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Hi everyone,

we’ve been running a very large EA incubation setup since January 2024 — around 20 demo accounts, currently hosting 700+ active EAs, all of them 100% EA Studio–generated strategies (no manual coding, no third-party bots, no external licensed EAs).

Recently, we completed a stable workflow that generates a “Ready for Live” list each month based on FxBlue data and a proprietary scoring system. But we also wanted to answer a deeper question:

What happens to each EA Studio strategy when the historical window expands month after month?

To find out, we did something more.

✔️ We rebuilt the Ready-for-Live list backwards

from June → November (6 cumulative snapshots)

✔️ Then we flipped the perspective

Instead of looking at the list for each month…
we tracked each EA strategy across all months.

This allowed us to see:
    •    who stays consistently strong
    •    who collapses when more data is added
    •    who is a “meteorite” (looks good early → fails later)
    •    who is slowly becoming a strong EA
    •    who is just lucky in one snapshot

To measure this cleanly and repeatably, we created a new metric:

⸻

Maturity Score v2

A composite indicator based on:
    •    how many months an EA appears
    •    whether those months are consecutive
    •    how stable PF, Win%, Recovery and Score are
    •    how performance changes as we add more history
    •    total trade depth (a major signal)

This produced some very interesting results.

⸻

1. Only two EA Studio strategies are truly “elite”

(6 months stable, high trades, strong KPIs, no collapse)

① EA 250083819

The best EA in the entire incubator.
Always Ready, ~470 trades, extremely strong PF/Win/Recovery.
Total structural stability.

② EA 1506928733

Also present in all months, very reliable, very stable.
Clear long-term maturity.

⸻

2. Two EAs are strong but not (yet) elite

③ EA 1987477025

Very good metrics but more volatile.

④ EA 1074696949

Excellent KPIs but started appearing only recently.
Could become elite with more months of stability.

⸻

3. Three EAs are “mid-tier survivors”

Stable but not exceptional → good as satellites, not for core allocation.
    •    1264298459
    •    1326733007
    •    1958683245

⸻

4. Four EAs are “meteorites” — strong early, collapse later

These looked excellent in June–August but fell apart when more history was added:
    •    2120452330
    •    1784140930
    •    1699341130
    •    1740201819

This is a classic overfitting pattern.

⸻

5. Three EAs are late bloomers

Too little data to conclude:
    •    1223417011
    •    297120297
    •    1905225350

They need more months.

⸻

What this analysis shows

✔️ Persistence > peak PF

Many high-PF strategies disappear once we expand the window.

✔️ Second-year strength matters

Real robustness only shows up after multiple cumulative periods.

✔️ Trade depth is essential

Strategies with 200–400 trades behave differently from those with 50–70.

✔️ Our EA incubator filters aggressively

Out of 700+ EAs…
only 2 show elite long-term stability.
This is a sign of good filtering and realistic expectations.

⸻

Our new “Live Portfolio” will include

Core
    •    250083819
    •    1506928733
    •    1987477025

Watchlist
    •    1074696949

Satellite
    •    1264298459
    •    1326733007
    •    1958683245

Reject

4 strategies that collapse under expanded history

Observe

3 late bloomers

⸻

I strongly believe that in this forum there is a lot of knowledge and many smart people.
The outcome of the above analysis came up thanks to an intensive exchange with people met in the forum.

A big thank to Hez for the great contribution and inspiration.

This should really encourage everyone to share knowledge, challenges and pain points as well as great ideas.

I’ll be happy to tell your more about my Incubation Strategy...

Vincenzo

Hi,

I was reviewing EA Studio and I’m not sure whether this option already exists—probably not. There are some important features that, if added to the current version, would be very useful for customers.

In the Walk-Forward section, a commonly used metric called Walk-Forward Efficiency (WFE) should be included, as many similar programs provide it. Since the panel already displays all data for each segment, it should be easy to add WFE.

WFE = Sum(OOS net profit) / Sum(IS net profit)

Hi Popov, what is the difference between MQL Gen and EA studio?

Hey everyone,

I’m curious to see how different traders handle the demo incubation phase before going live.
The goal isn’t to decide what’s right or wrong — just to share, understand, and improve how each of us approaches this step.

If you’d like to take part, simply copy (or “quote”) the questions below and check (✅) the options that match your workflow.
Even short replies are useful to get a clearer view of what’s common (and what’s not) in our community.

⸻

1. Do you use a demo incubation phase in your workflow?
☐ Yes☐ No☐ Sometimes / depends on the strategy

1.1. If not, why?
(Free text answer)

2. Average duration of the demo incubation phase:
☐ <1 month☐ 1–3 months☐ 4–6 months☐ >6 months

3. Average number of strategies incubated at the same time:
☐ <20☐ 21–50☐ 51–100☐ >100

4. Broker or environment used for incubation:
☐ Same broker as live trading
☐ Different broker but similar conditions
☐ Any broker (just for technical testing)

5. Main criteria to promote a strategy to live:
☐ Profit factor
☐ Win rate
☐ Drawdown
☐ Consistency with backtest
☐ Other (please specify in comments)

6. Do you use incubation only to test logic, or also to check live robustness (spread, execution, slippage)?
☐ Only logic☐ Both☐ Depends on the EA type

7. Do you update strategies during incubation (e.g. rebalancing, optimization, filters)?
☐ Never☐ Occasionally☐ After each new data cycle

8. Do you have fixed thresholds to decide when to promote to live or discard?
☐ Yes, which one: ………………
☐ No
☐ Variable depending on the group

9. How do you monitor performance during incubation?
☐ Manually (Excel, charts, logs)
☐ Dashboard / automated tool
☐ Python (custom scripts)
☐ Artificial intelligence / automated analysis
☐ Just by general observation

10. In one sentence: what have you learned or improved thanks to demo incubation?
(Open answer)

⸻

Goal of this thread: gather experiences and ideas to improve how we test and qualify strategies before going live.
All input is welcome — even short answers help map different workflows in the community.

If at least 50 people participate, I’ll compile the results into a community summary post.

⸻

Great to hear, thank you and happy trading!

The problem has been solved after I follow your instruction.

Many thanks, Footon

Usually this error presents itself when Visual C++ 2010 Redistributable Package is not installed. Check if your vps has it and install it if it's not.

It presents.

If you check this folder -> \MQL4\Libraries, is the .dll file present or not?

I'm trying to run the MT4 Bridge on a VPS, but I keep getting the error message:
"Cannot load 'FSB Bridge.dll'"
However, when I run the same setup on my local PC, everything works fine without any issues.
Has anyone encountered this problem before? Is there a specific configuration or permission required on the VPS to make the DLL load properly?
Any help would be greatly appreciated!