Wall Street’s mistaken reliance on price correlation

Diversification and balance

Things that don’t count

Our subject is diversification and the blind reliance many investors place on the statistical correlation of prices.

Howard Marks writes: “it’s the rare investor who achieves the sophistication required to appreciate correlation, a key element in controlling the riskiness of an overall portfolio.” (Marks, 2013)p.219

Correlation is not a term most people are familiar with. It is the mutual relationship between two or more things. In finance and investing it is most often thought of as price statistical correlation. Like much of statistics this can lead you down the garden path.  

Would you believe that there is a 95.24% correlation between people who drowned after falling out of a fishing boat and marriage rates in Kentucky? Check it out for yourself at https://www.tylervigen.com/spurious-correlations

This example illustrates the problem that many things correlate statistically that have no mutual relationship.

There is a further problem that ties directly into our diversification question. That is the problem that many things that can be counted don’t count. This delightful bit of wisdom has been attributed by many to Albert Einstein. The author apparently was a Professor of Sociology named William Bruce Cameron. The full quote from the 1960s is: “Not everything that can be counted counts, and not everything that counts can be counted.”

Wall Street has succumbed to counting things that don’t count. Since about 1952 when Harry Markowitz did his work on diversification, volatility and risk, the world of finance has come to accept that using price correlation tools, investors can combine in one portfolio investments of similar riskiness and reduce the overall portfolio risk to less than the riskiness of the individual components.

Carrying out price correlation analysis is child’s play for computers. The counting is easy. The flaw in this approach is that price correlation does not count for very much in assessing the mutual relationship of the different holdings in a portfolio. Back testing will come up with all sorts of neat correlations. But they are measuring something with very little relevance, price, and calling it a proxy.

The best way to take advantage of the free lunch offered by diversification is to carry out a business analysis assessing the mutual business and business sector relationships of the various components of the portfolio. The worst way is to put blind faith in quantitative analysis based on erroneous theories and a naïve faith in statistics.

Want to read more about the issues raised in this post, take a look at Chapter 36. Diversification, Balance and Strategy, 36.01 Correlation, 36.03 Correlation continued, 16.05 Cause and correlation, 16.06 Causal connections based on pure narrative and supposed correlation

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