HEDGE GRID is a systematic trading algorithm that combines structured grid placement with conditional hedging, dynamic position sizing, and market structure filtering. Designed for short-term volatility capture, the system operates on configurable timeframes (default M1) and is parameterised for deployment across liquid forex and commodity pairs. While the included validation report focuses on XAUUSD, the architecture is symbol-agnostic and supports multi-asset configuration through adjustable volatility thresholds, session windows, and spread filters.

📊 Backtesting & Validation Methodology

Performance validation was conducted using cTrader’s Historical Replay engine with tick-level server data to ensure execution accuracy. The testing environment simulated real-market conditions, including:

• Variable spread modelling based on historical tick data
• Slippage tolerance enforcement (1.2 pips default)
• Order-fill latency simulation and partial fill handling
• Session-based time filtering and daily trade/profit limits
• See Images with live trading XAUUSD algorithm settings, in cloud profitable trades settings validation
• Walk Forward

The reported results reflect behaviour under the specific parameter constraints provided, including a hard drawdown limit of 6.4%, daily profit target of $8.1, maximum daily trades of 8, and strict position/volume caps (9 positions, 1.81 lots total). Fitness optimisation prioritised consistency metrics (Sortino ratio, win rate, profit factor, and payoff) with penalty weighting for low trade frequency and excessive volatility exposure.

Note: Backtest results are conditional on the specific market regime, broker execution model, and parameter set used during validation. They do not guarantee future performance across different instruments, timeframes, or live trading environments.

🎯 Intended User Profile & Optimization Workflow

HEDGE GRID is engineered for both beginner and experienced traders who prioritise systematic discipline, but it is explicitly not designed for passive or “set-and-forget” operators. Because the algorithm’s performance is intrinsically tied to instrument-specific volatility profiles, session liquidity, and broker execution behaviour, each asset class—whether FX pairs, indices, commodities like gold, or equities—requires dedicated optimisation to identify optimal settings before live deployment. This is a state-of-the-art, professionally engineered system, and its sophistication lies in a proprietary custom fitness optimisation framework that simultaneously evaluates multiple performance dimensions, including Sortino ratio, profit factor, win-rate consistency, payoff efficiency, and drawdown resilience. By assigning targeted weights to these metrics, the fitness engine filters out curve-fitted noise and surfaces statistically robust parameter sets that deliver a measurable, sustainable edge. This architecture demands active involvement, structured testing, and careful fine-tuning. If you are seeking a plug-and-play solution requiring zero configuration, this system is not suitable. However, for traders willing to invest time in proper optimisation, HEDGE GRID provides a transparent, highly controllable, and institutional-grade framework for disciplined algorithmic trading.

⚙️ Technical & Infrastructure Requirements

• Hosting: A Dedicated Virtual Private Server (VPS) can be optimal for stable operation. Hedge Grid Strategy works well on the local CTrader machine and the CBot cloud
• Latency: Optimal execution requires sustained network latency of ≤1ms to the broker’s execution server. Higher latency may degrade Fill-or-Kill routing, spread filtering accuracy, and hedge trigger precision.
• Broker Environment: ECN/Raw spread account recommended. Minimum deposit should accommodate maximum configured exposure and margin requirements.
• Platform: cTrader Desktop or cTrader Web with cBot API access enabled.
• Server Time Alignment: Required for accurate session filtering (12:04 to 01:02 server time default).

🧩 Core Architecture & Configurable Parameters

Grid Engine

Base spacing 10 pips with 1.2x multiplier, max 9 levels, ATR-smoothed boundaries (3.1–36.9 pips), optional volatility-adaptive spacing

Hedging Protocol

Distance-triggered hedge at 28.6 pips, configurable hedge ratio (0.3x), optional ATR-based trigger override

Risk Controls

Daily trade limit (8), daily profit target with auto-close, hard position caps (6 per side), unit-lot risk model (6.21% per entry), break-even & trailing options

Market Filters

Order block detection, breakout/compression analysis, adaptive spread/ATR ratio filtering, session time windows

Execution Routing

Limit order preference, Fill-or-Kill enforcement (0.3 pip tolerance), slippage control, dynamic lot sizing with hard volume cap

For backtesting the Try Product, you can input these parameters for standard and ECN raw accounts.

With the try product optimisation,n any trader can find many setups to backtest and try with Demo.

⚠️ Important Disclaimers

1. No Performance Guarantees: Trading financial instruments involves substantial risk. Past performance, including backtested or historical replay results, is not indicative of future results. The developer makes no representations or warranties regarding profitability, consistency, or drawdown behaviour in live markets.
2. Market & Broker Dependency: Actual results vary based on broker execution quality, spread conditions, slippage, liquidity, news volatility, and server infrastructure. The algorithm’s filters and hedging logic assume stable, low-latency execution environments.
3. Parameter Responsibility: All configurable settings (grid spacing, multipliers, risk per trade, session filters, lot sizing, etc.) are user-adjustable. Improper configuration may increase exposure, breach margin limits, or trigger unintended position clustering. Users must thoroughly test parameter sets in demo environments before live deployment.
4. Use at Your Own Risk: By installing or running CBOTs, you acknowledge that you have read, understood, and accepted all technical requirements, configuration responsibilities, and risk disclosures. The developer assumes no liability for losses, margin calls, platform errors, or execution deviations resulting from live trading.
5. Electronic Communication Network ECN (Finance/Trading): a computerised system that automatically matches buy and sell orders for securities. It allows major brokerages and individual traders to trade directly without an intermediary like a stock exchange specialist. Broker-dealers ' quality of matching engine and order-filling varies across the industry and requires traders to actively monitor slippage and spreads, limiting max spread and max slippage to obtain optimal order matching. Important to understand that Broker-dealer desks often do not match retail traders' algorithmic strategies, as this is due to the technical requirement of VPS latency <1ms. but also on Brokers' routing choices. CFDs are synthetic prices, not centrally cleared at the stock exchange level, but algorithmically matched by Broker-Dealers ' desks.

Important on Optimisation Requirements

This algorithm is designed for both beginner and expert traders, but it is absolutely not suitable for lazy traders. For each financial instrument you wish to trade, whether it is a currency pair, index, commodity like gold or silver, or individual stock, you must perform your own optimisation process to find the optimal settings. Market behaviour differs significantly between instruments, and what works perfectly on one symbol will not work on another without proper tuning. The algorithm provides a state-of-the-art, high-quality framework and unique fitness optimisation tools, but you must be willing to invest the effort to adapt it to your chosen markets. This is a precision tool for serious, active traders who understand that market adaptation is the key to long-term profitability.

Past performance, including the backtest results presented for XAUUSD, does not guarantee future results. The algorithm's performance will vary based on market conditions, broker execution quality, latency, and parameter configuration. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown in backtests.

The algorithm requires instrument-specific optimisation. Parameters that perform well on one symbol or timeframe may produce losses on another. Users are solely responsible for conducting their own testing and validation before deploying the algorithm on a live account.