Our approach is active because we believe that markets are not efficient.

Beating the benchmark is not easy. In our case, it involves a well-structured, very detailed process of numbers-crunching (the ‘Machine’ part) and analysis of supply and demand conditions (the ‘Man’ part).

See Philosophy 1: Man-Machine

One thing should always be kept in mind; it is not easy to consistently provide clients with good advice. Financial markets are dynamic entities with price formation a function of dozens of return and risk factors. Risk management is, therefore, critically important as well.

See Philosophy 2: Near Optimization

Philosophy 1: Man-Machine

Prices in financial markets are the result of supply and demand actions by individuals, be they private, professional, or institutional investors. Their actions are not error-proof, but on average, point estimates of market valuation as derived by actual prices aren’t that bad either. We are, therefore, active investors that understand and respect market efficiency thinking. Generating excess returns is a difficult job when properly taking risk into account. However, it is not an impossible task, as we have shown in the past and will continue to show in the future.

As mentioned above, markets are, on average, quite often correct. However, human beings make mistakes. Behavioral finance has indicated that excess volatility stemming from the fact that human actors, as a group, are sometimes too optimistic and, at other times, too pessimistic with respect to the outlook for markets. This is where a well-structured system encompassing state-of-the-art risk management can benefit, but if, and only if, this system is continuously updated to ensure that new pieces of information are incorporated.

The combination of a market that gets things right most of the time, but terribly wrong in periods of exuberance or crisis, provides the conviction that the only way to get things right most of the time, while at the same time minimizing losses when markets go crazy (either way) is:
A structured, quantitative approach that ensures rigorous and solid risk management (Machine) that
Incorporates, as essential, embedded elements of the system analyst judgments supported by algorithms that capture the human behavioral aspects of market valuation (Man)

Philosophy 2: Near Optimization 

Not surprisingly, risk management plays an important role at Compendeon. The long-lasting relationship with Dr Markowitz, who received the Noble Prize for his contributions to risk management in financial markets, has certainly contributed to that sensitivity.

Our quantitative approach ensures that we will only look for excess return (alpha) to the extent that risk, as measured by market sensitivity (beta), volatility and other factors incorporated into our forecasting and risk models, have been properly accounted for. We are, at all times, cognizant of the fact that after an unexpected negative result, a bigger plus is needed to compensate for it.

The Financial Analysts Journal published the important Markowitz – Van Dijk contribution to risk management (Near Optimization) in its March/April 2003 issue. MIT Professor Mark Kritzman has performed important empirical tests indicating that our approach (re-labeled by him as the Markowitz – Van Dijk heuristic) provides superior results when comparing it to other practitioner approaches to portfolio rebalancing. This is, of course, just one of the many possible applications of our risk framework.

As part of their collaboration in integrating return and risk management, Markowitz and Van Dijk have also written a seminal chapter on the topic in the Zenios, Ziemba Handbook on Asset and Liability Management, North-Holland Science Publishers, 2006. We believe that a good GTAA system should be embedded in the strategic allocation (ALM) of investors in general and institutional investors in particular. As such, our GTAA approach encompasses the possibility of embracing ALM output as an essential starting point for our work.