متاح الآن! بحث تيليغرام 2025 — أهم رؤى العام 
Enrique Enguix MQL5
الذهاب إلى القناة على Telegram
Algorithmic Trading Systems Developer | Quantitative Researcher en Markets https://www.mql5.com/en/users/envex
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منشورات القناة
After giving it a lot of thought, I have decided to bring this chapter to a close.
Starting on the 18th of this month, I will stop selling all of my products and tools.
Over the years, I have invested a tremendous amount of time, energy, and passion into developing EAs, tools, and projects such as NeuroBot, SuperBot, Atomic79, Node Neural, Center EA, Nexus, AntiOverfit Pro, and many others. I have always tried to do things to the best of my ability and to provide something genuinely useful to those who placed their trust in my work.
Today, I feel that this chapter has reached its natural conclusion. Not because I have stopped believing in what I have built, but because, at this point in my life, my time and energy need to be focused elsewhere.
I would like to sincerely thank everyone who has been part of this journey over the years, whether as customers, users, collaborators, or simply by following and supporting the project.
For those who have already purchased any of my products, you will not lose access to them. Your purchases will remain linked to your account, and you will continue to be able to download them through MetaTrader 5 just as you always have.
Sales will remain available only until the 18th of this month. After that date, no new purchases will be possible.
Support for existing customers will continue until the end of the month in case anyone needs help with anything pending. After that date, I will no longer be providing active support.
For now, this chapter comes to an end.
Thank you for all the support, trust, and time you have shared with me throughout these years.
Wishing you all the very best.
| 2 | # Interpretation of the Chart
The chart appears to show the relationship between the AntiOverfit PRO score and the Forward Profit Factor obtained later on unseen or forward data.
Each blue dot represents a rule, strategy, or trading system tested.
- X-axis: AntiOverfit PRO score.
- Y-axis: Forward Profit Factor, visually clipped at 4.
- Dashed horizontal line: PF = 1, the basic threshold between losing and profitable systems.
- Shaded area: Selection zone, starting around score 60.
- Orange line: Progressive median of Forward PF.
- Blue line: Linear trend.
## Main Meaning
The main message is:
> As the AntiOverfit PRO score increases, the Forward Profit Factor also tends to increase.
This does not mean every high-score strategy will be profitable. It means the score appears to rank strategies probabilistically: higher scores are associated with better forward behavior on average.
[CONF: HIGH]
## Why the Orange Line Matters
The orange line is probably the most important element.
It shows that the median Forward PF rises progressively as the AntiOverfit PRO score increases. This suggests the effect is not caused only by a few extreme outliers. The central tendency itself improves as the score improves.
[CONF: HIGH]
Around score 60, the median Forward PF appears to approach or exceed PF = 1. Above that level, the chart marks a “selection zone,” implying that strategies in this region have a better probability of being forward-profitable.
[CONF: MEDIUM]
## What This Would Mean in Practice
If the experiment is clean, the chart suggests that AntiOverfit PRO is not merely describing past robustness. It may be acting as a forward-selection filter.
That would be important because, in systematic trading, the key problem is not producing attractive backtests. The key problem is selecting which systems are more likely to survive outside the optimization sample.
[CONF: HIGH] | 111 |
| 3 |  لا يوجد نص... | 104 |
| 4 | Using AI for trivial things is ridiculous; I encourage anyone to ask ChatGPT or Gemini or whoever else what this graph means. | 105 |
| 5 | 🔺Above this message is the reason why every trader should use AntiOverfit PRO.
There is currently no other trading tool anywhere that has such a high rate of predicting whether an Expert Advisor (EA) will perform well in the future. | 107 |
| 6 | https://www.mql5.com/en/blogs/post/771304 | 40 |
| 7 |  After analyzing more than 10,000 strategies across different symbols and random historical periods, we observed a clear tendency:
AntiOverfit PRO scores appear to reflect forward robustness reasonably well.
