Testing the Effect of Technical Analysis Strategies on Achieving Abnormal Return: Evidence from Egyptian Stock Market
Why this work is in the frame
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Bibliographic record
Abstract
This study examined the effect of using inter and exit signals of three of the most common used technical analysis strategies on achieving abnormal return compared with the buy and hold strategy in the Egyptian security market. The tests were done using data for short term, relatively long term, during bull and bear market. Using bootstrap methodology and wilcoxon/mann-whitney test for daily closing prices during the period from 1-1-1998 to 14-1-2016, the results indicated that; First, market timing with technical analysis yields more return and reduces risk in general. Second, short term investing is not recommended at all, as it is less profitable even than bear market period. Third, in long term and during bull market technical analysis is more profitable than short term. Fourth, technical analysis importance have been reduced during the last few years due to the effect of the Egyptian revolution on the security market. As for investors, they should use technical analysis trading rules to determine when to enter and exit the market, so that they can improve their investment decisions, as it leads to achieve abnormal return and reduces risk more than buy and hold strategy in all cases, while pay more attention for the current and political events than before.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.064 | 0.163 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it