Moreland System 1


MORELAND SYSTEM 1

Proprietary XAUUSD H1 Support-Reversal Trading System

Moreland System 1 is a proprietary automated trading system developed by Moreland Algorithmic for XAUUSD on the H1 timeframe.

The system is built around structured support-reversal logic, systematic execution and defined risk. It is designed to identify qualifying market conditions, calculate position size according to the configured risk level and manage trades automatically according to its internal rules.

The underlying strategy logic, entry thresholds, confirmation rules and proprietary parameters are deliberately protected. The user controls the level of account risk, while the core strategy remains fixed.

http://www.morelandalgorithmic.com

TRADING APPROACH

Moreland System 1 focuses on identifying structured reversal opportunities around significant support areas in XAUUSD.

The strategy is rules-based and operates without discretionary intervention once enabled.

Core characteristics include:

  • XAUUSD-specific trading logic
  • H1 timeframe
  • Support-reversal methodology
  • Automated market analysis
  • Automated position sizing
  • Defined stop-loss protection
  • Structured profit targeting
  • Automated trade management
  • Percentage-based risk configuration
  • Account-level protection controls

PROBE-BASED ENTRY STRUCTURE

System 1 uses a controlled probe-based entry structure.

Rather than automatically committing the entire intended position immediately, the system may begin with a reduced-size initial position before evaluating whether the required confirmation remains present.

Where the system's internal conditions are satisfied, it may make one planned additional entry.

This structure is not intended to operate as an unlimited averaging or recovery system.

System 1 does not rely on:

  • Martingale position multiplication
  • Unlimited grid entries
  • Repeated averaging into losing positions
  • Progressive lot-size escalation

RISK MANAGEMENT

System 1 uses percentage-based risk sizing.

The intended risk amount is calculated from account equity and the configured risk percentage. Position size is then determined using the stop-loss distance and the value of the instrument per unit.

Position size is risk-driven, not leverage-driven.

Leverage affects the margin required to support a position, but it does not directly multiply the position size calculated by the system. If available margin becomes the limiting factor, leverage can affect whether the intended position can be opened in full.

Historical testing presented below was conducted using 1:50 leverage across all simulations.

User-configurable risk controls may include:

  • Risk per Trade (%)
  • Daily Drawdown Limit
  • Maximum Account Drawdown / Equity Floor
  • Account Profit Target (%)

The strategy logic itself remains protected and is not exposed through unnecessary optimisation parameters.

HISTORICAL TESTING & RISK ANALYSIS

The following results are derived from three independent historical simulations of Moreland System 1.

The purpose of testing multiple risk configurations separately is to evaluate how the realised trading path changes as risk increases rather than simply multiplying the result of a single backtest.

Test specification:

  • System: Moreland System 1
  • Instrument: XAUUSD
  • Timeframe: H1
  • Backtest window: 1 January 2024 - 30 June 2026
  • Platform: cTrader
  • Historical data: Tick data
  • Broker environment: FTMO historical environment
  • Starting balance: 100,000 account currency per simulation
  • Configured risk profiles: 0.4%, 1.0% and 2.0%
  • Leverage: 1:50 across all simulations

Final positions were entered on or before 30 June 2026, with final closure on 1 July where applicable.

EXECUTIVE PERFORMANCE SUMMARY

Metric 0.4% Risk 1.0% Risk 2.0% Risk
Ending Balance 222,779 418,074 846,615
Net Return +122.8% +318.1% +746.6%
Max Closed-Balance Drawdown 6.60% 20.17% 28.32%
Sharpe Ratio 2.46 2.02 1.90

The results demonstrate a clear relationship between configured risk, terminal growth, volatility and drawdown.

Growth increases materially as risk rises, but the results do not scale linearly. The simulations followed different realised execution paths rather than being simple mathematical multiples of one another.

EQUITY GROWTH COMPARISON

Configured Risk Ending Balance Net Return CAGR Closed Transactions
0.4% 222,779 +122.8% +37.9% 1,704
1.0% 418,074 +318.1% +77.5% 1,646
2.0% 846,615 +746.6% +135.5% 1,646

The higher-risk configurations produced substantially higher historical terminal balances, but they also generated materially greater volatility and drawdown.

