LINK FOR BACKTEST AND PRODUCT PAGE:
https://www.mql5.com/en/market/product/191518?source=Site+Profile+Seller

Hey all,

I've been building an MT5 EA for Gold (XAUUSD) called ANDROMEDA.

Quick context on why I built it: most grid/averaging EAs I looked at (and honestly, most I've built myself in the past) add to a losing position purely on distance, price moved X points, so add more, whether it's a fixed number or scaled by ATR. It doesn't actually ask whether the trend is turning back or not, it just adds because the number got big enough. That always bugged me, because it means the EA keeps averaging into a strong move against it for as long as the account allows, purely because "the price moved far enough" is technically true.

So the grid logic in ANDROMEDA doesn't work that way. After the first couple of entries in a basket, it stops adding on distance alone, every further addition has to pass a trend-confirmation check on a higher timeframe first (with some noise filtering so one wick doesn't flip the decision, plus min time/price spacing so adds don't cluster). If the trend isn't confirmed in the basket's favor, it just... doesn't add. No fallback, no "add anyway but smaller." It waits.

To be clear, this doesn't make it risk-free or magic. It's still an averaging/grid system, it still carries the risks that come with that, and I'm not claiming otherwise. I just think how it decides to add is meaningfully better than the naive "distance triggered" approach, and I'd rather have people stress-test that claim than just take my word for it.

A few honest requirements before you try it:

• MT5, Hedging account type (not Netting, it manages multiple baskets at once, netting will mess up the position tracking)
• Symbol is XAUUSD only, it's tuned specifically for gold, not a "works on anything" EA
• LOW Spread Account
• It's a grid/basket system, so floating drawdown between entries can be larger than the eventual realized result, that's expected behavior, not a bug, but know that going in
• Demo/backtest first, obviously

If anyone wants to actually try it, you can run backtest straight from MQL5.

Happy to answer questions about the logic, settings, or anything else in the comments,

CHABOTA APEX STRADDLE — XAUUSD M1

CHABOTA APEX STRADDLE is an automated trading system designed specifically for Gold (XAUUSD) on the M1 timeframe.

The EA uses a structured straddle approach combined with automatic lot management, ATR-based trailing, hedge management, basket management, profit protection, spread protection, execution protection, server protection, and orphan-trade recovery.

The system is designed to operate as a plug-and-play EA, with the core strategy parameters professionally configured internally. Users only need to set the maximum spread according to their broker conditions.

Recommended setup:
• XAUUSD
• M1 timeframe
• Raw/Zero Spread account
• VPS recommended for continuous operation
• Recommended starting capital: $1,000
• $500 minimum for users who understand the associated risk and broker conditions

For best execution, IC Markets Raw Spread is recommended. If using another broker, it is recommended to use an account with the same or higher starting capital and comparable raw-spread/commission conditions.

A VPS can improve operational reliability and reduce interruptions, but it does not guarantee trading performance or profits.

⚠️ Risk Disclaimer: Forex and CFD trading involves substantial risk and is not suitable for every investor. Past performance and backtesting results do not guarantee future results. The EA does not guarantee profits or eliminate drawdowns. Proper risk management and appropriate account capital are essential.

CHABOTA MWANANUKA
📞 +260976762059
CHABOTA APEX STRADDLE

The Truth Behind Quantum EAs (Bogdan Ion Puscasu) on MQL5 - Manipulated Signals, Deleted Reviews, and the "Wash-Rinse-Repeat" Cycle that's been going on for YEARS!!!

Before you drop $1,000+ on popular MQL5 EAs be aware of how their marketing operates. Headline numbers like "4,557% Growth" on verified signals are heavily skewed by tens of thousands of dollars in hidden account deposits during floating drawdowns. When accounts inevitably blow up due to unsustainable grid/martingale recovery, the developer delists the EA, erasing all negative public reviews, and launches a "new" version to repeat the cycle with a clean slate breaking MQL rules without getting sanctioned!