Strategies with low AOP scores were more frequently associated with weak forward results, often with a Profit Factor below 1.0. As the AOP score increased, forward performance tended to improve progressively in periods where the strategies had not been optimized.
This does not mean the score is perfect.
Some high-score strategies still failed in forward conditions. Likewise, some low-score strategies went on to perform well. Trading remains inherently uncertain, and no robustness metric can eliminate that uncertainty completely.
However, within this sample, those situations appeared to be the exception rather than the rule.
The overall pattern was straightforward:
- Low AOP score → higher probability of forward deterioration.
- High AOP score → higher probability of forward survival.
AntiOverfit PRO is not designed to predict the future. Its purpose is to evaluate how dependent a strategy may be on a single historical path.
This experiment suggests that robustness information can provide meaningful insight before exposing a strategy to unseen market conditions.
A backtest shows one path.
Robustness measures what may survive when the path changes.
🔗 Product:
https://www.mql5.com/en/market/product/168279 | 181 |
| 8 | After receiving many messages following the removal of Nexus EA Forex MT5 from the marketplace, I want to clarify a few important points.
First, Nexus was removed because the initial offer was limited to 200 buyers, exactly as announced from the beginning. Once that number was reached, the product was no longer available publicly on MQL5.
That said, some users who currently have Nexus rented have asked whether they can acquire a permanent license. For that reason, we are offering a special option only for users who already have an active rental license:
Nexus EA Forex MT5 — Lifetime License: $493
This purchase would not be made through MQL5. It would be handled externally through our website.
Additionally, some users have asked about the possibility of acquiring the source code. Until now, this was not something we offered publicly, except in very specific cases, but we have decided to make this option available under specific conditions.
Nexus EA Forex MT5 — Source Code: $5,000
Acquiring the source code does not automatically grant the right to resell, redistribute, or commercialize the product under its current name.
If anyone is interested in either of these options, feel free to contact me directly. | 195 |
| 9 |  From score to action.
A robustness score is only useful if it helps you make a better decision.
That’s why I added a simple practical guide for interpreting AntiOverfit PRO results:
Grade A — High Robustness
Grade B — Solid Robustness
Grade C — Limited Robustness
Grade D — Insufficient Robustness
The product still gives a 0–100 robustness score.
These grades are just a practical way to act on that score.
The goal is simple:
Don’t just admire a backtest.
Check if the EA can survive when the market path changes.
AntiOverfit PRO for MT5:
https://www.mql5.com/es/market/product/168279 | 170 |
| 10 |  Why AntiOverfit PRO uses 100 worlds and around 5–6 years of history
In AntiOverfit PRO, we do not believe that “more history is always better”.
That sounds intuitive, but in trading it is often wrong.
A market from 10, 12 or 15 years ago may contain information that is no longer useful today.
Different liquidity.
Different volatility structure.
Different execution conditions.
Different macro environment.
Different participants.
Different market microstructure.
So the question is not:
“How much history can I use?”
The real question is:
“How much relevant history should I use?”
For most robustness analysis, a 5–6 year window gives a better balance.
It is long enough to include different market regimes:
- trending phases
- ranging phases
- high-volatility periods
- low-volatility periods
- drawdown periods
- recovery periods
- structural changes inside the same market
But it is not so long that the test becomes contaminated by very old market behavior that may have little relationship with current conditions.
Using too little history has the opposite problem.
If you test only a short window, the EA may look robust simply because it was tested inside one favorable regime.
That is not robustness.
That is regime dependency.
This is why AntiOverfit PRO normally works best with:
100 synthetic worlds
around 5–6 years of historical data
The 100 worlds are not there to create “random noise”.
They are there to observe the distribution of outcomes when the same EA is exposed to many plausible alternative versions of the same market.
With too few worlds, the robustness score becomes unstable.
With too much historical data, the test may start measuring behavior from a market that no longer matters.
The goal is not to make the backtest longer.
The goal is to make the robustness test more meaningful.
AntiOverfit PRO does not ask:
“Did this EA win on one perfect historical path?”
