First Advisor

Blumenthal, Richard

Second Advisor

Ina, Donald J.


College for Professional Studies

Degree Name

MS Software Engineering and Database Technologies


School of Computer & Information Science

Document Type

Thesis - Open Access

Number of Pages

120 pages


Technical analysis of financial markets involves analyzing past price movements in order to identify favorable trading opportunities. The objective of this research was to demonstrate that a fuzzy logic stock trading system based on technical analysis can assist average traders in becoming successful by optimizing the use of technical indicators and trading rules that experts use to identify when to buy and sell stock. Research of relevant literature explored the current state of knowledge in methodologies for developing and validating trading systems using technical indicators and fuzzy logic trading systems, providing guidelines for the development and evaluation of the system. Evaluation of the system confirmed that fuzzy logic can have a positive contribution to a successful trading system, and that once a successful trading system has been developed and verified an average trader can be successful by simply following the trading system's buy and sell signals. The trader need not be an expert at interpreting the underlying technical indicators or react to price movements emotionally. The trading decisions are made by the trading system, so the only decision that the average trader need make is whether there is enough confidence in the system to commit real money in live trading. Suggestions for future research include improvements in accuracy and flexibility, and investigation of additional trading models and filters.

Date of Award

Summer 2011

Location (Creation)

Denver, Colorado

Rights Statement

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