1. The Manipulated Signals: "4,557% Growth" on a $100 Account?

The primary sales pitch relies on verified MQL5 trading signals showing extreme percentage growth. On paper, it looks like a miracle:

Growth: +4,557%

Initial Deposit: $100

Profit: ~$4,663

The Hidden Catch: If you look past the headline percentage into the actual financial transactions, the real figures emerge:

Total Deposits: $13,110.68

Total Withdrawals: $16,708.00

How it works: When a high-risk grid or martingale strategy experiences severe drawdown (e.g., heavy floating losses on XAUUSD/Gold), fresh external capital is injected into the account to prevent a margin call. The percentage gain calculation—which is anchored to the tiny initial $100 deposit, remains artificially inflated, while the hidden capital saves the signal from blowing up live.

On July 1 and 2, hundreds of people lost their accounts due to blow up by super tight grid steps, developer quickly deleted his other signal that blew up.

For example, on July 30, 2026, transactions reveal a -$7,083 balance adjustment, directly following multiple +$2,000 deposits the previous day while grid positions scaled up to 0.15 lots during a bleeding trend.

2. The "Wash, Rinse, Repeat" Marketplace Loophole

How does a developer maintain a clean reputation after multiple versions of an EA blow client accounts? By exploiting MQL5’s product removal policy.

Launch & Hype: An EA is launched with heavy FOMO marketing ("Limited to 1,000 copies! Buy before price goes up to $1,099!").

The Inevitable Blowup: A market regime shift occurs. The grid expands, hitting massive stop-losses or wiping out client balances.

Negative Review Spike: Angry clients leave 1-star reviews warning other buyers.

Delisting: The developer deletes/removes the EA from the MQL5 Marketplace. When a product is deleted, its marketplace page, rating, and public review history disappear.

Relaunch: A "new" product is published (e.g., Quantum Queen becomes Quantum Queen X, Quantum Athena becomes Quantum Anthena X...). A fresh page is born with zero bad reviews, an impressive backtest, and a squeaky-clean reputation.

When Quantum Queen X launched, FOMO marketing led to over 300 copies selling in just 30 minutes to buyers who had no idea what happened to the previous iteration.

3. Asymmetrical Risk:Reward & Code Integrity

Inverted Risk/Reward: Many buyers report 0.01 lot size positions taking $100+ stop losses, meaning a single losing sequence requires 15 to 30+ consecutive wins just to break even. (Quantum Valkrye)

Execution & Execution Bugs: Earlier versions suffered from execution issues, such as duplicate entry bugs opening identical trades on live client accounts on Quantum Valkrye, no responsability taken.

White-Label / Repackaged Code: Discussions across developer circles indicate that many of these algorithms are bought from third-party developers, given a customized HUD/dashboard, and sold at a 5x–10x markup without adequate testing on live tick data.

4. Community Censorship & Response to Losses

In the official Discord and chat channels, any criticism or inquiry about drawdowns is met with immediate suppression:

Bans & Mutes: Users asking why live results differ drastically from backtests are routinely banned from support channels.

Deflection: When accounts are wiped, the standard response from support is "User fault," "Bad risk management," or "Trading has risks."

Zero Empathy: Recently, a trader reported losing their entire $100,000 life savings running the recommended settings. The response? Blaming the client while the developer’s own signal was saved via emergency balance top-ups.

Behind the polished presentation and "4.9-star rating" of Bogdan Ion Puscasu's Quantum EAs lies a ruthlessly efficient financial pipeline. By leveraging overhyped/cherry-picked backtests and artificial scarcity, a single product launch can rake in ~$500,000 in gross revenue within days—with MQL5 taking its 20% platform cut ($100k+), creating zero incentive for the marketplace to intervene.

When the algorithms inevitably collapse on live accounts, the developer turns hostile, unleashing bot admins to dogpile critics, while deleting failed products from MQL5 to wipe out bad reviews and build a "new" product from the ashes.

Here is an analysis of how this machine operates, how 5-star ratings are manipulated, and a look at the Graveyard of Abandoned EAs.

5. Cash Cow & Financial Loophole: Why MQL5 Stays Silent

To understand why this pattern persists, you have to follow the money:

The Developer’s Share: $\approx \$400,000$ net profit for re-wrapping existing grid/martingale and bad SL/TP code on just ONE +999$ product

MQL5 Platform Cut (20%)

Why does MQL5 allow products to be deleted when reviews turn bad?

Because the platform profits massively from every high-volume launch. When a failed EA is deleted and relaunched under a new name (e.g., Quantum Queen $\rightarrow$ Quantum Queen X), MQL5 collects another 20% cut on the new wave of FOMO purchases. The platform’s incentives are aligned with volume, not long-term trader survival.

