Abstract
The predictive ability of technical trading rules has been studied in great detail however many papers group all technical trading rules together into one basket. We argue that there are two main types of technical trading rules, namely rules based on trend-following and mean reversion. Utilising high-frequency commodity ETF data, we show that mean-reversion based rules perform increasingly better as sampling frequencies increase and that conversely the performance of trend-following rules deteriorate at higher-frequencies. These findings are possibly related to noise created by high-frequency traders.
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