It asks:
“Does this EA still make sense when the market path changes within a plausible range?”
That is the difference. | 220 |
| 11 | Until now, AntiOverfit PRO could make one very specific claim:
It could detect Expert Advisors that depended too heavily on one historical path.
In other words: EAs that could show a beautiful backtest, but became much weaker when the market no longer followed that exact same path.
That was already useful.
But it was not enough.
Over the last few weeks, we have opened a much broader research process.
We built a battery of 1,000 trading strategies and tested them across 14 different markets, using multiple time subwindows.
The goal was simple:
to check whether a high AntiOverfit PRO score was not only useful for identifying fragile systems, but also related to a higher survival rate outside the original backtest.
Until now, AntiOverfit was especially strong at detecting over-optimization.
But we did not want to claim that a high score was linked to higher future survival until we had stronger methodological evidence.
That was the missing piece.
This research also forced us to review the internal engine.
Our first approach — using Kolmogorov-Smirnov on returns and autocorrelation-based validation — was pointing in the right direction.
But it still left out some important dimensions of the problem.
In the next version, synthetic world generation will become stricter and better aligned with the real objective:
making a high score more clearly associated with stronger survival, while keeping low scores as a warning signal for structural fragility.
This does not mean predicting profits.
It does not mean guaranteeing results.
It does not mean that an EA with a good score will make money.
It means something more precise:
AntiOverfit PRO is evolving from a tool that detects historical fragility into a tool designed to measure robustness with higher practical value.
While we prepare this update, I want to say this clearly:
AntiOverfit PRO is still available for 111 USD.
If you work with EAs, optimizations, backtests, or MT5 trading systems, it can save you a lot of time, money, and false expectations.
The price will increase.
There are already professional users buying and using AntiOverfit PRO in contexts where the real value of the tool is much higher than the current price.
Right now, it is still an early opportunity.
The backtest is the pitch.
AntiOverfit is the check.
https://www.mql5.com/en/market/product/168279 | 69 |
| 12 |  I want to run a different kind of AntiOverfit test.
Most public EA analysis starts from what is popular, visible or heavily promoted.
This time I want to start from something more useful:
MT5 Expert Advisors that traders have actually used for at least one year.
Not perfect systems.
Not miracle robots.
Not screenshots.
Just EAs that survived real use long enough to deserve a serious robustness check.
If you know an EA that has been used for at least 12 months, send me:
1. EA name or MQL5 link
2. Symbol/timeframe used
3. How long it has been used
4. Whether it used fixed settings or frequent re-optimization
Please do not send cracked files, commercial files you do not own, or anything you are not allowed to share.
I will select a few candidates for AntiOverfit Public Lab testing.
The goal is simple:
compare “EAs people actually trust” against synthetic-market robustness evidence.
Maybe most will fail.
Maybe a few will surprise us.
That is exactly why this test is worth doing. | 295 |
| 13 | https://antioverfit.com/ | 285 |
| 14 | AntiOverfit PRO updated to v1.36:
This update improves the operational compatibility of synthetic worlds with Expert Advisors that perform strict market checks before opening trades.
In previous versions, synthetic worlds materialized as custom symbols with valid M1 history, but with some of the operational layer oversimplified. Specifically, bars could be written with a zero spread, a fixed minimum tick volume, and without fully replicating some practical properties of the original symbol, such as trading sessions, quote sessions, or margin rates.
While this approach was sufficient for many Expert Advisors, some systems perform internal validations before trading. These validations can include trading mode, market availability, active sessions, spread, Bid/Ask, minimum volume, margin calculation, tick value, tick size, or filling mode. In such cases, the EA could interpret the synthetic world as a non-fully operational symbol and omit entries, even if the synthetic history was valid.
Starting with this update, AntiOverfit PRO strengthens the materialization of custom symbols. Synthetic worlds better replicate the operational properties of the original symbol and retain practical information from the M1 historical data, including spread, tick volume, and real volume when available. Quote sessions, trading sessions, and margin rates are also cloned to improve compatibility with Expert Advisors (EAs) that validate the environment before sending orders.
