MT5 OptiBooster
- 유틸리티
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Andrey Dik
I WILL CONSIDER PROPOSALS FOR THE PUBLICATION OF A BOOK (TEXTBOOK) ON OPTIMIZATION ALGORITHMS.
A group for communication on optimization and free product testing://t.me/+vazsAAcney4zYmZi
Attention! My Telegram doppelgangers have appeared, my real nickname is @JQS_aka_Joo - 버전: 5.0
- 활성화: 20
Dear traders and investors! We present to you the MT5 Optimization Booster – an innovative product that will revolutionize your optimization experience on MetaTrader 5!
The MT5 Optimization Booster is based on the innovative Quantum Swap Protocol (QSP) algorithm – a unique proprietary optimization strategy that forms the core of the product and elevates the process of finding optimal solutions to a new level.
After the purchase, be sure to contact me.
The product is designed to enhance the capabilities of the standard optimizer in all directions:
1. Unlimited number of parameters for optimization:
- Don't limit yourself! Now you can optimize any number of parameters of your EA without restrictions.
- Configure parameters with maximum flexibility! Set the optimization step as you see fit, starting from zero.
- Perform as many historical runs as you need. No restrictions – only results!
- The algorithm ensures fast and accurate convergence to the best solution. Your strategies will work more efficiently, saving you time.
- A simple interface, intuitive for all experience levels. No complex settings (no settings at all) – start optimizing right away!
- QSP does not depend on previous solutions. This means that testing agents no longer idle while waiting for new tasks in a new population. No populations – no idle agents, optimization now occurs as smoothly and continuously as possible.
Make sure to read the User Manual for the product.
Don't miss the chance to improve your trading strategies with the MT5 Optimization Booster!
Achieve maximum efficiency with your EA!
Try the MT5 Optimization Booster now and see its power for yourself!
⚠️ FAQ
"Why do I get a overfitted model?"
— In the context of using Booster, it is important to understand the fundamental error in the concept of "overfitting."
Let's consider some specific real-life examples:
Example with the guy:
A guy has a model of the ideal wife and is looking for a life partner. If he finds a girl who perfectly meets his criteria and their marriage is successful, no one would say that his model was "overfitted." The success confirms that the evaluation criteria (fitness function) adequately defined the girl's suitability for this model.
Example with the girl:
A girl has a model of "the prince on a white horse." If she finds someone who is not quite a "prince" and not quite "on a horse," the problem is not that the model of the perfect partner is too idealized ("overfitted"), but rather that her fitness function for evaluating candidates was not strict enough—it allowed too much deviation from the desired model.
Application to Booster:
1. When an EA shows poor results on new data, it does not mean that the model is "overfitted." It means that the selected fitness function inadequately assesses the EA's alignment with the actual market process.
2.The task is not to fight against an imaginary "overfitting," but to find a fitness function that truly accurately evaluates the quality of the EA's performance.
The concept of "overfitting" is unscientific because:
3. It is impossible to quantitatively measure the degree of "overfitting."
- It is impossible to quantify the degree of "retraining"
- There is no reliable way to determine its existence.
- The assessment is completely subjective.
- Clearly defining what we want from the EA (model)
- Developing adequate criteria for evaluating the EA's performance (fitness function)
- Strictly aligning the evaluation criteria with the real demands of trading.
Thus, the success of using Booster depends not on combating "overfitting," but on the correct choice of evaluation criteria for the EA that truly reflect the requirements for its performance in real conditions.
