Ginga 9AI Ensemble

5
Ginga 9AI Ensemble - Next-Generation Ensemble EA

Overview

A next-generation ensemble EA that makes trading decisions through majority voting by 9 independent AI models.

  • Training Period: 2003-2024 (22 years)
  • Strict Selection: 9 elite models selected from over 100 candidates through 10 years of Walk-Forward Testing (WFT)
  • Prop Firm Ready: Equipped with a daily stop loss feature

Main Features

1. Ensemble AI Strategy

Many AI EAs rely on a single model, making them vulnerable to overfitting and changing market conditions. Ginga combines 9 AI models trained with different approaches, allowing the weaknesses of one model to be compensated by the others.

  • If one model underperforms in a specific market condition, the others can compensate
  • Trade entries require agreement from multiple models (EntryScore can be adjusted)
  • Greatly reduces false signals for more stable trading
  • Each of the 9 models can be turned ON/OFF individually (single-model operation is also possible)

2. Prop Firm-Friendly Daily Risk Control

Most prop firms enforce daily loss limits. Ginga includes built-in control features designed for these requirements.

Daily Stop Loss

  • When the daily loss reaches a set percentage of account balance (default 5%, including floating loss), positions are automatically closed
  • New entries are stopped for the rest of the day
  • Trading automatically resumes on the next trading day

Daily Take Profit (Optional)

  • When the daily profit target is reached, positions are automatically closed
  • New entries are stopped for the rest of the day
  • Helps prevent giving back profits through overtrading

The daily thresholds can be adjusted to match the rules of each prop firm.

3. Advanced AI Architecture

  • CatBoost Machine Learning: A gradient boosting algorithm well-suited for financial time series forecasting
  • 3-Class Classification: Predicts Buy / Sell / Hold to avoid low-probability trades
  • 102-Dimensional Feature Space: Analyzes price action, volatility, technical indicators, time patterns, and market microstructure
  • Strict Model Selection: Hundreds of models were tested through 10 years of WFT, and only the most stable ones were adopted

Technical Specifications

Item Specification
Symbol XAUUSD (Gold) only
Timeframe H1 (1-hour chart) only
AI Engine CatBoost 3-class classification
Number of Models 9 elite models (ensemble)
Training Period 2003-2024 (22 years)
Feature Dimensions 102 dimensions
Default Daily Stop Loss 5% of account balance
Minimum Recommended Deposit 1,000 USD
Recommended Deposit 3,000 USD or more
Prop Firm Compatible Yes
VPS Recommended (not required)

Entry Logic (Default Settings)

  1. Prediction Timing: AI models generate predictions once every hour
  2. Score Calculation:
    • The prediction results of all AI models are aggregated
    • Buy prediction = +1, Sell prediction = -1, Hold = 0
    • The total score of 9 models is summed (range: -9 to +9)
  3. Entry Conditions:
    • Score +5 or higher → Buy entry
    • Score -5 or lower → Sell entry
    • The threshold can be adjusted with the EntryScore parameter
  4. Exit Conditions:
    • When the score becomes 0
    • When an opposite signal appears
    • Exit behavior can be selected by parameter (force close / close profit only / trailing / do nothing)
  5. Daily Function:
    • If the daily loss reaches 5% of account balance (default, including floating loss), positions are closed and new entries are stopped until the next day
  6. Grid Trading (Optional):
    • By default, the EA operates with a single position
    • Can be switched to multiple-position operation using NanpinCount
    • Hedging is not used

Parameter Description

Category Parameter Description Default
Main Comment Order comment Ginga
Main Magic Magic number (set it so it does not conflict with other EAs) 900
Main EntryLots Position size for new entries 0.01
Main DailyTakeProfit Daily profit target as a % of account balance (0 = disabled) 0
Main DailyStopLoss Daily loss limit as a % of account balance (0 = disabled) 5
Main LimitClose Whether daily-limit closing is performed using pending close levels true
Filter Slippage(point) Allowed slippage (in points) 10
Filter MaxSpread(point) Maximum allowed spread (in points) 100
Filter EntryBuy Allow buy entries true
Filter EntrySell Allow sell entries true
Model EvenClose Action when AI prediction score becomes 0 (NOUSE / TRAIL / PLUS / MINUS) MINUS
Model ForceClose Action when the AI prediction score turns into an opposite signal (NOUSE / TRAIL / PLUS / MINUS) MINUS
Model Threshold[Buy] Probability threshold for buy predictions (0.3-0.6, higher = more selective) 0.3
Model Threshold[Sell] Probability threshold for sell predictions (0.3-0.6, higher = more selective) 0.3
Model EntryScore Minimum score required for entry 5
Model UseModel0 ~ UseModel8 Enable / disable each AI model individually true
Nanpin NanpinCount Maximum number of positions (1 = no grid) 1
Nanpin NanpinWidth Price distance between positions (as % of current price) 0.3
Nanpin NanpinLots Lot multiplier for each additional position 1.5
Nanpin NanpinInterval Minimum time interval between additional entries 3 hours
TimeSetting TimeZone Broker GMT time zone offset 2
TimeSetting SummerTime Daylight saving adjustment (None / US / UK) -
Other ShowIndicator Whether to display information on the chart (total profit/loss, AI score, daily profit/loss, etc.) false
Other StopAtLimitOrder Stop EA operation if pending orders exist in the same account false
Note: EvenClose / ForceClose behavior
  • NOUSE: Do nothing
  • TRAIL: Execute trailing stop
  • PLUS: Close only if in profit
  • MINUS: Force close

