The Performance of Technical Trading Rules: A cross country approach
Why this work is in the frame
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Bibliographic record
Abstract
This paper tests the performance of the seven commonly used technical trading rules: dual moving average crossovers, moving average convergence divergence, channel breakout rule, Bollinger bands, relative strength index, stochastic oscillator and directional movement index across six developed countries: USA, UK, Canada, Germany, Australia and Spain by using the data of three companies having highest market capitalization from each country. The period of study is from 1 January 2005 to 31 December 2010 and is divided into three sub-periods of two years each. Overall our results provide existence of positive excess returns over buy-hold strategy in all the countries for lower transaction cost and negative excess returns for higher transaction cost. Also most of the excess returns are negative during the sub-period 2007-2008 when there was recession in the developed countries. The Moving Average Convergence Divergence has outperformed every other rule. It has shown positive excess returns and positive Sharpe’s ratio across every company and in every sub-period. The Channel Breakout Rule shows positive excess returns and Sharpe’s ratio in many cases for the sub period 2005-2006 and the Dual Moving Average Crossovers shows positive excess returns and Sharpe’s ratio in many cases for the sub period 2009-2010. The performance of combination rules did not exceeded to that of Moving Average Convergence Divergence and was more than Channel Breakout Rule and Dual Moving Average Crossovers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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