How everyone can prepare for a more unusual investment environment

At the intersection of Computer Science, Finance, and Statistics lies a mostly-hidden but powerful way to change the way people think about active and passive investment management. I believe being proficient in all three fields is important. Below, I show how to apply the power of Statistics to the other two fields:

0)  Randomly sample with replacement the 20-yr empirical, arithmetic return data from all asset classes and at a daily resolution.

1)  With this randomly-sampled data, re-create a completely different 20-yr data set - but intentionally adjust the mean return, standard deviation, excess kurtosis, skewness, covariance, etc. to something worse than what the original, empirical data showed.  We do this to reflect the expectation of more difficult market environment that many professional asset managers including myself are concerned about.

2)  Lastly, re-test your current investment strategies using this hostile data set to double check if you and perhaps your current asset manager are as prepared as possible to navigate a potentially more difficult investment environment in all asset classes on a forward basis (i.e. decreased expected returns and increased volatility). Then have the computer repeat the process 100's of times more to obtain more reliable bootstrap estimates of Sharpe ratios and other metrics around which confidence intervals may be formed.

In the above photo, I apply the same process to our low-fee, robo-advisor's models against just one potential future iteration of a more hostile data set - something that no investor has ever seen before. Investors should probably ask what their current asset managers are doing to pro-actively prepare for the future.