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Means to a blend

Blending managers in a multi-manager structure is the task of optimally combining managers that offer complementary characteristics and should enhance performance potential within a more efficient risk framework. It is as important as choosing the managers in the first place.

To do this, it is important to understand the many different characteristics of each manager and their often complex processes. An effective multi-manager team needs to have a sound understanding of the principal risk and return drivers of different markets.

The process employs qualitative and quantitative analysis and incorporates the use of historic information, such as drivers of risk and return and forward-looking judgement. The quantitative part is focused mostly on breaking down and analysing risk exposures. This can provide important insights into the differences between one manager and another and therefore their potential complementary nature.

The risk that drives excess returns can be the result of emphasising benchmark-related risks, generally known as beta, that are identifiable and can be captured by risk systems. It can also be the result of undertaking non-benchmark-related exposures, generally known as alpha sources. It makes sense to focus on combining alpha sources as we consider these to be more predictable and persistent. Alpha sources can include investments in stocks not in the chosen benchmark or stocks in the benchmark which move differently from their industry/sector/country/region peers. Such investments are typically the result of a particular competitive edge that a manager may enjoy. Unless there are long-term structural rewards for beta exposure, it does not make sense to introduce such biases because beta exposures are difficult to time and may not always deliver a positive return.

There are a number of sophisticated risk systems at a multi-manager’s disposal. These tools provide a useful starting point by providing access to detailed information regarding historic risk exposures and sources of returns of chosen managers. Quantitative models require compromise to enable them to cope with the complexity of real world financial markets. With this in mind, a good multi-manager investment process should draw not only on risk model outputs but also on the team’s accumulated experience and understanding of the manager’s philosophy, process and likely risk-taking behaviour to create a blend that achieves adequate diversification as well as sources of alpha. The end result aims to achieve enhanced returns while lowering volatility.

Nick Pothier manages the HSBC open global return fund


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