Empirical investigations began in 1981 at the Pension Research Institute (PRI) at San Francisco State University.
Dr. Hal Forsey and Dr. Frank Sortino were trying to apply Peter Fishburn's theory published in 1977 to Pension Fund Management.
Mr. Rom coined the term PMPT and began using it to market portfolio optimization and performance measurement software developed by his company.
The first publication in a major journal was co-authored by Sortino and Dr. Robert van der Meer, then at Shell Oil Netherlands.
These concepts were popularized by articles and conference presentations by Sortino, Rom and others, including members of the now-defunct Salomon Bros.
By defining investment risk in quantitative terms, Markowitz gave investors a mathematical approach to asset-selection and portfolio management.
It has long been recognized that investors typically do not view as risky those returns above the minimum they must earn in order to achieve their investment objectives.
[2]" Recent advances in portfolio and financial theory, coupled with increased computing power, have also contributed to overcoming these limitations.
In 1987, the Pension Research Institute at San Francisco State University developed the practical mathematical algorithms of PMPT that are in use today.
This is consistent with observations made on the behavior of individual decision-making under where d = downside deviation (commonly known in the financial community as 'downside risk').
The continuous form permits all subsequent calculations to be made using annual returns which is the natural way for investors to specify their investment goals.
Our ability to make these statements comes from the process of assuming the continuous form of the normal distribution and certain of its well-known properties.
[4] Volatility skewness is the second portfolio-analysis statistic introduced by Rom and Ferguson under the PMPT rubric.
Thus, with the recent advent of hedging and derivative strategies, which are asymmetrical by design, MPT measures are essentially useless, while PMPT is able to capture significantly more of the true information contained in the returns under consideration.
Many of the common market indices and the returns of stock and bond mutual funds cannot themselves always be assumed to be accurately represented by the normal distribution.