Comparisons of investment standard deviation over multiple time periods

I swear it’s not as boring as the title sounds...well maybe it is

In the last post, we saw a colorful chart that compared total return for stocks and gold versus the S&P 500 over various time periods. We obviously want to make more money when we invest but the other side of the equation is the risk we take on to get a return on our investments. Having a diversified portfolio that is simply split between gold and stocks decreases our risk significantly:

Just like in the previous analysis, a couple time periods stand out as big winners or losers. The first is for the short time periods at the start of 2006 and 2007, where a 50/50 portfolio had more deviation than just stocks. The second is for the start of 2020, where a 50/50 portfolio had much less deviation!

The key difference between the standout periods between this analysis and the previous analysis, is that they are focused on the short time periods. In the total return analysis, the really good or really bad periods were heavily skewed toward longer time horizons.

While in the short run you can’t guarantee a less risky portfolio, in the long run the performance becomes clear. Let’s make it even clearer by only highlighting the time periods where a 50/50 portfolio deviation was worse than 100% in the S&P 500:

To me, that chart is convincing. With a few exceptions in the short term and only two exceptions of at most a two-year horizon, a 50/50 portfolio always has less risk than a 100% S&P 500 portfolio over this analysis timeframe. That’s the power of diversification.

If we remember the hot spots on our total return analysis, we also can see that, whether in the case of better or worse return, those periods still had less deviation. We can’t promise that a diversified portfolio is going to make more or less money but we can generally say that it will be a smoother ride toward your inevitable happiness or disappointment compared to the returns of a less diversified portfolio.

In the next post, we will integrate both approaches into one return-to-risk analysis to see the combined interaction between both effects.