ideas and practices exists. If markets are random, you can only “play the game” and index tracking is the appropriate investment strategy6. But even in random markets plenty of risk-takers are around who believe they can outsmart the market. Many traders believe that they have developed valuable tacit knowledge such as heuristics (Willman et al, 2001). They consider it justified true beliefs7, but more often than not they simply trade on noise rather than on signals8.
Clearly not all markets are random as informational differences can exist due to the existence of transaction costs and information asymmetries. Moreover, differences in cognitive processes exist meaning that some traders / investment managers are simply quicker to act on certain information than others. These factors relate to Zack’s advanced knowledge and can be translated into an active investment strategy. In recent years a strong case has been made for so-called alpha and beta separation. The beta represents a market return and the alpha the excess return the investment manager adds to the portfolio. The reason for this separation is, amongst others, that by breaking up the total performance one can assess whether the asset manager indeed possesses advanced knowledge and adds value.
The behavior of many market participants touches on the concept of illusion of control, which rests on the failure to distinguish between controllable and uncontrollable events. The trap they easily fall into is that price movements look like real patterns, and that there are many examples of successful investment managers who made a lot of money by correctly forecasting dramatic turnarounds in the market9. However, these risk takers tend to suffer from over-optimism and fall victim of the fallacy that more information leads to more knowledge. But the only real result is that more information tends to make people more confident about the outcome of their decision. Capital markets possess many elements that increase the illusion of control (FentonO’Creevy et al, 2003). Stress and anxiety contribute significantly to the illusion of control. So does competition, a strong focus on (financial) bonuses and the identification with the markets in which investment managers are active. Knowledge management begins by asking critical questions about the justification of investment strategies. As trivial as these questions may seem, many times investment decisions are solely based on an alleged existence of tacit knowledge.
Traditional investment managers versus hedge funds
Hedge funds are often regarded as highly sophisticated asset managers constantly outsmarting and leading the financial industry. They are seen as possessing Zack’s innovative knowledge. For quite some time their investment results were very impressive indeed, but lately some cracks have appeared. Even Atticus Capital, which was considered one of the most powerful hedge funds around, reported substantial losses of its two flagships funds of a quarter and a third.
The difficulty with hedge funds is that they cannot be treated as one specific group bounded by similar characteristics, because their activities are very wide and diverse. Moreover, not much is known about how they actually operate. Many hedge funds simply decline to be transparent and investors just have to trust them by paying a whopping 2% management fee and 20% performance related fee. And many investors do, but why? Perhaps most of us want to believe that there are extraordinary returns out there which are driven by skill rather than by luck. Hedge funds do a wonderful job cultivating the idea how market savvy they are. But how real can this claim be? Do hedge funds possess more knowledge than the traditional asset managers? Did the head energy trader at Amaranth really have such a knowledge advantage, or did he just follow a historic trend with highly concentrated positions? Referring back to Atticus Capital, according to an article in the Financial Times (September 1, 2008) the losses10 were due to large and highly concentrated (event driven) bets in combination with a few “short” positions to lower the risk. Does this mean that Atticus Capital has more talented portfolio managers at work and/or that their knowledge creation is more flexible? Although this all might be true, we do not know for sure. But as they work in the very same markets as traditional asset managers, they cannot be fully isolated from general market movements. As Atticus Capital wrote in their July report: “we continue to be disappointed by what we believe is an overreaction in specific themes to concerns about growth”. To what extent is this any different than many traditional asset manager? Probably some hedge funds do possess some advanced and/or innovative knowledge which they can use to generate good investment results, which implies that their knowledge management is up to speed. But irrespective of their focus on knowledge management or not, three fundamental differences related to their business set-up could help their performance: type of investment exposures, size and less supervision. Many hedge funds are launched by successful traders who used to work for investment banks. As long as their focus remains on specific trading areas, they can benefit from an information advantage related to technical trading opportunities in the market other market participants do not focus on. The profit margins related to these activities are often thin and the investment return only becomes interesting enough by using leverage. Still, one should be very careful in believing in the innovative character of the knowledge applied. A good example are Bear Stearns’ high-grade structured credit and structured credit enhanced leverage funds, which were no more than a basis trade between cash instruments and derivatives. As long as the basis remained in a trading range, returns could be boosted by using leverage up to 20 times. In terms of knowledge, we could argue that this knowledge could easily be made explicit and is a good example of contingently tacit knowledge. However, as soon as the basis broke out of the range, the collapse in performance was evident. Traditional asset managers do not work this way, because these small scale opportunities hardly add any value to their investment portfolios without leverage.
