Sherif Mourad


There is an ongoing controversy, whether technical analysis does provide useful information in the context of predicting future market trends and, therefore guided by technical trading systems investors can beat market performance. This controversy has motivated researchers across various markets to compare the performance of different technical analysis systems to market performance and see whether technical analysis does add value to the investment decision-making process. In our review of the literature, we neither came across any research that has utilized an actual trading platform in testing, nor one that has been conducted on the Egyptian stock market. The purpose of this thesis paper was to investigate the value of technical analysis in the investment decision-making process through a comparison of profitability between technical analysis systems and a passive buy-and-hold strategy. Our empirical testing utilizes a set of 10 popular technical trading systems and data from the Egyptian stock market. We ran a total of 220 simulations using MetaStock (one of the most popular trading platforms worldwide) as our trading platform, half of which were during an in-sample period where we optimize our systems’ parameters and the other half was during an out-of-sample period where we test our optimal parameters. Each system was tested on daily data of the EGX30 index, which is considered the main benchmark of the Egyptian stock market, and for robustness we re-test each system across a sample of 10 out of the 30 stocks that comprise the index. We found strong evidence of economically significant out-of-sample excess returns for the EGX30 index as well as for the 10 stocks over the period 7/2/2006– 12/31/2014. On average our set of technical analysis systems did substantially outperform the passive buy-and-hold strategy.


Management Department

Degree Name

MS in Finance

Graduation Date


Submission Date

February 2016

First Advisor

Bassiouny, Aliaa

Committee Member 1

El-Shahat, Ahmed

Committee Member 2

Ahmed, Neveen


102 p.

Document Type

Master's Thesis


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Institutional Review Board (IRB) Approval

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