Discussing the article: "Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy"
I can't seem to replicate the back tested results on AUDUSD over the 2024 period. The results I'm getting is much worse. I checked and my input parameters seems to be identical to what was used in the tutorial video. Any ideas why my results doesn't tie up to what you have in the article?
1149190 #:
I can't seem to replicate the back tested results on AUDUSD over the 2024 period. The results I'm getting is much worse. I checked and my input parameters seems to be identical to what was used in the tutorial video. Any ideas why my results doesn't tie up to what you have in the article?
I can't seem to replicate the back tested results on AUDUSD over the 2024 period. The results I'm getting is much worse. I checked and my input parameters seems to be identical to what was used in the tutorial video. Any ideas why my results doesn't tie up to what you have in the article?
Hello. The video shows everything, from compilation, test period, and input parameters used.
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Check out the new article: Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy.
In this article, we develop the Adaptive Crossover RSI Trading Suite System, which uses 14- and 50-period moving average crossovers for signals, confirmed by a 14-period RSI filter. The system includes a trading day filter, signal arrows with annotations, and a real-time dashboard for monitoring. This approach ensures precision and adaptability in automated trading.
The Adaptive Crossover RSI Trading Suite Strategy is built on a foundation of moving average crossovers and momentum confirmation, creating a balanced approach to trading. The core signals will be derived from the interaction between a 14-period fast-moving average and a 50-period slow-moving average. A buy signal will occur when the fast-moving average crosses above the slow-moving average, suggesting a bullish trend, while a sell signal will be generated when the fast-moving average crosses below the slow-moving average, indicating a bearish trend.
To enhance the accuracy of these signals, a 14-period Relative Strength Index (RSI) will be employed as a confirmation filter. The RSI will ensure that trades align with prevailing market momentum, reducing the likelihood of entering trades in overbought or oversold conditions. For instance, a buy signal will only be validated if the RSI is above a threshold of 50, while a sell signal will require the RSI to be below its corresponding threshold. The strategy will also incorporate a trading day filter to optimize performance by avoiding trades on days with historically low volatility or poor performance. This filter will ensure that the system focuses only on high-probability trading opportunities. In a nutshell, the strategy blueprint is as follows.
Sell Trade Confirmation Blueprint:
Author: Allan Munene Mutiiria