Important Warnings and Disclaimer

⚠️ Past performance does not guarantee future results

No matter how strong backtest or walk-forward results may be, future profitability is never guaranteed. Market conditions are always changing.

⚠️ For XAUUSD H1 only

This EA is specifically optimized for Gold on the 1-hour timeframe. Do not use it on other symbols or timeframes.

⚠️ Test on demo first

Please test on a demo account for at least 2 weeks before going live. Make sure you understand how the EA behaves and adjust parameters according to your risk tolerance and prop firm rules.

⚠️ How the daily functions work

The EA checks the daily limits on every tick. Once a limit is reached, no new positions will be opened until the next trading day (server time).

⚠️ This is not a holy grail

No EA can win 100% of the time. Ginga is an advanced tool, but proper money management and realistic expectations are essential.

Frequently Asked Questions (FAQ)

Q. Can I run it together with other EAs?

A. The daily take profit / daily stop loss functions calculate the total profit and loss of the entire account without considering magic numbers. Therefore, the performance of other EAs may affect how Ginga behaves. If possible, avoid running it together with other EAs on the same account.

Q. Should I add +1 to TimeZone during daylight saving time?

A. No. During daylight saving time, the EA automatically calculates TimeZone+1 internally. Just enter the GMT value for non-daylight-saving periods.

Q. Can I run it with the default settings?

A. In general, yes. However, please check the following:

  • If multiple EAs are running on the same account, consider disabling the daily functions or stopping the other EAs
  • Make sure the TimeZone setting matches your broker

Q. "TradeLimit" is displayed on the chart

A. This means the daily function has been triggered and new entries are temporarily stopped. Trading will automatically resume on the next day based on server time.

Q. It does not trade

A. Please check the following:

  • Whether the daily function is active and trading has been stopped by the profit/loss of other EAs
  • If using StopAtLimitOrder, make sure there are no pending orders in the same account
  • Whether MaxSpread is set too tight
  • Whether both EntryBuy and EntrySell are set to true

Support

After purchase, support is available via MQL5 messages or the product comments section. Feel free to contact us.

Legal Disclaimer

  • This product is not investment advice
  • Forex and CFD trading involve substantial risk of loss
  • Past performance does not guarantee future results
  • The developer assumes no responsibility for user losses
  • Users are responsible for complying with the rules and regulations of their prop firm
  • Use only funds you can afford to lose, at your own risk
  • Always test thoroughly on demo before live trading
  • Please confirm EA compatibility with your prop firm before use
Comentários 5
zeke21t2
648
zeke21t2 2026.07.05 05:07 
 

