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Advisor First Steps in Constructing Capital Market Assumptions

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The 2008 market tailspin has put enormous pressure on advisors to better understand asset allocation strategies and risk management. Sophisticated and forward-looking modeling of capital markets assumptions is the foundation for building stronger portfolios, assessing their risk, and making Monte Carlo forecasts. Virtually every portfolio construction or modeling tool uses some form of capital markets forecasts. Some evaluate risk/return expectations based on long-term historical trends alone. Others anticipate potential volatility over a longer time horizon.

Some advisors are content to rely on traditional, historical-based forecasting methods. Others are ready to make a rigorous evaluation of their current methodology to determine if it is equipped to assess extreme long-term volatility. Understanding what you are using to determine your forecasts and believing in their validity are the first steps in establishing a foundation for portfolio construction.

Whatever an advisor’s stance, he or she needs to at least do some window shopping, armed with the list of categories required for testing any capital markets assumptions modeling tool. These categories include the following:

  • Expected returns
  • Standard deviations
  • Correlations

For each category, ask the questions below to review the proposed assumptions and their underlying rationale.

Expected Returns

  • How does the modeling tool/software formulate expected returns?
  • If the numbers are based on historical data, do you believe the historical period used will resemble the period of time on which they are based?
  • Do you have confidence in the numbers?
  • Have you compared the forecasts to other available forecasts sources, such as


those provided by asset management firms like JP Morgan or Blackrock?  

Standard Deviations

  • How are standard deviations determined?
  • Are they based on raw historical data?
  • What time period is used?
  • Do the benchmarks that are used match up to the asset classes you use?
  • Do the numbers seem reasonable to you?
  • How do the numbers compare to other sources?
  • Is there any error baked in to reflect that these are forecasts?


  • How are correlations calculated between different asset classes?
  • Do they use an asset class-by-asset class, pair-by-pair approach or do they use only the longest common time period and make a single estimate?
  • What time period is used?
  • Given what happened in that time period, do you believe the next five, 10 or 15 years are represented by the longest common time period?

If you can answer all of these questions to your satisfaction, you should stick with your capital market assumptions methods. If you answered “No” to any of these questions or felt the answer failed to pass the test, keep shopping.

Asset allocation analysis is complex – and only as good as the underlying forecast data and assumptions. With the right mix of asset classes, overall long-term risk and volatility can be potentially minimized, but they depend on the advisor’s ability to identify forward-looking, optimal risk-return strategies.

In our next article, we’ll take a closer look at the factors that drive our capital market assumptions, and what advisors are to make of them going forward.