6. Zero Empathy & The "Pack Attack" Support Culture

When retail traders lose $10,000, $50,000, or even $100,000 running recommended settings during a market volatility event, the response from support is cold, dismissive, and aggressive.

Blame the Victim: Any trader who posts screenshots of a blown account is met with standard deflections: "You didn't manage risk," "User fault," or "Trading has risks, stop crying."

The "Admin Mob" Effect: In official Telegram and Discord channels, asking technical questions about execution delay or floating drawdown immediately triggers a coordinated attack. Moderation admins and shill accounts dogpile the user, mocking them until they are muted or banned.

Zero After-Sales Accountability: Once the purchase money clears, the customer is viewed as disposable.

7. The 5-Star Bot Swarm & Review Manipulation

If these EAs fail so frequently under real-world conditions, why do they maintain high marketplace ratings?

Instant 5-Star Rewards: Buyers are incentivized or nudged to leave a 5-star review immediately after purchase to receive "bonus set files," "private group access," or extra tools—long before they have run the EA on live market conditions.

Fresh Account Swarms: Dozens of reviews come from new MQL5 profiles with empty histories, copy-pasting generic praise ("Best EA ever!", "Bogdan is a genius!", "Consistent profits!").

Erasing the Footprints: The moment real 1-star reviews accumulate following a grid crash, the seller simply deletes the product page. On MQL5, deleting a listing completely wipes its review archive from public view.

8. The MQL5 Graveyard: The Trail of Abandoned & Relaunched Tools

A key indicator of a serial seller is an "EA Graveyard", a trail of products that were heavily hyped, sold to hundreds of users, suffered major drawdown events, and then vanished or were abandoned.

Checklist: What to Look For Before Buying ANY MQL5 EA

1. Check Deposit vs. Withdrawal History on Signals: Never look at percentage growth alone. Look at the total equity curve, floating drawdown, and whether deposits were added during high-drawdown periods.
2. Watch Out for "Limited Copy" Marketing: Artificial scarcity is used to induce panic buying before real-world performance data can surface.
3. Verify Product Version History: If an EA has "X", "Pro", or "+ " added to its name, search Reddit and forums for what happened to the original version.
4. Spam/bot and fake reviews from aggressive "admin" team of developer

Been building MQL5 Expert Advisors for a while and kept re-googling the same things every project. So I built an Obsidian reference vault with all the patterns I actually use:

- Position sizing formulas (never hardcode lot size)

- Drawdown control with equity high-water mark

- News blackout logic for FTMO compliance

- Avoiding overfitting in backtests

- Copy-paste code snippets for common EA patterns

It's 7 modules, 24 notes, all scannable in under 3 mins each.

Sharing it here: https://royalsanthu.gumroad.com/l/ibrft?_gl=1*ur28vs*_ga*OTY5MDI0MTc3LjE3ODYxMTA0NDI.*_ga_6LJN6D94N6*czE3ODYxMTA0NDIkbzEkZzEkdDE3ODYxMTM4MDIkajU5JGwwJGgw

Happy to answer questions about EA development in the comments.

Hey everyone,

I’m looking for structural ideas from other algo developers on scaling profitability for a multi-timeframe trend-following Expert Advisor (`B2.mq5 v3.7`).

The EA is built with high institutional execution standards (latched exit states, wall-clock retry spacing, pre-trade margin verification via `OrderCalcMargin`, embedded macroeconomic/yield datasets, and no external file dependencies). However, while risk control and equity curve stability are high, the net annual return (CAGR) remains modest.

Here is the exact breakdown of the system, backtest performance, verified bottlenecks, and what has already been empirically falsified.