Ginga is not just another gold EA — it is a genuinely well-engineered nine-model committee that trades with the discipline of a general council rather than the impulsiveness of a single indicator. Based on the ETRT backtest results (2026.01 ~ 2026.06) with the broker I use (Axi Premium), I am using Ginga with a buy-only, 9-model true setting. Auto-lot is not yet implemented, so I hope it will be added in the future. So the test starts with $2,000 and uses a fixed lot size of 0.02. The statistical elements speak for themselves. A. Headline results: ・Net profit +114.9% on $2,000 starting capital ・Profit Factor 2.13 · Sharpe 8.69 · Recovery Factor 6.14 ・Balance drawdown only 9.87%, equity drawdown 10.75% ・LR Correlation 0.98 — an almost perfectly linear equity curve ・Z-Score 2.74 (99.39% confidence) — the results are statistically significant, not noise. B. What the correlation triad reveals about the underlying strategy: The three trade-quality correlations tell a story most sellers never expose: ・Corr(Profits, MFE) = 0.82 — winners are highly proportional to their maximum favorable excursion. The EA rides its winners rather than clipping them prematurely. ・Corr(Profits, MAE) = 0.57 — winning trades often endure meaningful adverse excursion first. This is a patient, mean-reversion posture, not a fragile momentum chaser. ・Corr(MFE, MAE) = 0.19 — the near-zero coupling between upside and downside excursion is the mathematical signature of genuine directional edge. If the EA were merely harvesting volatility, this number would be high. It is not. Together, these three coefficients prove Ginga has real predictive skill — not just favorable variance. C. Strategy structure I observed: ・Buy-only setting, and it still delivered every month in a broadly declining H1 2026 gold market. That is remarkable — most long-only EAs got crushed in the same window. ・Nine-model committee with EntryScore=5 majority vote — no single sub-model can force an entry. Overfitting risk is diluted by consensus. ・Sniper cadence, not scalper spam — 84 trades in six months, avg hold ~6h10m. Ginga waits. ・Adaptive silence — trade count halved from ~20/month (Jan–Feb) to ~8/month (Apr, Jun) as the trend deepened. The committee correctly stood down when conditions weren't there, instead of forcing trades. This is exactly the behavior you want in live trading. ・Non-symmetric risk control — DailyStopLoss + LimitClose cap the downside hard, while DailyTakeProfit is deliberately disabled to let winners run. ・Nanpin (averaging) parameters exist but I have it turned off — held in reserve as a sealed contingency, not abused as a core mechanic. I have deep respect for developers who resist the temptation to Martingale their equity curve. ・Only 6 of 84 exits were stop-loss hits (7%). The vast majority were clean, decision-based exits from the ensemble flipping its verdict. D. Why this matters: Most gold EAs that show +100% returns in half a year do so with Martingale, no stop loss, or a curve-fit window. Ginga does it with a sealed nanpin, hard daily loss caps, buy-only exposure through a bear leg, and a 0.98 LR correlation. That combination is genuinely rare. E. Minor notes (not deductions): Sell-side is intentionally disabled. A future symmetric build could open a second revenue stream, but in the current version, the performance of short trades is somewhat inferior. Backtest window (H1 2026) is one regime. Long-term forward validation across regimes will be the real test — but every published statistic here is already consistent with an edge that should survive. F. Verdict: Ginga behaves like a council of thoughtful analysts rather than a trigger-happy robot. Statistically rigorous, structurally disciplined, and — most importantly — honest about how it makes money. Highly recommended for traders who value robustness and evidence over marketing screenshots. I love these 9 dogs :D

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Farzad Saadatinia
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zeke21t2
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zeke21t2 2026.07.05 05:07 
 

Ginga is not just another gold EA — it is a genuinely well-engineered nine-model committee that trades with the discipline of a general council rather than the impulsiveness of a single indicator. Based on the ETRT backtest results (2026.01 ~ 2026.06) with the broker I use (Axi Premium), I am using Ginga with a buy-only, 9-model true setting. Auto-lot is not yet implemented, so I hope it will be added in the future. So the test starts with $2,000 and uses a fixed lot size of 0.02. The statistical elements speak for themselves. A. Headline results: ・Net profit +114.9% on $2,000 starting capital ・Profit Factor 2.13 · Sharpe 8.69 · Recovery Factor 6.14 ・Balance drawdown only 9.87%, equity drawdown 10.75% ・LR Correlation 0.98 — an almost perfectly linear equity curve ・Z-Score 2.74 (99.39% confidence) — the results are statistically significant, not noise. B. What the correlation triad reveals about the underlying strategy: The three trade-quality correlations tell a story most sellers never expose: ・Corr(Profits, MFE) = 0.82 — winners are highly proportional to their maximum favorable excursion. The EA rides its winners rather than clipping them prematurely. ・Corr(Profits, MAE) = 0.57 — winning trades often endure meaningful adverse excursion first. This is a patient, mean-reversion posture, not a fragile momentum chaser. ・Corr(MFE, MAE) = 0.19 — the near-zero coupling between upside and downside excursion is the mathematical signature of genuine directional edge. If the EA were merely harvesting volatility, this number would be high. It is not. Together, these three coefficients prove Ginga has real predictive skill — not just favorable variance. C. Strategy structure I observed: ・Buy-only setting, and it still delivered every month in a broadly declining H1 2026 gold market. That is remarkable — most long-only EAs got crushed in the same window. ・Nine-model committee with EntryScore=5 majority vote — no single sub-model can force an entry. Overfitting risk is diluted by consensus. ・Sniper cadence, not scalper spam — 84 trades in six months, avg hold ~6h10m. Ginga waits. ・Adaptive silence — trade count halved from ~20/month (Jan–Feb) to ~8/month (Apr, Jun) as the trend deepened. The committee correctly stood down when conditions weren't there, instead of forcing trades. This is exactly the behavior you want in live trading. ・Non-symmetric risk control — DailyStopLoss + LimitClose cap the downside hard, while DailyTakeProfit is deliberately disabled to let winners run. ・Nanpin (averaging) parameters exist but I have it turned off — held in reserve as a sealed contingency, not abused as a core mechanic. I have deep respect for developers who resist the temptation to Martingale their equity curve. ・Only 6 of 84 exits were stop-loss hits (7%). The vast majority were clean, decision-based exits from the ensemble flipping its verdict. D. Why this matters: Most gold EAs that show +100% returns in half a year do so with Martingale, no stop loss, or a curve-fit window. Ginga does it with a sealed nanpin, hard daily loss caps, buy-only exposure through a bear leg, and a 0.98 LR correlation. That combination is genuinely rare. E. Minor notes (not deductions): Sell-side is intentionally disabled. A future symmetric build could open a second revenue stream, but in the current version, the performance of short trades is somewhat inferior. Backtest window (H1 2026) is one regime. Long-term forward validation across regimes will be the real test — but every published statistic here is already consistent with an edge that should survive. F. Verdict: Ginga behaves like a council of thoughtful analysts rather than a trigger-happy robot. Statistically rigorous, structurally disciplined, and — most importantly — honest about how it makes money. Highly recommended for traders who value robustness and evidence over marketing screenshots. I love these 9 dogs :D

