An overview of technical analysis in systematic trading strategies returns and a novel systematic strategy yielding positive significant returns

This paper contributes to the literature on systematic trading strategies, in particular technical analysis profitability. We measure the profitability and forecasting power of a trend following strategy implemented in Python on a wide perimeter (205 European stocks, 11 industries, 7 major stock exchanges) over 8 years: from 2015 to 2022. The strategy signal is based on 4 moving averages and a trailing stop loss. We also introduce a mechanism based on trailing upper and lower price bounds to avoid false signals and limit transaction costs during lateral movements. We calibrate the iper-parameters to all stocks belonging to the same industry. The returns of the strategy applied to the constituents of the top performing industries provides a total return of 20% net of transaction costs, with an annualized Sharpe ratio of 0.54, in the out of sample time window from 2020 to 2022.