ANALISIS IMBAL HASIL DENGAN AUTOMATIC TRADING DALAM PERSPEKTIF MONEY MANAGEMENT : Studi Eksperimental dengan Expert Advisor pada Pasar Futures

  • Candra P
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Abstract

In this study an experimental study was using automatic trading by develop an expert advisors to works with backtesting simulation from January 2010 to December 2019 to research the performance returns of the double moving average cross strategy with 6 pairs from SMA (10.30), SMA (10.50) and SMA (10,100) and EMA (10,30), EMA (10.50), and EMA (10,100). EMA performance (10.30) that given treated 3 types of money management methods, namely fixed lot, fixed % lot, and martingale (1.5x) in the GOLD futures market (XAUUSD) at 1 hour timeframe which will be compared with descriptive analysis. This study shows that the EMA (10.30) without using money management (fixed lot) method shows the most optimal results with a total return 63.5% in the futures market which is higher than the passive strategy. The experimental results show that the fixed % lot method decreases performance with lower returns and increases risk when compared without using money management (fixed lot). While the most optimal money management method is martingale (1.5x) with the achievement of a total return 6,610.56% and a risk adjusted ratio (RAR) at 5.02%. Individually, the method that gives the highest yield is shown by EMA (10.30) on the fixed lot method with a total return of 63.5% and RAR at 2.41%, EMA (10.30) on the fixed sum lot method with a total return of 62.77% and RAR 1.52% and EMA (10.100) with a total return 6.610.56% and RAR 5.02% on the martingale method simulated using expert advisors in the futures market.Keywords: Moving Average, Money Management, Gold, Return, risk adjusted return, Martingale, Fixed Lot, Fixed Ratio, Expert Advisor, Automatic Trading

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APA

Candra, P. (2020). ANALISIS IMBAL HASIL DENGAN AUTOMATIC TRADING DALAM PERSPEKTIF MONEY MANAGEMENT : Studi Eksperimental dengan Expert Advisor pada Pasar Futures. Equator Journal of Management and Entrepreneurship (EJME), 8(4). https://doi.org/10.26418/ejme.v8i4.43637

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