Shota Watanabe
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Resposta do desenvolvedor Shota Watanabe 2026.07.05 08:57
Thank you so much for taking the time to write such a thorough and objective review. What made me happiest wasn't simply that you praised Ginga's performance—it was that you understood the philosophy and intentions behind its design. As the developer, I can always explain what I intended to build and why I made certain design choices. But no matter how honestly I say it, those words will inevitably carry some bias. That's why having a third party analyze the EA so deeply and independently arrive at the same conclusions means so much to me. Reading your review made me feel that the goals I had been pursuing all along were indeed the right ones. I've devoted an enormous amount of time to researching and developing gold EAs. My focus has never been just on making an EA that wins, but on understanding *why* it wins, how it generates profits, and how to build something that can remain robust over the long term. To be honest, I never expected to receive a review like this. It genuinely feels like all those years of hard work have been rewarded. The reality is that many EA users only care whether an EA makes money. That's completely understandable, and as a developer I've always known that the underlying architecture, risk management, statistical consistency, and design philosophy often go unnoticed. That's why your review was so meaningful to me. You didn't just analyze the performance—you looked beyond the numbers and understood the reasoning behind the system itself. As a developer, that level of insight is incredibly rewarding to see. In fact, I found myself wishing I had your level of analytical insight as well! 😄 Thank you again for your outstanding review. It truly means a great deal to me.
ys1267 tkhs
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ys1267 tkhs 2026.06.16 02:05 
 

O usuário não deixou nenhum comentário para sua avaliação

Shota Watanabe
8102
Resposta do desenvolvedor Shota Watanabe 2026.07.05 15:17
Thank you very much for your wonderful review! I'm especially happy that you felt the EA has a low risk of overfitting. One of my main goals during development was to make the model learn meaningful market patterns without memorizing market noise. I believe this is one of CatBoost's greatest strengths. Achieving this balance is much more difficult with deep learning, and I think it's one of the reasons Ginga has remained stable in live trading. Thank you again for your kind words and support. I'll continue doing my best!
Cristian Salute
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Cristian Salute 2026.05.22 18:18 
 

O usuário não deixou nenhum comentário para sua avaliação

Shota Watanabe
8102
Resposta do desenvolvedor Shota Watanabe 2026.05.23 14:31
Thank you so much for the wonderful review!
We will continue to work hard on developing even better EAs.
Please keep following me so you can receive the latest updates.
Thank you!
Yonatan Hellman
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Yonatan Hellman 2026.05.07 10:38 
 

O usuário não deixou nenhum comentário para sua avaliação

Shota Watanabe
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Resposta do desenvolvedor Shota Watanabe 2026.05.07 11:15
Thank you so much for your kind review! Our EA currently calculates the day's realized and unrealized P&L to automatically close positions and stop trading. We are planning an upcoming update that will include TP and SL functionality. We hope you will continue to enjoy using it, and we look forward to bringing you even better performance with the next version!
René
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René 2026.05.06 19:00 
 

O usuário não deixou nenhum comentário para sua avaliação

Shota Watanabe
8102
Resposta do desenvolvedor Shota Watanabe 2026.05.07 11:17
Thank you so much for the wonderful review, René! I believe this will become my greatest masterpiece, and I have high hopes for it. I look forward to your continued support!
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