- Model PortfoliosCreating preset Model portfolios of assets can be a quick and efficient method of offering your expertise to clients. Based on the analysis of the client’s Risk Profile and the current portfolio the advisor can expand or reduce the list of available assets and assign specific investment vehicle. In some cases advisors might offer a complete portfolio (assets and securities), but it is not recommended prior to your initial evaluation and analysis. These Models might include one or more variations for each of the following:Capital Preservation Income Growth & Income Growth Aggressive Growth
- Forecasted Returns (standard deviations, correlations)In order to evaluate the performance characteristics of the recommended portfolio and comparison with the current portfolio, it would be appropriate to forecast expected returns for the near term (1-5 years). Clearly, your return assumptions will materially affect the probable performance.
- Subjective Analysis of Alternative Investment ScenariosIn some cases advisors may simply be able to add or substitute asset classes iteratively based on alternative scenarios and manually modify allocations. The advisor would then run each scenario through the analysis procedure to determine if any of these portfolios will provide suitable returns within established risk parameters. While this is extremely subjective and time consuming, it may offer both the advisor and the client a better understanding of the various trade-offs suggested by each iteration.
- Find Theoretically Optimal PortfoliosOptimization is the process of mathematically determining those combinations of investments (assets and/or securities) that will achieve the highest possible rate of return for any level of risk that an investor is willing to accept. In general, it is recommended that advisors optimize portfolios at the Asset Class level. Once this has been done, the advisor can find investment vehicles that are coordinated with the selected Asset classes and compliant with the investor’s risk and objectives.
Method of Optimization: AdvisoryWorld’s applications employ a highly sophisticated quadratic (multi-factor) mean-variance optimization algorithm. This algorithm calculates optimal solutions using the asset and/or security rates of return, standard deviations, correlation coefficients, covariances, and maximum or minimum constraints assigned at the asset type, asset class or security levels. An Efficient Frontier curve is displayed which includes alternative portfolio solutions. Users can calculate optimal portfolios on a pre-tax or after-tax basis, with management fees, or net of inflation.
When using strictly historical data, optimizers may be unequivocally relied upon to provide the optimal portfolio in terms of return and “risk” for the specified time period. For example, using a time horizon of 1985 to the present, the optimal portfolio displayed would have been the “optimal” portfolio for that time period. Unfortunately, there is no statistical evidence to support the idea that returns will ever repeat themselves at any time in the future. Therefore, it is extremely important that the advisor carefully determine the underlying assumptions that are being used in the system.
If you believe that the next 12 -60 months will be somewhat inflationary, then you might want to use an historical time period that was, in fact, inflationary such as 1975-1980, or 1987-1990. Using this time horizon allow you to calculate the correlations and standard deviations which actually may exist in this type of economic environment. Then forecasting rates of return for the next 12-60 months might give you a better scenario for the portfolio you are designing. Again, there is no guarantee that future returns will actually be reflected by these forecasts or the displayed values for the portfolio.
When using the optimization function the application will first find the optimal portfolio that will achieve the highest possible rate of return without exceeding the Minimum ROR specified for the client. This value is the greatest amount of downside risk (real or nominal loss of principal) in any 12 month period that the client is willing to accept.
The same algorithm will solve for those portfolios that can be expected to achieve the client’s goals. Using Cash Flow & Financial Plan Analysis, the advisor can quickly determine if the current or proposed portfolio will achieve the client’s goals while remaining within their tolerance for risk.
Are there any asset constraints (minimum/maximum amount allocated to specific assets)?
If your client currently holds investments in long-term, illiquid assets, the portfolio will be constrained by the capital committed to that asset. The advisor should not arbitrarily constrain the portfolio assets (assign minimums and maximums) before optimizing the portfolio. It is strongly recommended that the advisor optimize the portfolio and then iteratively set minimum or maximum levels for each asset (or you may set global minimums or maximums of some amount) until the portfolio meets your satisfaction.
If you believe that the optimization algorithm has allocated too much or too little to a particular asset, you should review the returns before setting constraints. It may well be that the asset in question has a rate of return far higher than you are comfortable with. Consequently, you should lower the return estimate and then re-optimize. You should find that the allocation is materially different using the new ROR estimate.
A good example of the foregoing would have been the Pacific Rim index in 1988-89. At that point the index return for the past 10 years was around 21%, far higher than most advisors were willing to forecast for the next 12 – 24 months. By lowering the forecasted return to the 10% level the allocation to Pacific Rim securities dropped from 80%+ to around 12%. This allocation was predicated on the asset’s forecasted ROR, historical STD and its relationship to each other asset in the portfolio, and not some arbitrary figure that would have been incorrect in relationship to the other assets and the portfolio as a whole.
The reason for not pre-setting constraints is that there is no way the advisor can know precisely the mathematical relationship of each asset to each other asset in the portfolio. Consequently, pre-setting constraints may have the adverse effect of tilting the portfolio in the wrong direction.
6. Finding Appropriate Investment Vehicles.
Once the portfolio asset class allocation has been established the advisor will find those investment vehicles that match the performance characteristics of the asset classes (rerun, standard deviation, correlation to appropriate benchmarks).