The handling of tick history in custom symbols has also been corrected. AntiOverfit PRO no longer inserts a single synthetic tick, as this could result in artificially poor or insufficient performance for certain EAs in some Strategy Tester modes. By overwriting existing worlds, the tool can clean up old ticks to avoid remnants from previous versions.
The broker's original symbol is maintained as the baseline for comparison. AntiOverfit PRO does not create or replace the base symbol with a custom version. The analysis flow remains the same: original symbol versus synthetic worlds derived from the same market.
The following have not been modified:
- Statistical trajectory generation
- KS validation
- ACF/ACF² validation
- Robustness Score
- Scoring formulas
- XML import
- Interpretation of results
- Baseline structure versus synthetic worlds
In practice, this version does not change the statistical significance of AntiOverfit PRO nor relax the validation criteria. The improvement focuses on making synthetic worlds not only statistically plausible but also more operationally compatible within the MetaTrader 5 Strategy Tester, especially with Expert Advisors that apply strict filters before opening trades. | 317 |
| 15 |  We analyzed several of the top-rated Expert Advisors from the MQL5 Market.
The goal was simple:
not to check whether the backtest looked good,
but to see how robust each EA remained when tested against synthetic market worlds generated from the original symbol.
These synthetic worlds preserve key statistical properties of the original market, but slightly alter the historical path.
The result was surprising.
Some products that look very strong on the original backtest collapsed under small, plausible market-path variations.
Others produced weak or insufficient robustness scores.
And in one case, even a very high score came with a warning signal that makes the result suspicious.
After reviewing the audits, I would probably trust only one of the results.
You can see the full AntiOverfit Audit certificate list here:
https://www.antioverfit.com/certificates
External robustness audit. Not a promise of future results. | 340 |
| 16 |  We have started a new optimization round for Nexus EA.
This time, the process will not be based only on finding the best backtest.
The goal is different:
Find sets that can survive small changes in the market path.
For this round, I’m using AntiOverfit PRO together with a new internal tool I’ve built to automate the robustness-validation process.
The workflow is simple:
- Run a standard MT5 optimization.
- Select the best candidate sets.
- Test those sets across synthetic market worlds generated by AntiOverfit PRO.
- Penalize fragile configurations.
- Keep the sets that remain stable outside the original historical path.
This is not about forcing a beautiful equity curve.
It is about reducing fragility before a set is considered usable.
Hopefully, the results will be favorable.
But if they are not, that will also be useful information. | 273 |
| 17 |  A good backtest can fool you.
One clean equity curve ≠ robustness.
It’s just one path the market happened to take.
What happens if the path changes?
Because it will.
AntiOverfit PRO:
https://www.mql5.com/en/market/product/168279 | 227 |
| 18 | We have just published the official AntiOverfit Audit website
From now on, we will use this site to publish selected robustness analyses, verified audit certificates and technical notes about Expert Advisors tested with AntiOverfit PRO.
We are also opening the personalized EA robustness audit service for developers, vendors and traders who want an independent analysis before relying on a backtest, a product page or commercial capital.
A beautiful backtest is not enough.
Robustness must be tested beyond the exact historical path that produced it. | 263 |
| 19 | AntiOverfit Audit — Robustness Audits for MetaTrader 5 Expert Advisors
https://www.antioverfit.com/ | 256 |
| 20 |  Hardcoded-looking Expert Advisors are becoming a trend.
Beautiful historical curve.
Spectacular backtest.
Very high apparent quality.
Then you look deeper and find something strange:
the EA trades almost the same way across different synthetic worlds.
Maybe it is robust.
Maybe it is just extremely rigid.
Maybe the backtest was never telling the full story.
AntiOverfit PRO does not accuse.
It exposes patterns.
And sometimes, the pattern is more important than the score. | 312 |
