T&F high road

High volatilityThis is a long-term EA created based on currency pairs.

The time frame used is4-hourwith a large setting for a single strike.

The currency pair used isUSD/JPY.

Regarding the parameters, you can use themas default values. (Since it is set to allow changes, you can also trade according to your style. Only for the 4-hour time frame)

Compound interest operationis recommended for long-term use, as you will be able to feel the effects of this EA.

A small riskis strongly recommended. (This is because the best results come from long-term use.)

When purchasing, pleasecarefully check the backtest databefore proceeding.

As of December 20, 2024, the results of backtesting conducted on MetaTrader5

This time, optimization was performed on six parameters: the main logic "mult_total," "mult1," "per1," "per2," and the filters "ATRperiod," "ATRprice."

The values used for optimization include multiple items such as profit and loss, number of trades, win rate, PF, DD%, etc. It is recommended to conduct your own backtesting before actual operation.

Figure 1: Optimization results of mult_total

Figure 2: Optimization results of mult1

Figure 3: Optimization results of per1

Figure 4: Optimization results of per2

Figure 5: Optimization results of ATRperiod

Figure 6: Optimization results of ATRprice

Figure 7: An example of backtest results

Figure 8: Backtest results

Discussion of optimization results

The results of each variable in the EA optimization will be discussed using Figures 1 to 6. The main purpose is to evaluate the strength of the logic and focus on optimizing the main logic rather than the filters.

Figure 1: Results related to the weighting of per1 and per2

In Figure 1, it was confirmed that larger values tend to yield better results. This variable relates to the weighting ofper1andper2, and as the value increases, more diverse combinations become possible. It is believed that securing a certain number of patterns allows the EA's characteristics and strengths to be demonstrated.

Figure 2: Results of variables related to Figure 1

The variables used in Figure 2 have a direct relationship with the variables in Figure 1, but it cannot be said that there is a superiority for specific values. No significant differences were observed within the scope of this verification.

From this,it is inferred that this variable has a small impact on the overall performance of the EA.

Figure 3: Results of the extreme values of the variables

In Figure 3, it was confirmed that the values of the variables tend to be small at both extremes. From this result, it can be determined that values near the center are optimal.

Figure 4: Tendency for improvement as values increase

In Figure 4, it was confirmed that the larger the values, the better the results.

Figures 5 and 6: Optimization results of ATR

Figures 5 and 6 show the optimization results of variables related to ATR. As the ATRperiodincreases, the values tend to become smoother and converge to specific values. From the figures, good results are obtained for both short and long periods.

However, when the ATR period is small, it may have high responsiveness but also a lot of noise.

Additionally, while long periods yield smooth and stable results, responsiveness may decrease.Therefore,the setting of ATRperiod needs to be optimized based on the cyclicality of USD/JPY.

Comprehensive considerations

In this optimization, emphasis was placed on parts directly related to the main logic rather than filter conditions. As a result, it was found that the EA's logic is highly flexible to market fluctuations and possesses a certain strength. The following points are particularly important:

1. Stability of the logic: Consistently good results were obtained in a specific value range across multiple variables.

2. Flexibility of parameters: Particularly, the variables related to the weighting of per1 and per2 can accommodate diverse patterns and are elements that draw out the strengths of the EA.

This optimization aims to optimize parts directly related to the main logic rather than filters, indicating that this EA is logically strong.

As of January 15, 2025, version 1.4

Due to unexpected trading times, corrections were made in the version update. Additionally, changes in trading were confirmed, leading to new optimizations on MetaTrader. The results will be shown below.

In this optimization, a compound interest mode is used. As can be seen from the graph of the transition of effective margin below, the win rate was high. When using compound interest mode, the increase in assets becomes larger with each successive trade. Consequently, the trading volume also increases, leading to significant fluctuations from a single loss. Therefore, the DD tends to be high. As a result, compared to previous optimizations, the maximum value of complex criteria decreases. Additionally, the number of trades has also decreased. If you want to suppress DD a bit more, please consider using simple interest operation or setting lower trading volumes. If you have any questions or other requests, please contact us directly.