Investors with global portfolios of equities and bonds are generally aware that their asset allocation decisions, the proportions of funds they invest in the different asset classes, their regional exposures as well as the degree of currency exposure, are amongst the most important decisions they make (from an investments point of view).

When deciding on the appropriate allocation, they are usually comfortable making the simplified assumption that their investment objective is to maximise expected return for a given level of risk.

Asset allocation is the process of dividing investments among different kinds of asset classes, namely, equities, bonds, cash or even real estate in such a manner so as to achieve an adequate combination of risk and reward (known as the risk-reward trade-off) that is commensurate with an investor's specific situation and goals.

It is a known fact that the crux of the optimal asset allocation decision lies on what investors call diversification and investment managers refer to as correlation.

Managers of balanced funds tend to adopt the od structuring a portfolio of unrelated securities that tend to move in opposite directions (having negative correlation) so that when one asset class is weak, the return of the portfolio is improved by the better returning (stronger) asset class, thereby reducing losses with the potential of achieving better risk-adjusted returns.

However, what is more fundamental than diversification are they key risk measures and expected returns. Risk, return and asset correlation are the key measures fund managers use in their portfolio models in order to achieve the optimal asset mix between different asset classes. Hence the most important factor in asset allocation and financial modelling is the evaluation of risk.

The most widely used measure of risk is standard deviation; low standard deviation securities, such as short-term Treasuries and Bunds, are considered low risk, whereas highly volatile securities such as high yield bonds and equities represent high levels of risk.

In a portfolio optimisation model, investors specify asset classes and base the model on forward-looking assumptions for each asset class' return and risk as well as the co-movements (co-variance) among the asset classes. When portfolio managers utilise a scenario-based approach, asset returns are simulated based on these forward-looking assumptions after which an optimization algorithm is used to derive percentage allocations to different asset classes, better known as the asset mix.

The optimal portfolio concept, developed by Harry Markowitz in 1952 in his Modern Portfolio Theory, is one of the many used portfolio optimisation tools used by asset managers worldwide, primarily within the context of a portfolio of an array of asset classes, such as balanced funds (Modern Portfolio Theory is a theory of finance that attempts to maximise portfolio expected return for a given amount of portfolio risk by carefully selecting the proportions of various asset classes).

Sixty years later, financial modelling programs have been developed and engineered based on the fundamentals of this theory, and continue to prove that it is possible for different portfolio to have varying levels of risk and return. The key point is for an investor (portfolio manager) to decide how much risk to take on and then subsequently allocate the portfolio’s assets according to the risk profile in a diversified manner.

This article was issued by Mark Vella, business manager at Calamatta Cuschieri. For more information visit, . The information, view and opinions provided in this article are being provided solely for educational and informational purposes and should not be construed as investment advice, advice concerning particular investments or investment decisions, or tax or legal advice.


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