The difference in transaction counts also confirms that these are separate historical simulations rather than simple arithmetic rescaling.

RISK-ADJUSTED PERFORMANCE

Metric 0.4% Risk 1.0% Risk 2.0% Risk
Net Return +122.8% +318.1% +746.6%
CAGR +37.9% +77.5% +135.5%
Max Balance Drawdown 6.60% 20.17% 28.32%
Annualised Volatility 13.0% 29.5% 49.4%
Sharpe Ratio 2.46 2.02 1.90
Sortino Ratio 6.61 5.54 5.92
Calmar Ratio 5.74 3.84 4.78
Gain-to-Pain 1.92 1.72 1.72

The 0.4% configuration produced the strongest historical risk-adjusted efficiency, including the highest Sharpe and Calmar ratios.

The 1.0% configuration produced materially higher historical growth while retaining a Sharpe ratio above 2.0.

The 2.0% configuration produced the highest historical terminal balance and CAGR, but also the greatest volatility and maximum closed-balance drawdown.

ANNUAL AND MONTHLY PERFORMANCE

Period 0.4% Risk 1.0% Risk 2.0% Risk
2024 +19.8% +54.1% +135.3%
2025 +74.2% +183.2% +258.8%
2026 H1 +6.8% -4.2% +0.3%
Positive Months 23 / 30 18 / 30 16 / 30
Best Month Apr 2025 +13.2% Jan 2025 +26.9% May 2025 +44.4%
Worst Month Jan 2024 -4.8% Jan 2024 -11.7% Jan 2024 -20.9%

The monthly distribution illustrates one of the principal trade-offs involved in risk scaling.

At 0.4% risk, 76.7% of the 30 historical months were positive.

At 1.0%, this fell to 60.0%.

At 2.0%, 53.3% of the historical months were positive.

Higher configured risk increased both the magnitude of strong months and the severity of weaker months.

MONTH-BY-MONTH HISTORICAL RETURNS

Month 0.4% 1.0% 2.0%
Jan 2024 -4.82% -11.74% -20.95%
Feb 2024 -0.42% -1.22% -2.63%
Mar 2024 +6.94% +17.77% +36.56%
Apr 2024 -1.62% -4.18% -7.71%
May 2024 +2.88% +7.33% +13.49%
Jun 2024 +2.35% +5.99% +14.52%
Jul 2024 +5.02% +12.60% +20.81%
Aug 2024 +4.29% +10.72% +31.05%
Sep 2024 +2.59% +7.04% +15.48%
Oct 2024 +4.83% +12.40% +7.06%
Nov 2024 +0.29% +0.43% +2.68%
Dec 2024 -3.47% -8.59% -7.16%
Jan 2025 +10.23% +26.88% +24.24%
Feb 2025 +0.64% +1.61% -1.37%
Mar 2025 +4.70% +11.92% +25.44%
Apr 2025 +13.20% +18.64% -5.43%
May 2025 +5.98% +16.52% +44.38%
Jun 2025 +1.01% -3.77% -14.77%
Jul 2025 -2.13% -3.30% -8.74%
Aug 2025 +3.26% -3.25% +0.76%
Sep 2025 +10.05% +19.85% +42.15%
Oct 2025 +6.12% +18.41% +28.97%
Nov 2025 +2.82% +4.28% -2.40%
Dec 2025 +2.02% +6.55% +21.94%
Jan 2026 +3.96% +10.36% +23.66%
Feb 2026 +1.30% -4.38% -2.42%
Mar 2026 -1.76% -1.28% -4.90%
Apr 2026 +1.58% -3.90% -4.73%
May 2026 +2.30% -2.07% -2.51%
Jun 2026 -0.68% -2.26% -5.92%

Monthly returns are calculated using realised month-end closed balances. Final 1 July closures, where applicable, are excluded from the June monthly return.

