Knowledge Management in Asset Management
Erasmus University Rotterdam (EUR) – Department of Financial Management
Stanford University – Global Projects Center
August 11, 2015
The idea that superior knowledge is required to drive financial outperformance runs counter to some of the most pervasive theoretical frameworks used by investors today. The Efficient Market Hypothesis and the Capital Asset Pricing Model, for example, posit that capital markets are efficient and that no consistent outperformance can be generated without increasing risk. Active asset managers, however, argue differently and claim that skills and knowledge are critical for capturing excess returns. We agree. In fact, in this paper we argue that knowledge assets and the use of superior knowledge are crucial to the success of all asset managers and, in particular, active managers. And yet, despite its clear importance, very little is known about knowledge management in asset management. This article thus seeks to remedy this by offering insight into the role that knowledge plays in the investment process and, more specifically, into the adoption of knowledge management by asset managers. The paper concludes with a blueprint that offers a way for investors to become knowledge and asset managers.
Knowledge Management In Asset Management – Introduction
Asset management refers to the professional administration and investment of financial assets to achieve specified investment goals and objectives. On the surface, asset managers have a simple and attractive business: They take an initial stock of money – what we’d call financial capital – and they put that money to work through the application of human capital (i.e., people), market intelligence (i.e., research, technology and networks) and governance (i.e., policies, processes and procedures). When these three inputs are combined effectively with an initial stock of capital, asset managers can generate attractive investment returns for clients and, in turn, revenues for their business and employees. Generally speaking, then, a successful investment organization is one that is adept at employing talented individuals in operating environments constrained by policies, processes and procedures in order to identify and then exploit informational advantages in a timely manner. This may seem to be a simple formula for success, but it raises important and complex questions. For example, what are the factors that allow for investment organizations – be they for-profit asset managers, such as hedge funds, or beneficial investment organizations, such as endowments or pensions – to develop and mobilize the inputs listed above? And, in turn, once the inputs are mobilized, can these investors substantiate their value? It’s in answering these questions that the business of asset management becomes rather complicated. In our opinion, the creation, maintenance and exploitation of ‘knowledge’ are critical to the success of any investment organization.
As Nonaka and Takeuchi (1995) define it, knowledge is about forming beliefs and making commitments; it is about putting information and data into action. As this implies, knowledge also goes to the heart of investment decision-making. And, if we assume that active management is a zero-sum game (or at least close to it), superior knowledge would seem to be the only way to achieve excess investment returns. While this may seem an obvious observation, it’s worth noting that this view actually runs counter to some of the dominant frameworks used by investors today (see Clark 2014). For example, the Efficient Market Hypothesis (Fama, 1965) and the Capital Asset Pricing Model (Treynor, 1961; Sharpe 1964; Lintner 1965) are based on the premise that capital markets are efficient and that no asset manager has superior knowledge over the broader market, believing that all possible information is reflected in current market prices and excess returns are simply a function of the level of risk taken.1 But, as you might expect, the community of active asset managers disagrees with these mainstream views, arguing that informational advantages do exist and that opportunities for generating excess returns can be identified in the market.2 This is a view that also seems to be in line with recent empirical research. For example, Harvey, Liu and Zhu (2014) identified more than 300 factors that affect equity returns in empirical literature. However, gathering and leveraging those factors in the context of trading requires developing formal policies for knowledge management. More general research also shows that all organizations, independent of industry, get value from knowledge management and that knowledge carries as much value as financial or even human capital (Grant 1996; Spender 1996). In short, the way an organization is structured will inevitably affect its ability to create, maintain and use knowledge – and it’s in the context of the organization’s design that knowledge ultimately drives performance.
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