eprintid: 159
rev_number: 4
eprint_status: archive
userid: 6
dir: disk0/00/00/01/59
datestamp: 2008-10-07
lastmod: 2015-05-29 19:48:23
status_changed: 2009-04-08 16:55:00
type: report
metadata_visibility: show
item_issues_count: 0
creators_name: Tsao, Min
creators_name: Aggarwala, Rita
creators_name: Aurag, Hassan
creators_name: Paulhus, Marc
contributors_name: Amjoun, Benyounes
contributors_name: Calistrate, Dan
contributors_name: Caprioglio, Myriam
contributors_name: Hawkins, Brenda
contributors_name: Kjiri, Mounia
contributors_name: Koziak, Tamara
contributors_name: Lemaire, Vincent
contributors_name: McVean, Jason
contributors_name: Powojowski, Miro
contributors_name: Reed, Bill
contributors_name: Tomoda, Satoshi
contributors_name: Zhou, Julie
title: Efficient Portfolio Selection
ispublished: pub
subjects: utilities
subjects: finance
studygroups: ipsw3
companyname: Merak Projects Limited
full_text_status: public
abstract: Merak believed that an efficient frontier analysis method that combined the robustness of the Monte Carlo approach with the confidence of the Markowitz approach would be a very powerful tool for any industry. However, it soon became clear that there are other ways to address the problem that do not require a Monte Carlo component.

Three subgroups were formed, and each developed a different approach for solving the problem. These were the Portfolio Selection Algorithm Approach, the Statistical Inference Approach, and the Integer Programming Approach.
problem_statement: If portfolios made up of a selection of petroleum projects are plotted on a graph of expected value versus risk, there is an upper bound above which no portfolios are found. This upper bound is known as the efficient frontier.

The goal for this project is to address the weaknesses of two approaches to efficient frontier analysis, one developed by Harry Markowitz in the 1950s using matrix algebra, the other developed by Merak based on Monte Carlo, perhaps by combining or partially combining them.
date: 1999
date_type: published
pages: 17
citation:   Tsao, Min and Aggarwala, Rita and Aurag, Hassan and Paulhus, Marc  (1999) Efficient Portfolio Selection.  [Study Group Report]     
document_url: http://miis.maths.ox.ac.uk/miis/159/1/portfolio.pdf