TRADE PROFILE & EXPECTANCY

Metric 0.4% 1.0% 2.0%
Closed Transactions 1,704 1,646 1,646
Profit Factor 1.84 1.58 1.66
Win Rate 41.8% 40.6% 36.1%
Average Winner +378.34 +1,293.43 +3,148.13
Average Loser -148.31 -560.11 -1,071.86
Winner / Loser Payoff 2.55x 2.31x 2.94x
Expectancy / Transaction +72.05 +193.24 +453.59
Largest Winner +5,481.27 +28,551.69 +111,228.60
Largest Loser -1,449.42 -4,905.80 -13,074.38
Maximum Losing Streak 23 23 27

Across all three simulations, System 1 retained a positively asymmetric payoff profile.

Average winning transactions were materially larger than average losing transactions.

The 2.0% simulation recorded the lowest win rate at 36.1%, but the highest winner-to-loser payoff ratio at 2.94x.

A closed transaction represents one ledger line and may represent a probe or planned additional entry. It should therefore not be interpreted as a count of unique market setups.

EXECUTION COSTS & MARKET EXPOSURE

Metric 0.4% 1.0% 2.0%
Gross Trading P&L +139,294.35 +369,254.55 +852,606.55
Commissions -2,287.68 -9,218.52 -31,407.00
Swap -14,227.30 -41,961.95 -74,584.10
Net P&L +122,779.37 +318,074.08 +746,615.45
Median Holding Time 9.1h 8.2h 6.0h
Average Holding Time 20.1h 19.5h 15.4h
Time Exposed 49.2% 46.1% 36.9%

All reported net historical results include commissions and swap contained in the underlying trade ledgers.

The higher-risk simulations incurred materially larger absolute trading and carrying costs because the position sizes were larger.

DRAWDOWN & RECOVERY

Metric 0.4% 1.0% 2.0%
Max Percentage Balance Drawdown 6.60% 20.17% 28.32%
Largest Absolute Balance Drawdown 8,760 68,495 199,415
Longest Underwater Period 81 days 147 days 146 days
Recovery Factor 14.02x 4.64x 3.74x
Calmar Ratio 5.74 3.84 4.78

Important drawdown limitation: these drawdown figures are derived from realised closed balances.

The source ledgers do not contain a continuous mark-to-market equity series. Intratrade floating-equity drawdown therefore cannot be reconstructed from the supplied data and may have been larger than the figures shown.

INTERPRETING THE THREE RISK PROFILES

0.4% LOWER CONFIGURED RISK

Historical return: +122.8%
Maximum closed-balance drawdown: 6.60%
Sharpe ratio: 2.46

This configuration produced the lowest historical volatility and drawdown of the three simulations. It also produced the highest Sharpe and Calmar ratios and the greatest proportion of positive months.

1.0% INTERMEDIATE CONFIGURED RISK

Historical return: +318.1%
Maximum closed-balance drawdown: 20.17%
Sharpe ratio: 2.02

This configuration produced materially higher historical growth with greater path volatility. Sharpe remained above 2.0 while maximum closed-balance drawdown increased to approximately 20.2%.

2.0% HIGHER CONFIGURED RISK

Historical return: +746.6%
Maximum closed-balance drawdown: 28.32%
Sharpe ratio: 1.90

This configuration produced the highest historical terminal balance and CAGR, but also the most volatile return path, the fewest positive months and the highest historical closed-balance drawdown.

LEVERAGE

All three historical simulations used the same 1:50 leverage.

The configured risk percentage determines the intended risk amount from account equity and stop-loss distance.

Leverage changes the margin required to support the resulting position. It does not directly scale the intended position size unless available margin becomes the limiting factor.

METRIC METHODOLOGY

Net P&L: derived from the source trade ledger after commissions and swap.

Monthly returns: realised month-end closed balance divided by the previous month-end closed balance.

Sharpe ratio: annualised from weekday closed-balance returns using 252 trading days and a 0% risk-free rate.

Sortino ratio: calculated using the same return series with downside deviation only.

