More Downside Risk than Upside Potential?
Turns out potential investment risk / return expectations in the short run are often not represented as a normal distribution. Many times it can be positively or negatively skewed, offering additional upside potential for the amount of risk taken or more risk than potential upside.
So, assumptions of normally distributed returns in metrics used to develop an allocation strategy produces flawed analysis data? YES!!
Now that sounds like it can be useful! How can it be recognized?
Simple! Use a form of the lognormal distribution that can use negative as well as positive returns to skew the distribution either left or right. You just need the average return and standard deviation of each investment, plus a portfolio return objective. Given the improved shape, the model can then calculate better statistics.
The key forecasting element used is the Upside Potential ratio which has shown its superiority over the Sortino Ratio.
That “better shape” distribution is the brain child of two professors at Cambridge University, Aitchison and Brown. Better, in that one could have beaten the market more often than not over the past 26 years.
This paper “The Cost of Assuming Symmetry in a Skewed World” by Frank Sortino & Kal Salama offers a tool for recognizing those times when there is more downside risk than upside potential and vice-versa and how to manage it better by formally recognizing a different shape to uncertainty that is better suited to the task at hand.
If this sounds familiar too you at all, then maybe you have seen some of the references from Salt Creek Investors Active Allocation strategy. This work is a core component in the investment selection process for these SCI models. This is the part of our quarterly rebalance research and analysis that helps identify the mix of investment choices that creates optimal positive skew.
I encourage you to take a closer look at the paper and the Salt Creek Investors Platform.
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