Gold Cortex AI
- エキスパート
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Shipra Gupta
私はShipra Gupta、数学、経済学、アルゴリズム取引システムに強いバックグラウンドを持つトレーダー兼クオンツ戦略開発者です。これまで、Forex、ゴールド、指数、コモディティ、暗号資産市場に幅広く携わり、一貫性、精度、規律ある執行を重視したデータ駆動型の取引戦略を構築してきました。 - バージョン: 1.50
- アクティベーション: 10
Gold Cortex AI - Advanced Gold Trading EA for MetaTrader 5
Gold Cortex AI is a gold trading Expert Advisor for MetaTrader 5 designed for automated XAUUSD trading. This gold trading EA combines proprietary market analysis, multi timeframe evaluation, intelligent trade filtering, and volatility based trade management in a structured automated trading system. Developed for the XAUUSD M15 chart, Gold Cortex AI provides automated trade execution, configurable risk management, and flexible strategy controls for traders seeking a systematic approach to gold trading.
The system uses a proprietary decision framework to evaluate market conditions and identify potential trading opportunities without relying on a single market signal. Its internal strategy methodology remains proprietary, while traders retain control over key execution, risk, and filtering parameters.
Key Features
| Feature | Description |
|---|---|
| Proprietary Strategy | Multi layer market analysis with confidential internal trading logic |
| Multi Timeframe Analysis | Evaluates market direction and conditions across multiple timeframes |
| Four Trading Engines | Independently configurable engines within a shared strategy framework |
| Automated Execution | Pending order placement, refreshing, and expiration management |
| ATR Based Protection | Volatility adjusted Stop Loss and Take Profit levels |
| Trailing Stop | Automated protective stop adjustments after a defined profit threshold |
| Dynamic Position Sizing | Percentage based risk calculation or fixed lot trading |
| Execution Filters | Configurable spread limits, trading hours, and optional day filters |
Strategy Overview
Gold Cortex AI uses a proprietary market analysis framework designed to evaluate gold market conditions before placing trades.
Its core principles include:
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Market structure assessment to evaluate potential trading opportunities.
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Multi timeframe analysis to establish broader market context.
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Directional and momentum filters to assess trade suitability.
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Multiple analytical engines to evaluate different market structures.
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Volatility aware trade management to define protective levels.
The precise entry conditions, internal engine configurations, and strategy parameters are intentionally not disclosed.
Risk Management
Gold Cortex AI offers configurable position sizing and trade protection controls.
| Parameter | Default | Purpose |
|---|---|---|
| RiskPct | 1.2 percent | Calculates position volume using account balance and planned Stop Loss distance |
| FixedLot | 0.01 | Fixed volume when percentage based risk is disabled |
| MaxLot | 5.0 | Maximum permitted volume per order, subject to broker limits |
| SL_ATR | 2.0 | Initial Stop Loss distance as an ATR multiple |
| TP_ATR | 4.0 | Initial Take Profit distance as an ATR multiple |
| TrailStart | 2.0 | Profit threshold for trailing eligibility, measured in ATR |
| TrailDist | 1.2 | Trailing distance measured in ATR |
Actual risk may differ from the configured percentage due to broker minimum lot requirements, volume rounding, slippage, gaps, and execution conditions.
Installation and Setup
Follow these steps before enabling automated trading.
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Open MetaTrader 5 and select your broker's XAUUSD symbol.
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Open an M15 chart and attach Gold Cortex AI.
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Enable algorithmic trading and verify the EA permissions.
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Confirm sufficient H1 and D1 historical data is available.
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Configure risk settings, spread limits, and trading filters.
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Review the individual engine switches and retain the default configuration for initial testing.
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Run a Strategy Tester backtest before proceeding to demo forward testing.
Broker symbol specifications, trading permissions, margin requirements, and order restrictions can affect execution.
Understanding the Main Parameters
| Parameter Group | Key Settings | Function |
|---|---|---|
| Risk | RiskPct, FixedLot, MaxLot | Controls position sizing and maximum order volume |
| Trend | UseTrendGate, EmaPeriod | Controls the primary directional filter |
| Daily Filter | ShortD1Gate, D1EmaPeriod, D1SlopeBars | Controls additional daily confirmation for sell trades |
| Momentum | MomGate, MomEma, MomATR | Controls momentum confirmation |
| Volatility | AtrPeriod, SL_ATR, TP_ATR | Controls volatility measurement and protective distances |
| Trailing | TrailStart, TrailDist | Controls trailing stop behaviour |
| Execution | MaxSpreadPts, FridayCutH | Controls spread and Friday pending order restrictions |
| Schedule | SkipWednesday | Optionally excludes Wednesday trading |
| Engines | EngA, EngB, EngC, EngD | Enables or disables individual strategy engines |
Parameter names correspond to the EA inputs. Changes should be evaluated systematically because they can affect trade frequency, exposure, drawdown, and performance.
Parameter Optimization Guide
The objective of optimization is to find robust settings that remain reasonably consistent across different market conditions, rather than maximizing historical profit alone.
Step 1. Establish a Baseline
Run the default configuration using realistic historical data and trading costs.
Record the following metrics:
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Net profit after trading costs
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Maximum equity drawdown
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Profit factor
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Total number of trades
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Average trade duration
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Recovery factor
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Performance across separate market periods
Step 2. Optimize Risk Settings
Test conservative position sizing before increasing exposure.
A research range of 0.25 to 1.0 percent risk per trade can be used to compare drawdown and recovery behaviour. These values are testing suggestions, not guaranteed safe or optimal settings.
Step 3. Test Trade Management
Optimize related parameters in controlled groups.
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Evaluate Stop Loss and Take Profit distances.
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Test trailing activation and trailing distance separately.
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Compare trade frequency, average trade outcome, and drawdown.
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Avoid changing every parameter simultaneously.
Step 4. Evaluate Filters and Engines
Test the market filters and individual engine switches to understand their contribution to overall performance.
Compare different combinations using the same data, execution assumptions, and evaluation metrics. Consider whether additional engines improve consistency or simply increase exposure.
Step 5. Validate Results
Use separate optimization and out of sample periods.
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Optimize on historical data from one period.
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Validate the selected settings on unseen data.
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Test across trending, ranging, and volatile market conditions.
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Conduct demo forward testing under realistic broker conditions.
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Prefer stable parameter ranges over isolated high performing combinations.
Excessive optimization can lead to curve fitting, where settings perform well historically but fail under new market conditions.
Recommended Testing Environment
| Setting | Recommendation |
|---|---|
| Trading Instrument | XAUUSD |
| Chart Timeframe | M15 |
| Analytical Timeframes | H1 and D1 |
| Backtesting | MetaTrader 5 Strategy Tester |
| Modelling | Most realistic available tick modelling |
| Trading Costs | Account for spread, commission, and slippage |
| Validation | Out of sample testing and demo forward testing |
Important Risk Disclaimer
Gold trading involves substantial financial risk. Volatility, spread widening, slippage, gaps, and broker execution conditions can result in losses that exceed the intended risk estimate.
Gold Cortex AI does not guarantee profits. Backtested results do not guarantee future performance. Traders should understand the EA settings, evaluate their own risk tolerance, and test the system thoroughly before using it on a live account.
Gold Cortex AI
A structured approach to automated gold trading through proprietary market analysis, multi timeframe evaluation, configurable execution controls, and volatility based risk management. Designed for traders who value systematic execution, flexible configuration, and disciplined strategy evaluation.
