Monte Carlo analysis is a better way to a retirement planning approach to the standard “straight-line” retirement projection, because it s considerate not only average returns, but a range of probable volatile returns, allowing the prospective retiree to understand how the retirement plan might fare in many situations. However, with the additional capability illustrates many volatile returns – potentially across multiple investments or asset classes – comes a greater burden to craft appropriate investments assumptions for the Monte Carlo analysis. Otherwise, there’s a risk that the Monte Carlo analysis could mis-state the risks of various retirement portfolios.
The key issue is that when selecting investment assumptions for a Monte Carlo analysis, there are three core points of data that are necessary for each investment: expected return, volatility, and correlation. And correlations are much more challenging assumptions, because an assumption is needed for the relationship between each investment and every single other investment paired to it! And a rising number of investments necessitates dramatically more correlation pairs – as a result, 3 investments requires 3 correlations, but 5 investments requires 10 correlations, and 10 investments requires assumptions for a whopping 45 correlation relationships!
And the reality is, given the underlying math of a Monte Carlo analysis, even making no correlation assumption is a guess. It’s just an implicit assumption of zero correlation… which is actually a very dangerous assumption, because, in the real world most investments don’t have zero correlation. Yet by assuming zero correlation when the correlation is actually higher, the projection ends out overstating the benefits of diversification, and therefore understating the risk to the retiree and overstating their probability of success in retirement!
In the end, this doesn’t mean it’s bad to have a diversified portfolio, but it’s crucial to recognize that adding more investments to a Monte Carlo analysis doesn’t necessarily make it more “accurate”, and in fact will decrease the accuracy of the projection unless the entire correlation matrix is properly included (with appropriate assumptions). As a result, a better practical approach for many advisors may be to utilize simpler two-asset-class portfolios of stocks and bonds for Monte Carlo purposes… as while this may slightly understate the benefits of having a fully diversified portfolio, at least it won’t overstate the benefits, and it is far easier to help a client adjust to a retirement that is going better than expected, than to adapt to one that is going worse!