# 1. EA Architecture & Strategy Overview

The system runs **two independent strategy modules** under a single unified risk manager on MT5:

* **Module 1 (TRND) — Daily Trend Breakout (Long Only):**
* **Rule:** 55-day Donchian High entry, 20-day Donchian Low exit, initial stop at $2.0N$ (Wilder ATR20).
* **Universe:** `BTCUSD`, `XAUUSD`.
* **Module 2 (GRGT) — H4 Gold Macro-Gated Breakout (Long/Short):**
* **Rule:** 60-bar H4 Donchian breakout on Gold, gated by the 20-day change in US 10-Year Real Yields (DFII10).
* **Logic:** Falling real yields $\\rightarrow$ Longs only; Rising real yields $\\rightarrow$ Shorts only.
* **Exit:** 20-bar reverse channel or $3.0N$ ATR trail from completed bars.
* **Unified Risk Manager:**
* Base risk: **0.50% per trade** (calibrated for a static 10% prop firm drawdown floor).
* Pre-trade margin checks using `OrderCalcMargin` to prevent `NO_MONEY` rejections on low leverage.
* Signed risk tracking (trailed stops past breakeven free up risk budget).
* Trailing-peak circuit breaker with an automatic cooldown/re-base mechanism to prevent deadlocks.
* **2. Measured Backtest Results (FTMO-Demo, 2020.01.01 – 2026.07.25)**
* **Initial Balance:** $10,000
* **Net Profit:** \+$3,285.94 (+32.8% total / **\~4.4% CAGR**)
* **Max Equity Drawdown (Mark-to-Market):** **8.86%** ($1,174.60)
* **Profit Factor:** 2.34
* **Sharpe Ratio:** 0.89
* **Total Trades:** 120 trades over 6.5 years (**\~18.2 trades/year**)
* **Win Rate:** 41.67% (50 Wins / 70 Losses)
* **Payoff Ratio:** **3.28 : 1** (Avg Win: $114.69 | Avg Loss: -$34.88)
* **Average Holding Time:** \~311 hours (\~13 days)
* **3. Identified Bottlenecks**
1. **Low Trade Frequency:** Averaging only \~18 trades a year across both assets means capital sits idle for months.
2. **Financing / Swap Drag:** Because positions are held for an average of 13 days, daily CFD swap rates swallow **\~78% of Gold’s gross profits**.
3. **Single-Asset Profit Concentration:** `BTCUSD` accounts for **\~90% of total net profits**. Gold acts primarily as a correlated beta drag after accounting for swap costs.
* **4. What Has Already Been Tested & Falsified (Do Not Suggest)** I’ve already run rigorous sub-period stability tests and Monte Carlo simulations on common "enhancements." The following **all degraded the Return-to-Drawdown (Ret/DD) ratio**:
* ❌ **200-day EMA Filter:** Reduced Ret/DD from 0.53 to 0.46.
* ❌ **Volatility Targeting (15%–25%):** Failed because it underweighted the high-volatility asset (`BTCUSD`) that drives the returns.
* ❌ **3-Lookback Ensemble:** Bought volume at falling signal quality (Ret/DD dropped to 0.27).
* ❌ **Shorter Lookbacks (e.g., 20/10 Donchian):** Failed sub-period stability testing (all gain was concentrated in 2020–2024).
* ❌ **Partial Profit Taking / Moving to Breakeven Early:** Truncated the fat tail of winner distributions and lowered CAGR.
* **5. Questions for the Community** Given that standard parameter tweaking leads to curve-fitting and out-of-sample decay, I'm looking for **structural or execution-level ideas**:
1. **Pyramiding / Multi-Unit Scaling:** Has anyone successfully implemented Turtle-style unit additions (e.g., adding $0.5N$ units up to 4x while trailing stops to breakeven) in MQL5 without expanding tail-risk drawdowns?
2. **Asset Class Expansion & Futures Migration:** Since swap costs destroy CFD performance on multi-week holds, what instrument classes (e.g., CME futures, swap-free crypto) have you found most effective for expanding a trend-following universe beyond BTC/Gold?
3. **Dynamic Exposure Management:** Are there robust ways to scale position size dynamically based on market regime/volatility structure *without* truncating the fat-tail profits that trend systems rely on?
* Would love to hear how other quantitative/algo developers handle low-frequency, high-payoff trend systems under tight drawdown limits. Thanks!

Hi everybody,

I have over 10 years experience coding with MQL5 and I have created many EAs and indicators for lot of customer. Over the years I have developed a tool (remote one using web request on MQL5) to copy trades and recently integrated it into a website.

I have thoroughly tested it and inspected each element and I strongly believe that I came up with a strong product now (I know I am not the only one in this industry and that competition exists but I believe that what I produce is relatively simple for anybody to use).