Linked to the previous point is the issue of size. Most successful hedge funds are limited in size. Together with their focus they can act quickly on new information and/or market developments. This is often not the case for traditional asset managers who have many different clients and mandates to take care of. Compliance becomes a major issue for large asset managers as all clients with similar investment guidelines need to be treated equally. Therefore, the whole processing time related to executing a transaction is much longer for traditional asset managers than for hedge funds. Many successful hedge funds set limits related to their size and are closed for new business in order to maintain their competitive advantages.
The third difference is that hedge funds work in a different regulatory environment than most traditional asset managers. This means that hedge funds can be more flexible in terms of investment strategies, the type of investment instruments they use and the amount of leverage in the funds. Many investors in hedge funds allow them these degrees of freedom, while at the same time imposing all kind of restrictions on traditional asset managers. This goes hand in hand with the proposition that traditional asset managers are mainly used for managing market exposures, and hedge funds for market neutral alpha generation.
Knowledge management: where do we stand?
Every single day asset managers deal with a lot of data and information. Knowledge management has to do with the use of that data and information for investment decisions in order to specify how investment returns are generated. However, it is not an easy task to pinpoint exactly what the sources of excess return are. The reason is that we too often claim that we have control over uncertain outcomes. Moreover, we want to believe that investment managers and traders possess tacit knowledge which could lead to extraordinary results. But the essence is that if markets are efficient, there is no such thing as beating the market consistently. In such environment asset managers beat the market only by being lucky, taking more risk or by changing the rules of the game by holding off-benchmark exposures. Many hedge funds are not different in this respect. Still, not all markets are random. An asset manager must be expected to be able to distinguish between random and non-random markets and to determine what is needed to generate excess returns. Having a structure of knowledge assets in place should help this process. Moreover, by understanding clearly what the asset manager is really good at, it becomes easier to focus on its real strengths. In line with a knowledge centric view of the firm, it should try to expand this advantage to other market segments. Unfortunately though, investment philosophies and strategies are still too often described in vague terms and with many references to the existence of tacit knowledge. There is a role to play for investors too. In their due diligence process of external managers they should strongly focus on knowledge management as well. Because as long as investors do not differentiate in the fees they are willing to pay and warmly embrace the concept of excess returns based on tacit knowledge, asset managers and hedge funds alike will happily cultivate the idea that they possess superior knowledge.
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- Note that some knowledge may appear as tacit knowledge, but it is actually contingently tacit as the knowledge could be made explicit but it is kept by an individual purely for his own continued success.
- Communities of practice are informal groupings with the goal of developing members’ capabilities by building and exchanging knowledge.
- Some of the most successful asset managers are socalled index trackers offering their clients a market return at a low fee.
- A rather unpleasant side-effect is that luck is often mistaken or presented as skill. For those who still mistake randomness or luck for skill, Taleb’s “Fooled by Randomness” and “The Black Swan” are good readings.
- The number of CFA charter holders is still growing every year and is considered the global standard for investment professionals.
- Obviously when the investment universe is set wider than the benchmark, opportunities for excess return emerge again.
- Given the epistemological discussion mentioned earlier, this can not be considered knowledge as there is too much overriding evidence.
- There is a wide array of unrelated causal elements which have an impact on how prices move. This is called “noise” and is the arbitrary element in expectations (Black, 1986).
- Many deep and convincing stories are often produced only retrospectively to emphasize the rightness of the course of action.
- It must be said that Atticus Capital had very strong performance figures over the previous three years.