Why I Lost Trust in Quantum Queen and Bogdan Ion Puscasu’s EA Products
A technical case study about Quantum Valkyrie, Quantum Queen, the July 1/2 XAUUSD event, 300 ms execution delay, and why beautiful MQL5 backtests can be dangerously misleading
I am writing this article because I learned something the hard way.
This is not only about one EA, one seller, or one bad trading day. This is about a much bigger problem in the MQL5 marketplace: traders trusting beautiful backtests, attractive live signals, and expensive products without understanding what can happen when real execution conditions become ugly.
The product in this case is Quantum Queen, developed by Bogdan Ion Puscasu.
After my experience with Quantum Valkyrie and Quantum Queen, I personally lost trust in these products. Not because trading has no risk. Trading has risk. Grid EAs are dangerous by nature. Anyone who uses a grid system should understand that.
My issue is different.
My issue is that the risk shown in a normal backtest was not the same risk that appeared under live conditions and execution-delay testing.
A beautiful backtest is not a safety certificate.
And the real cost of a bad EA is not the purchase price. It is the account balance behind it.
How I ended up using Quantum Queen
My first experience with Bogdan’s products was not Quantum Queen. It was Quantum Valkyrie.
I bought Quantum Valkyrie because it looked more controlled. It had TP/SL logic, and for me that was important. I did not choose it only because of price. I chose it because I wanted something that looked safer than a pure grid system with no normal stop-loss structure.
But my live experience with Quantum Valkyrie was disappointing compared with the expectations created by the backtests and presentation.
I discussed this with Bogdan. I explained that I could have bought Quantum Queen earlier when the price was closer, before it became more expensive. Instead of a refund, he later offered me a limited/account-locked version of Quantum Queen as goodwill.
That is how I ended up using Quantum Queen.
At the beginning, I was still careful. Quantum Queen looked powerful, but I did not fully like the idea that it could run without a normal individual stop-loss structure. It is a grid EA. And grid EAs can look amazing for a long time, until one bad event exposes the real risk.
Because of that, I used my own external protection utility, Atropos Manager, to protect the account with external drawdown control.
That decision became very important later.
The July 1/2 XAUUSD event
There was a major XAUUSD event around July 1/2.
I am saying July 1/2 because the exact calendar label can differ depending on broker server time, signal display, and timezone. The same market event can appear as July 1 on one account and July 2 on another. The date label is not the important point.
The important point is the XAUUSD event where Quantum Queen opened a dangerous grid.
On my live IC Markets RAW account, using the recommended settings, Quantum Queen opened a deep buy grid. My external utility, Atropos Manager, closed everything at 30% drawdown.
Without that external protection, the result could have been much worse.
At first, I was thankful that my account was protected. I even supported Bogdan after the event because I saw many emotional and insulting comments against him. I believed that traders must understand risk. I still believe that.
But later, when I tested the event more carefully, my view changed.
The normal backtest looked much safer
After the event, I tested the same period in Strategy Tester using the same EX5 file, the same broker environment, and the same settings as closely as possible.
The normal backtest did not reproduce the same danger.
The grid was much smaller. The floating drawdown was much lower. The event looked almost harmless compared with what happened live.
That is when my concern started.
As a trader, coder, programmer, and MQL5 seller myself, I know that backtests can be misleading. I also know it is technically possible for EAs to behave differently depending on tester conditions, live execution, account mode, spread, slippage, delay, or other internal conditions.
So I contacted Bogdan and asked for a technical explanation.
The first explanation: spread, slippage, liquidity, execution
Bogdan first explained the issue as spread, slippage, execution delay, low liquidity, and broker execution differences.
That answer did not fully satisfy me at first.
Spread and slippage can explain worse fills. They can explain worse closing prices. They can explain some difference between live and backtest.
But they do not automatically explain why a live account opens a much deeper grid while a normal backtest shows a much smaller and safer result.
Then Bogdan gave one specific instruction:
Backtest the event with 300 ms delay.
That was the turning point.
The 300 ms delay test changed everything
I tested the event again with 300 ms execution delay.
This time, the backtest changed.
More grid exposure appeared. The risk profile changed. Drawdown protection became relevant.
This was the real discovery.
It showed that the clean backtest was not showing the full risk of the EA.
Then I tested a longer period — around two years — using 300 ms delay. I did not even go further back yet.
The result was disturbing.
The 30% drawdown level was hit many times. In some cases, the drawdown appeared to go even higher than 30%.
This was not a small difference. This was not just one unlucky tick. This changed the whole picture.
A normal backtest made the EA look attractive.
A 300 ms delay test exposed repeated dangerous drawdown events.
That means the real question is not:
“Can this EA make money?”
The real question is:
How much capital is required to survive its worst grid events under realistic execution stress?
“Every tick based on real ticks” is not enough
Many traders believe that if they test with “Every tick based on real ticks,” the backtest is realistic.
This case taught me that this is not enough, especially for a grid EA.
A grid EA can look excellent under clean execution. But under execution delay, spread pressure, slippage, liquidity stress, and fast movement, the same EA can behave very differently.
If 300 ms delay can materially change the result, then the normal backtest is only a best-case scenario.
It is not a real safety test.
Every serious EA buyer should test:
- 0 ms delay
- 100 ms delay
- 300 ms delay
- 500 ms delay
- Random delay
- Different spread limits
- Different leverage
- Lower balance
- Different brokers
- Worst historical events
- Max floating drawdown
- Max grid count
- Max total lots
- Deposit load and margin usage
If an EA fails ugly testing, it does not matter how beautiful the clean backtest looks.