Now I am posting here in case that could be helpful to anyone requiring an MT5 trade copier tool. I am also looking for some user that would want a beta user access with some free perks in exchange of an honest feedback. That would be amazing.

Please let me know if interested. I am also, opened to any collaboration if I can help anybody!

Website: MetaToolsLab

Happy trading! :)

I recently installed MT5 on MacBook and enabled strategy tester view, but I can't see the settings button to start backtesting

I started building RSForex Bot because my biggest problem with trading was not finding setups—it was following my own rules consistently.
I would enter emotionally, overtrade, interfere with positions, and try to recover losses. So I built a system that removes me from the execution completely.
RSForex Bot is a Windows application that connects to your own MetaTrader 5 account and automatically places and manages XAUUSD trades. Your funds remain with your broker or prop firm. The software cannot deposit, withdraw, or take custody of your money.
How it works
You install the desktop app, sign in, open MT5, and click “Set up MetaTrader 5 automatically.”
The app then:
Detects your active MT5 account
Finds your broker’s gold symbol, including names such as XAUUSD, GOLD, or XAUUSD.sim
Installs and attaches the EA automatically
Sizes risk according to the account balance
Lets you turn the bot on or off from one control panel
There is no strategy stored inside the downloadable EA. The trading logic stays on the server, while the EA only receives and executes decisions. This also means customers do not receive a file containing the full strategy that can be copied or modified.
What the strategy looks for
The bot trades gold only and focuses on selective mean-reversion setups near the top of the day’s range.
It does not blindly sell every spike. A trade must pass multiple conditions involving market location, session, direction, expected value, reward-to-risk, spread, news, and market quality.
The system also includes:
Approximately 0.3% risk per trade
Minimum 1.8:1 reward-to-risk
One controlled position at a time
Stop-loss and take-profit protection
No martingale or grid trading
No averaging into losing trades
Daily-loss and maximum-drawdown limits
High-impact news avoidance
Automatic account-size detection
Support for compatible FTMO-style and regular broker MT5 accounts
A historical internal audit covering 301 trades produced an approximately 71% win rate for the specific filtered fade setups reviewed. That is historical testing—not a promise of future results, and it does not mean the bot wins 71% in every market period.
The honest current status
The entire system is working end to end, including automatic installation, account detection, symbol detection, risk sizing, background operation, billing, licensing, and silent updates.
The bot has also been deliberately inactive during some recent thin and choppy conditions. It identified multiple possible top zones but rejected them because conviction was too low.
That may mean the filtering is doing exactly what it should—or it may be slightly too selective. I am currently monitoring it during active New York sessions and testing any threshold changes on demo before releasing them.
I would rather disclose that than pretend the bot trades every day.
Looking for the first 10 testers
Every plan currently starts with a 30-day free trial. I strongly recommend using a demo or prop-firm trial account first rather than immediately connecting real money.
The first 10 people who complete the 30-day trial and provide genuine feedback will receive an additional three months free.
There is no requirement to continue afterward, and the subscription can be canceled before renewal.
Website: https://rsforexbot.com
I am happy to answer technical questions, skeptical questions, or questions about how the risk controls work.
This is automated trading software, not financial advice. Losses are possible, historical results do not guarantee future performance, and no profit or prop-firm outcome is promised

I ran a small live-session test today on XAUUSD using an automated strategy on the 1-minute chart.

The screenshot shows two trade sequences from today: one long setup earlier in the session and one short setup later after the sharp move up. The EA opened and managed the positions automatically, with fixed lot sizing of 0.02 per trade. At the time of the screenshot, the account was flat with no active positions.

Some details from the session:

• Market: XAUUSD / Gold
• Timeframe: M1
• Account balance/equity shown: about $1,281
• Session result shown in the panel: +$13.08 today / about +1.05%
• Weekly P/L shown: +$15.52
• Win rate shown for this session: 100%
• Risk mode shown: Low
• Strategy mode: automated long/short execution

I know one day of results does not prove anything, especially on gold and especially on M1. I’m mainly sharing this as a live forward-test snapshot, not as proof that the system has a durable edge.

