We offer traditional mean-variance optimised models. But we also specialise in outcome-oriented, or goals-based, investing. We don’t believe that adopting a portfolio allocation based on a single risk score, or considering risk purely in terms of standard deviations, is the best way to achieve client objectives. For example, a client may have a superannuation portfolio with a fifteen-year investment horizon and low tax rate, and an investment portfolio where the investment horizon is much less certain and the marginal tax rate is much higher. Obviously, these make-up of the two portfolios should reflect those important differences.
In order to achieve the desired outcomes, we believe in looking at time horizon and tax environment first and foremost in order to shape the strategic allocation. There is also much greater emphasis on the direction and frequency of cash flows when it comes to implementation. We use a variety of risk measures, focussing on the most relevant to the particular strategy. We then use our forward expected returns and implementation techniques to dynamically allocate the portfolios to achieve the objectives with the greatest degree of certainty possible.
Our model portfolios are organised by tax environment and by objective, leading to a higher number of models than you would normally find. We try to be platform-neutral, so we produce policy portfolios and then adjust them for different platforms where certain products might not be available.