Are good months followed by good months?

Comment on ‘What is Value?’ – Mukul Pal, September 20, 2015.

Roxana Crisan
roxana.crisan@tralio.com

It’s shocking how Nobel Prize winning economists have relied on naive assumptions. Harry Markowitz [1] assumed that good months (performance) would tend to be followed only by good months and bad months by bad months. Was Harry correct in making such an assumption? No, he was wrong. Good months are not just followed by good months “Harry, sometimes good months are followed by bad months.”

‘‘What is Value? (Pal, 2015) covers aspects of the history of finance concerning the term ‘Value’. It states the origins of the term, its evolution and how ‘Value’ lost its statistical roots and acquired the current narrow fundamental definition. Along with the history, the author explains how this divergence between different definitions of ‘Value’ is the reason why a generation of economists has missed the big picture, failing to understand market behavior and consequently basing their models on incorrect assumptions. A wrong assumption could have been ignored if it was just any model. If it’s a model which forms the basis of Modern Portfolio Theory, the assumption can not be ignored. Could Harry’s assumption be the reason his efficient portfolio does not work? Pal, brings out such arguments in his paper.

Apart from the good month assumption, historically, price behavior has been studied only as a single asset price series. Even great discoveries like reversion, diversion, duration, linear assumptions, random walk etc. have been studied and treated individually. As a result group behavior was underresearched. “What is Value?” describes stock market as a framework that can explain not only a group of asset prices but also variables like sentiments or other non-capital market data. Pal defines the stock market as a non-linear system and uses the statistical definition of the term ‘Value’ to articulate the ‘Mean Reversion Framework’[2] (MRF), which harnesses the random with the non-random, linearity with non-linearity, explicitly acknowledging that relevance or irrelevance of data is linked to components’ state in the framework. A fascinating part of this paper is the revelation how the forces of reversion and diversion create and demolish momentum and why Nobel Prize winners like Harry Markowitz fall into such naïve assumptions that good months would tend to be followed only by good months and bad months by bad months.

The framework described in the paper is intuitive and it represents the real world fairly, especially because it analyses prices in a group of assets, dependent on others. What’s more, it takes into account that good months can be followed not only by good months but by bad months as well. Through this paper, the author makes a compelling argument for relying on the reversion-diversion process and discerning ‘Value’ rather a statistical idea, before giving it a fundamental character.

[1] Markowitz, H. M., Merton H. M., Sharpe W. F. The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 1990.
[2] Pal, M. “Mean Reversion Framework”, SSRN, 2015.