Abstract
Given the popularity and propagation of automated trading systems in financial markets among institutional and individual traders in recent decades, this work attempts to compare and evaluate such ten systems based on different popular technical indicators in combination – for the first time – with the d-Backtest PS method for parameter selection. The systems use the technical indicators of Moving Averages (MA), Average Directional Index (ADX), Ichimoku Kinko Hyo, Moving Average Convergence/Divergence (MACD), Parabolic Stop and Reverse (SAR), Pivot, Turtle and Bollinger Bands (BB), and are enhanced by Stop Loss Strategies based on the Average True Range (ATR) indicator. Improvements in the speed of the back-testing computations used by the d-Backtest PS method over weekly intervals allowed examining all systems on a 3.5 years trading period for 7 assets in financial markets, namely EUR/USD, GBP/USD, USD/JPY, USD/CHF, XAU/USD, WTI, and BTC/USD. To evaluate the systems more holistically, a weighted metric is introduced and examined, which, apart from profit, takes into account more factors after normalization like the Sharpe Ratio, the Maximum Drawdown and the Expected Payoff, as well as a newly introduced Extended Profit Margin factor. Among the automated systems examined and evaluated using the weighted metric, the Adaptive Double Moving Average (Ad2MA) system stands out, followed by the Adaptive Pivot (AdPivot), and the Adaptive Average Directional Index (AdADX) systems. AcknowledgmentsWe would like to thank Dr. Christos Schinas for his time and invaluable guidance towards the methodology of the weighted metric. We would also like to thank Michalis Foulos for the hardware setup and support and Nektarios Mitakidis for his contribution to the representation of the results.This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK-02342).
Highlights
The systems use the technical indicators of Moving Averages (MA), Average Directional Index (ADX), Ichimoku Kinko Hyo, Moving Average Convergence/ Divergence (MACD), Parabolic Stop and Reverse (SAR), Pivot, Turtle and Bollinger Bands (BB), and are enhanced by Stop Loss Strategies based on the Average True Range (ATR) indicator
Other metrics used in the examined that can be used for evaluating the tradevaluation of trading systems can include the prof- ing systems, as well as a new factor, the Extended it factor, the expected payoff, and the profit mar- Profit Margin, which is used in the weighted metgin
The study regarding the comparison of high-frequency algorithmic trading systems in financial markets is broadened by implementing ten such automated trading systems, based on a widely used technical indicator
Summary
In the past couple of decades, the scientific and financial community has tackled an ever-increasing amount of work to develop software systems that trade automatically in the financial and stock markets around the world. These systems have become ubiquitous in the global trading scene, and a need to evaluate them becomes apparent. The current research examines and attempts to evaluate ten automated trading systems that are based on widely used technical indicators For this purpose, the d-Backtest PS method is used to select the systems’ parameters, and a weighted metric based on five factors regarding the consistency, risk efficiency, and profitability of the systems is introduced. The results of each backtesting method were compared using a range of weights for each factor of the weighted metric, that produced a classification of the automated trading systems performance
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