Abstract/Details

Technical analysis based on moving average convergence and divergence


2010 2010

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Abstract (summary)

A trading strategy based on moving average convergence and divergence was defined and analyzed. Theoretical connections between moving averages, trader psychology and behavior were explored. Under model assumptions, the expected behavior of moving averages was analyzed. The question of whether or not the trading strategy was economically significant was explored using two historical sets of financial market data. A new test was described for examining the economic significance of any trading strategy. It was shown that this test also evaluates other predictive schemes in a variety of possible contexts.

The most significant findings of the study included that observed relationships between price movement and averages do not imply the existence of predictable market dynamics; that in one given data set, the trading strategy shows economic significance over a long time period; and that the new test proposed correctly identifies important properties of the trading strategy related to economic significance. The study also highlighted several practical concerns and limitations when implementing this particular trading strategy, or any strategy in general.

Indexing (details)


Subject
Applied Mathematics;
Finance
Classification
0364: Applied Mathematics
0508: Finance
Identifier / keyword
Social sciences; Applied sciences; Convergence; Divergence; Moving average; Trading rules
Title
Technical analysis based on moving average convergence and divergence
Author
St John, David
Number of pages
96
Publication year
2010
Degree date
2010
School code
0799
Source
DAI-B 71/12, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781124308111
Advisor
Knessl, Charles
University/institution
University of Illinois at Chicago
University location
United States -- Illinois
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3431286
ProQuest document ID
762997972
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/762997972
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