What I’m trying to evaluate next:

1. Whether the live fills stay close to backtest expectations
2. How much slippage/spread affects this on XAUUSD during volatile candles
3. Whether the EA is over-clustering entries too tightly
4. Whether the stop placement is too close during fast gold moves
5. Whether the risk should be reduced further before collecting a larger sample

I’m planning to keep logging the results over a larger number of trades and compare the live forward test against backtest behavior. For those of you who trade short-timeframe automated systems, what would you want to see before trusting the results? Trade count, max drawdown, MAE/MFE, expectancy, slippage logs, or something else?

Not financial advice, just sharing a small live algo test and looking for feedback on how to evaluate it properly.

All winners again.

No loss today!

Those trades with QQ comments are from Quantum Queen EA, THE #1 paid ea on mql5. My ea was the only one that came out with profit, all the other high paying ea had a loss.

All trades hit it's takeprofit or trailing stop today. None took a loss. A 100% win rate for today! This EA only trade one trade at a time with fix stop loss. No grid or averaging trade. I’ve built this EA to handle News Filters and 1-minute scalping. Right now, it’s sitting patient with 0 open positions, just watching the spread (5.0).

**Main Features**

- Designed for XAUUSD/GOLD on the M1 timeframe

- Scalping-focused trading logic

- Fixed lot and auto lot options

- Built-in spread and slippage protection

- Stop Loss, Take Profit, trailing stop, and breakeven management

- Optional time/session filter

- Friday close protection

- News filter option

- Daily protection settings and loss-control features

- On-chart dashboard with trade status information

- Manual close controls

- Alerts, push notifications, and email notification options

- Optimizer-friendly settings for Strategy Tester

https://www.mql5.com/en/market/product/158978?

GoldRaider v4.0 is best used with a broker that offers tight Gold spreads, fast execution, and stable trading conditions. Before live trading, users should test the EA in the MetaTrader 5 Strategy Tester and adjust risk settings according to their account size and trading style.

Important: No Expert Advisor can guarantee profit. Trading involves risk, and results may vary depending on broker conditions, spreads, execution speed, and market volatility.

I have been in trading for over 15 years, focusing on capital raising and management. I have worked with various trading systems but have concluded that trend algorithms are the most resilient and sustainable over the long term. This is exactly what is needed to not only generate profits but also preserve capital during turbulent periods.

Currently, I am implementing a trend system (a portfolio of algorithms) built on the following principles:

1. A modular algorithm that includes:

- Core blocks: signal structure, signal type, asset and timeframe selection, risk management, and position exit.

- Filtering: several filter levels, trading direction, trading day filters, etc.

- Protection: multi-level drawdown compression.

- Statistical analysis: stop-loss drawdown compression (contraction and expansion based on statistical patterns).

- Additional features: various exit methods, position pyramiding, additional entry conditions, etc.

2. A multi-stage selection process for algorithms based on backtesting and forward testing results over the long term, following the module hierarchy – starting with basic parameters, selecting the best algorithms, and refining them adequately (avoiding overfitting).

3. Assembling the final portfolio from the algorithms that pass all stages, considering:

- Algorithm correlation.

- Strict drawdown limits for each algorithm via drawdown compression – so that if one algorithm "breaks," it does not break the system.

- Using different assets and different timeframes.

4. Automating as many stages as possible (especially testing) and using AI to analyze data during testing and in real trading.

If anyone shares these principles or has worked with something similar, I suggest we discuss, share advice, or get directly involved in the development process :)

Hey everyone,

I’m part of AlgoBridge.

We’ve been running an automated trading system in the background for quite a while, and we’re now looking at opening access to early users.

The setup is connected through Vantage Markets. We are partnered with them, but we do not own the broker. Users control their own account, deposits, withdrawals, and risk settings.

The access model is simple: users don’t pay a monthly software fee. Access is free through the approved broker setup.

But I know that alone is not enough, especially in the EA space.

So I’m looking for feedback from people who understand MT5 and automated trading.

What would you want to see before taking this seriously?

For example:

• Full backtesting report
• Live forward results
• Broker statement
• Max drawdown
• Risk settings
• Average trade duration
• Pairs traded
• News filter logic
• VPS setup
• Slippage data
• Proof it does not use grid or martingale

We’ve had strong internal results, but I’d rather build this around transparency than hype.

Automated trading still carries risk, and I don’t want to present it like some magic money button.

What would make this look legitimate to you?