We use these studies to evaluate the probable growth and structure of client liabilities to develop practical asset allocation recommendations that best meet liabilities over time.
The data from an actuarial valuation report is used to model key variables, including population distribution factors by categories such as age, service, pay, and benefit formulas. Once our initial modeling is completed, we use the same actuarial assumptions in the actuarial valuation to project the population/demographics, liabilities, contributions, amongst other characteristics. We believe this is the most accurate way to project future liabilities, as a preface to determining the appropriate asset allocation.
Once we have identified the various portfolios to test against the Plan liabilities, we then utilize specialized actuarial software to model assets and liabilities in tandem. The efficient set of feasible portfolios is evaluated using Monte Carlo simulation methodology in the context of the liabilities. This process involves evaluating thousands of potential future inflation scenarios given the significant impact it has on both assets and liabilities. For example, high inflation not only leads to poor performance in the stock and bond markets, but it also impacts liabilities. This occurs due to changes in the actuarial discount rate as well as potential increases in future benefit payments through cost-of-living increases and payroll adjustments.
The result of the Monte Carlo simulation process is a range of outcomes for each of the key Plan variables under a wide range of market conditions. These results can then be analyzed to determine possible funding outcomes and the affect different asset allocations would have on such outcomes. The final product of the study being the identification of investment portfolios that are most likely to meet an institution's unique expected future cash outflows or spending needs, while minimizing the risk that those needs will not be met.