Why we rather pick the food supplier to space colonies than the shuttle manufacturer.
We look for “good” companies to constitute a well-diversified portfolio of equities and from time to time we want to re-allocate to avoid negative changes in the future financial development of our holdings and thus mitigating portfolio volatility. For the latter we have developed sophisticated models based on the belief that uncertainty in equity markets is translated into volatility leading us to the simple conclusion that “low-volatility” stocks represent “better” companies than stocks with higher volatility.
In addition, we are also of the opinion that variance amongst stocks should be controlled to find a smoother path to financial portfolio returns. Minimum variance controls portfolio volatility and allows for a wider dispersion of the type of companies that contribute to the overall return of a portfolio.
Thirdly we believe that history is a very good predictor of the future. A company that has been paying dividends for the last thirty years is likely to continue to do so, and a company with an above average peer-to-peer EPS-growth the last fifteen years is likely to stay above average. So, to summarise simplistically we like quality and portfolio construction.
Sounds like a pretty good recipe to apply when investing for the long term in equity markets doesn’t it? Oh, I forgot to mention large data sets, fast processing power, sophisticated portfolio optimization techniques to add to the mix.
Still our well balanced and tried recipe, has, over the last twelve months been rejected as one that has left a bad taste rather than delivering on its promise, or statement, given the that the world of financial products comes with extensive disclaimers. Low volatile stocks representing quality companies are now deliverers of disappointing returns.
In argument of the above we would argue that we make investments for the long term based on known facts put into a robust quantitative framework that can predict future volatility of stocks, filter relevant measurable fundamental key metrics and their inherent trends. We would also argue that a logical interpretation of large sets of data together with data processing power allows us to gain a competitive advantage. We take all these systematic steps into building a robust portfolio that can benefit from the attractive risk premiums that equity markets carry and by applying mathematics and statistics we want to mitigate future investment losses.
The Space Shuttle
What if we would disregard all this boring risk avert nonsense and just go for serious cash and future wealth? Let´s re-program everything with a very binary algorithm that will search for all or nothing. If that algorithm would be able to sound it would scream “buy TSLA”. The stock has had an annualised return of 65% since 2010, hardly any earnings; loaded with volatility and if you make an investment by assuming the annualised return, a USD 10 000 investment today will leave you with a handsome USD 18,000,000 in fifteen years from now. Apply the same compound rate on Tesla’s market cap of roughly USD 700bn; you can tell that there are some ETF:s that will just leave this stratosphere and find another investment galaxy to thrive in.
The Food Supplier
In contrast to the ballistic stock missiles, yes you would have guessed by now that our models do not pick Tesla, what kind of listed corporations would you find in a quantitative, systematic, global equity portfolio such as CIMalgo’s? In our unconstrained, equally weighted global large cap portfolio Hormel Foods Corporation is one that has been observed many times as a constituent. Its IPO took place on October the 1st in 1928. Since 1980 it has posted an annualised return of 16,21% with dividends invested, of which 13,73% is the price return.
A historically steady earnings and revenue growth gives our models comfort and visibility selecting Hormel Foods from an agnostic point of view. From time to time our algorithm might detect changes in the data stream which can lead to an exclusion of the stock until we have been able to separate the signal from the noise. One such moment in the future might occur when we start to populate planet Mars. Surely , by then, Hormel will be able to benefit from that technological leap in being a profitable supplier of foods to the earthlings in a galaxy far, far away. So far we are pretty sure that technological advances in data mining and processing power will separate the wheat from the chaff in equity investing, however investors will always look for earnings, income, sales, dividends, and financial growth. That will never change, not even if you trade stocks in a space colony on Mars.
André L. Havas