One of the important roles for the advisor is to help determine the right risk level for their client’s goals and circumstances.
Logia constructs and maintains a range of asset allocation models to serve investor needs across the risk spectrum. The models and their corresponding objectives are based on a target level of risk that advisors can match to their client’s risk tolerance and capacity. Modeling is based on forward-looking market forecasts, not historical data.
The formation of the models begins with a definition of the investable universe. Constraints and exclusions may be made for practical purposes without materially impacting the potential performance of the models.
Allocations for the eligible assets classes are based on capital market assumptions. Equity forecasts start with the Schiller P/E 10 for the S&P 500, and then use relative valuation models to set forecasts for sub-asset class returns. Bond returns are largely forecast based on the implied forward yield curve and credit spreads. Other approaches may be used for more esoteric asset classes as needed.
These return assumptions, standard deviations, and correlations are used as inputs to mean variance optimization to drive allocations. As a practical matter, the optimization is constrained to generate allocations that meet client and advisor expectations and control tracking error to the overall benchmarks.
The result is a set of asset models that forward-looking assumptions suggest are efficiently allocated. Models are reviewed periodically against updated capital market assumptions, and adjusted as needed.