The spread and slippage settings question
Quantum Queen has inputs for maximum spread and maximum slippage.
In my case, the values were set around 100/100.
After this event, I started asking a serious question:
What would have happened if the maximum spread was much lower, for example 15 or 20 points?
Could many dangerous grid entries have been avoided?
Maybe yes. Maybe no. It depends on the actual spread at the time of each execution. But this is exactly the point: buyers should know how sensitive the EA is to spread and execution conditions before trusting it with real money.
If a stricter spread filter reduces the danger but destroys the profit curve, then the original beautiful results were partly dependent on accepting dangerous execution conditions.
That is not something normal buyers understand when they look at a clean report.
The default risk question
One of the most serious questions is risk sizing.
I tested with a more conservative setup, such as 0.01 lot for around $2,000 balance. Even then, under 300 ms delay testing, dangerous drawdown events appeared repeatedly.
So what happens if users run more aggressive default or recommended settings?
What drawdown is supposed to be acceptable?
30%?
50%?
70%?
At what point does “risk management” become only a slogan?
An EA can make money for weeks or months, but if one execution-stress event can wipe out the entire gain, then the profit curve was never telling the full truth.
The live signal problem
Bogdan pointed to his live signal as proof.
After this experience, I do not trust live signals blindly anymore.
A live signal can look good for many reasons:
- larger balance
- different leverage
- different broker server
- different execution quality
- different risk settings
- manual intervention
- deposit and withdrawal activity
- emergency capital added during pressure
In this case, the public signal showed large deposit and withdrawal activity. I personally observed the signal under heavy floating pressure during the event. I saved screenshots of the signal statistics and the conversation in case verification is needed.
For me, a signal account with active balance management does not prove that a normal buyer using a fixed balance would survive the same event.
A signal can show survival.
But survival does not always mean the EA was safe.
Sometimes survival only means there was enough extra capital to survive the basket.
If the signal later becomes hidden or changed, I have screenshots saved.
The business model problem
This experience made me question the whole business model around expensive EAs.
If an EA is truly that powerful and safe, every buyer should ask a simple question:
Why sell it publicly?
Why not keep it private and compound serious capital quietly?
The uncomfortable answer is that, for many sellers, the real business is not trading. The real business is selling licenses.
That does not mean every seller is dishonest. But it does mean buyers must stop being naive.
When a seller earns from licenses and the trader carries the live account risk, the incentives are not the same.
After this experience, it looked to me like the seller’s income from licenses was protected better than the buyer’s trading capital.
The EA price is not the real danger.
The real danger is the account behind it.
A trader can pay $1,000 or $2,000 for an EA and think that is the risk. It is not. The real risk is the $5,000, $10,000, $20,000, or $50,000 account that the EA can damage when one ugly event appears.
Why I lost trust
After my experience with Quantum Valkyrie and Quantum Queen, I personally lost trust in Bogdan Ion Puscasu’s EA products.
Not because one trade lost.
Not because trading has no risk.
Not because grid systems are supposed to be magic.
Not because any EA must win forever.
I lost trust because:
- Quantum Valkyrie already disappointed me compared with expectations.
- Quantum Queen looked much safer in clean backtests than under execution-delay testing.
- The 300 ms delay test exposed a completely different risk profile.
- A two-year delay test showed repeated 30% drawdown hits.
- The live signal does not prove safety for normal buyers.
- The key execution-delay issue was not transparent from the beginning.
- Buyers may not know they must test delay before trusting the EA.
- The product became hidden after the disaster, while many users were left trying to understand what happened.
For me, that is not enough transparency.
This is not only about Quantum Queen
This article is not only about Quantum Queen.
Quantum Queen is the case study.
The real lesson is bigger:
Do not trust clean EA backtests.
Do not trust live signals blindly.
Do not trust expensive products only because they look professional.
Do not trust seller confidence.
Do not trust a beautiful equity curve without ugly-condition testing.
Before buying or running any EA, especially a grid EA, test it under bad conditions.
Test execution delay.
Test random delay.
Test strict spread limits.
Test several years.
Test lower balance.
Test realistic leverage.
Test the worst events.
Check the worst floating drawdown.
Check the max grid count.
Check the max total lots.
Check whether drawdown protection is enabled by default.
Use external protection.
If the EA cannot survive ugly testing, then the clean backtest means very little.
About AI writing
One more point.
Bogdan mentioned that my replies looked like they were written with AI.
Yes, I use AI to help me write clearly.
I am not ashamed of that.
AI did not trade my account.
AI did not create the live history.
AI did not create the backtest result.
AI did not invent the 300 ms delay test.
AI did not change the facts.
AI only helped me organize my thoughts and explain them better.
The experience, the testing, the screenshots, the account history, and the conclusions are mine.
Final warning to traders
Do not be lured by beautiful backtests.
Do not be lured by live signals.
Do not assume an expensive EA is safe.
Do not assume a seller’s recommended settings show the real worst-case risk.
Do not assume “Every tick based on real ticks” is enough.
Quantum Queen taught me one painful lesson:
The danger is not always visible in the beautiful report. Sometimes the real risk only appears when you test the ugly conditions.
One bad event can expose what months of profit were hiding.
If 300 ms execution delay can change the entire picture, then every buyer should ask:
What exactly am I trusting — the real system, or the clean version shown in backtests?
That is why I lost trust in Quantum Queen and Bogdan Ion Puscasu’s EA products.
