TITLE

Constructing and Defending Core Portfolios in Chaotic Markets

AUTHOR(S)
Tomasula Jr., Paul D.
PUB. DATE
December 2009
SOURCE
Journal of Financial Planning;Dec2009, Vol. 22 Issue 12, p38
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Financial planners, investment advisers, and their clients are thrown when securities markets make outsized moves. This article will address the assumptions that market movements are best depicted by a normal, Gaussian distribution and that markets are totally random. It will incorporate existing and innovative approaches. Financial planning software, based upon modern portfolio theory or Monte Carlo simulations, tends to group the probabilities of market moves under the Gaussian distribution, that is, bell-shaped curve. This assumption leads to expectations and portfolios that may disappoint the owner A more suitable portfolio-generating software would accept other distributions as more encompassing of market movements. Having shown that the Cauchy-Lorentz distribution better fits market data than the bell-shaped curve, we then work to show that markets are not totally random. The computerized search allowing for the full range of market moves helps us understand two ways in which the markets may not be random. First, superior portfolios consistently bubbled to the head of the list. Second, when all of the alternative portfolios of a sample case were graphed, a broad and consistent organization became apparent. We show an example of a non-linear calculation producing random-appearing results as the outcome of a simple, deterministic formula. The generation of portfolios from raw market data and the illustration of random behavior from a deterministic formula point to portfolios as an emergent phenomenon. The pursuit of emergent phenomena leads us to the Santa Fe Institute's mission of discovering the profound simplicity underlying the complexity that surrounds us. Using their four simple rules of complex phenomena, we examine how slack can protect our portfolios.
ACCESSION #
46794663

 

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