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Essay / Research Paper Abstract
This 9 page paper looks at three different articles that use linear programming to help in the decision making processes for investments. The articles and methods are compared and the value of linear programming as a decision tool are considered. The bibliography cites 3 sources.
Page Count:
9 pages (~225 words per page)
File: TS14_TElinprg.rtf
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Unformatted sample text from the term paper:
limited resources. From manufacturing though to investment, the tool has the power to provide information and help informed decision making processes. In this paper three articles are examined which all
consider the use of linear programming for investment decision making processes that are aided by linear programming. Trading of NASDAQ stocks on the Chicago Stock Exchange (Lau et
al, 1996) Written in 1996, this article looks at the benefits that are perceived by investors when looking to purchase NASDAQ shares though the Chicago Stock Exchange (CSE). Linear programming
is used to look at the occurrence of spreads in two similar portfolios of shares, one mane up of NASDAQ shares that can be bought through the CSE and one
of NASDAQ shares that cannot be bought through the CSE. As investors will often look to gain benefits from spreads, with a system set up allowing investors to deal directly
with each by placing limit orders on the stocks and avoiding the need for a broker, the attraction of NASDAQ stocks bought through the CSE may be understood (Lau et
al, 1996). In 1986 it had been decided by the Securities and Exchange Commission (SEC) to allow some NASDAQ stocks to be traded though the CSE in order to
increase the level of competition. The NASDAQ shares that could be bought in this way were limited to the most actively traded NASDAQ shares (Lau et al, 1996). The article
undertakes primary research by setting up two investment portfolios, one is made up of 100 NASDAQ stocks that are traded on the CSE, the second is set up with NASDAQ
only stocks, this time 1,480 stocks are included in the portfolio (Lau et al, 1996). The portfolios were chosen with matching variables, such as assets. Then, with the help of
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