Bloomberg news had an interesting article in their February 17^th magazine titled, “Selling Private Equity (PE) at The Superstore.” Yes, that sector of the market reserved for the very rich may soon be available as an ETF or mutual fund or both by VanGuard.  Isn’t that wonderful!  The retail investor will be able to put a few thousand dollars in PE that used to require $millions or $Billions.  That begs the question, who’s selling?  Wasn’t it just last year that I read about the hoards of cash PE companies were holding because they couldn’t find any worth while investments?  Some were even returning cash to shareholders.

My 60 years in the investment business tells me, anytime the institutional investors are selling something previously not available to retail investors, I should not be buying and neither should you.  You might say, If it is good enough for Warren Buffett to buy GEICO and Sees Candy and bring them private, why shouldn’t I get in on it?  Because you’re not Buffett and that was then and now is now. Also, last year Buffett warned:

“We have seen a number of proposals from private equity funds where the returns are really not calculated in a manner that I would regard as honest,” Buffett said Saturday at Berkshire Hathaway Inc.’s annual meeting. “If I were running a pension fund, I would be very careful about what was being offered to me.”

This is another indicator of a top in the market and a signal to stop buying equities and take profits.  To support this view, I provide the following update on some software my Colleague, Hal Forsey and I developed to provide a picture of the uncertainty you are facing in the stock market:

This may be a strange shape in Figure 1 for some of you. It is not bell shaped.  A bell shape implies you could lose an infinite amount of money and you cannot.  The Fed will make some banks bail you out like they did with AIG and Portfolio Insurance.  The bell shape calls for measuring risk as deviations about the mean and assumes volatility above the average return is just as risky as deviations below the mean.

We believe the mean is the wrong location point and deviations about the mean is the wrong measure of risk.[1]

                                                        Figure 1 

The shape in Figure 1 is a lognormal, given our inputs at the bottom of the graph. This version of the lognormal was developed by two professors at Cambridge University, Aitchison and Brown, and it allows the distribution to be flipped so that it is negatively skewed, as it would be at a top in the market.  I believe this is one of the greatest advancements in describing uncertainty yet devised. So, let’s flip it.

                                                     Figure 2

Only the sign of the extreme value has changed from negative to positive, causing the skewness toward negative returns. Now we measure reward and risk in terms of dispersion above and below the DTR, not the mean.  The DTR chosen is 8%, the most frequently used actuarial return by defined benefit plans.  Returns above this DTR will fund their plan within their cost constraints while returns below will cause them to be underfunded.  Risk and reward are thus directly related to the DTR, which cannot be said for standard deviation.  A DTR can be calculated for anyone investing to achieve a specified payout at a specified time.

We use Dr. Peter Fishburn’s proposed measure of downside risk (below target deviations) and measure reward (Upside potential) relative to the DTR in a ratio we developed with Professor van der Meer and his colleagues at Groningen University.  Here is how to interpret the ratio of upside potential to downside risk shown in Figure 2 above: 5.5% divided by 9.7% = .56, meaning, there is 44% more downside risk than upside potential.  Compare this to the Upside potential ratio in Figure 1 of .92, indicating only 8% more downside risk than upside potential and you see the difference between believing the outlook is positively skewed and believing it is negatively skewed.

Now, suppose you think the market will be more volatile than normal.  We accomplish this in Figure 3 by simply increasing volatility to 25%.

                                                       Figure 3

Note: The extreme kurtosis (pointiness) results in a 75.3% chance the return will be greater than the DTR, producing the potential to exceed the DTR by 8% for a total return of 16%.  Sounds even better than Figure 2?

That is a misleading statistic unless it is adjusted for risk as shown in the Upside potential ratio which has now dropped to .35.  Meaning, if volatility increases to recent levels, we are now facing 65% more downside risk than upside potential.

Conclusions:

Figure 1 represents my opinion of a best-case scenario.  If you truly believe these are normal times, don’t panic and sell positions you may never be able to restore at these levels. The almost equal trade-off between downside risk and upside potential indicates you are risk neutral, not, risk averse if you accept this trade-off. in that case a buy-hold strategy is appropriate.

Figure 2 is my most likely scenario.  The already dangerous levels of debt are bound to get higher in response to the corona virus impact on world trade and it is an election year and Bernie Sanders is leading the Democratic race.  Even Fareed Zakaria says, the worst outcome may be if he is elected President and is allowed by a Democratic Congress to implement his platform.  One thing both parties agree on is: the tech industry needs to be regulated and downsized. Therefore, the returns are probably skewed to the downside and the proper strategy would be to take some profits in tech stocks and put them in short term treasuries.

Figure 3 is my worst-case scenario.  Just like 2007 when people thought they could flip houses forever and the bull got killed after goring several financial matadors.  We all knew it would eventually happen but most (not me) believed it was far off.

You can download the “Forsey-Sortino” software free and change the inputs as you wish at:

https://drive.google.com/open?id=1j-lL2Y33dqHFBLdXfvNuKHZXtPvV7RxM

Instructions are provided in the readme file included in the download.

[1] For papers and books supporting this view see past postings on the right-hand side of this page.