Calmar ratio: CAGR divided by maximum percentage closed-balance drawdown.

Recovery factor: cumulative net profit divided by the largest absolute closed-balance drawdown in account currency.

IMPORTANT LIMITATIONS

  • Historical simulation: all results shown above are simulated using historical market data. Actual execution can differ because of spreads, slippage, liquidity, latency, outages, rejected orders, symbol specifications, broker rules and changing market structure.
  • No continuous equity series: risk metrics are derived from realised closed balance because the source files do not contain a continuous mark-to-market equity series. Floating drawdown may therefore exceed the historical closed-balance drawdown shown.
  • Risk setting is not a guaranteed loss cap: the configured percentage is an input to position sizing. Actual realised P&L can differ because of execution, additional entries, gaps, price movement, costs and trade management.
  • Leverage and margin: 1:50 leverage was held constant across the historical simulations. Leverage does not directly determine intended position size, but margin availability can become a constraint at larger position sizes.
  • Risk-adjusted ratios are methodology-dependent: Sharpe, Sortino and volatility use weekday closed-balance returns, a 252-day convention and a 0% risk-free rate. Different sampling methodologies or assumptions will produce different values.
  • Historical performance is not a guarantee of future performance.

WHO SYSTEM 1 MAY BE SUITABLE FOR

System 1 is intended for users who:

  • Want systematic XAUUSD trading
  • Prefer automated execution rather than discretionary entry decisions
  • Understand percentage-based position sizing
  • Want control over account risk without exposing proprietary strategy parameters
  • Understand that periods of drawdown and negative performance can occur
  • Understand the risks associated with leveraged trading

Users should confirm that their broker, trading account, leverage, symbol specification and available margin are technically suitable before live deployment.

Broker minimum-volume requirements may prevent exact risk sizing on very small accounts.

MORELAND ALGORITHMIC

Moreland Algorithmic is a UK-based trading technology company focused on the research and development of proprietary automated trading systems.

Our development process is centred on defined market logic, systematic execution, risk management, historical research, out-of-sample analysis and continued real-market validation.

Moreland System 1 has been developed as a structured automated trading system rather than as a collection of user-optimised indicators or discretionary settings.

CROSS-BROKER TESTING

The screenshots shown on this listing were intentionally produced using a different broker environment from the published Moreland System 1 research report.

The official September 2026 Historical Testing & Risk Analysis Report uses the FTMO historical environment as its fixed reference dataset. For this MQL5 listing, System 1 was subsequently re-tested using Pepperstone historical data with the same core strategy parameters and the same 0.4%, 1.0% and 2.0% risk configurations.

We chose to show the Pepperstone screenshots to provide an additional cross-broker comparison rather than simply reproducing screenshots from the same environment used for the original research.

The results remained closely aligned across the two environments. At 0.4% risk, both tests produced 1,704 closed transactions and a Profit Factor of 1.84. At 1.0% risk, both produced 1,646 transactions and a Profit Factor of 1.58. Maximum balance drawdown was also very similar across both environments.

At the higher 2.0% risk level, the difference became more noticeable, with the Pepperstone simulation ending at approximately 812,023 compared with 846,615 in the FTMO research simulation. This illustrates how relatively small differences in historical tick data, spreads, commissions, swap, execution prices, symbol specifications, volume rounding and margin conditions can become amplified through larger position sizes and compounding.

The September 2026 research report remains the official fixed historical reference for Moreland System 1. The Pepperstone screenshots are presented as supplementary cross-broker testing and are not intended to imply that identical results will occur across different brokers.

RISK DISCLOSURE

Trading leveraged financial instruments involves substantial risk and may result in the loss of some or all trading capital.

Historical performance, simulations, backtests and statistical measures do not predict or guarantee future results.

Moreland Algorithmic provides automated trading software and related product information. Nothing in this description constitutes personalised investment advice, a solicitation to invest or a guarantee of capital preservation.

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EA Trading Strategy Overview This strategy is designed with a focus on safety, consistency, and controlled growth , making it suitable for both beginners and long-term investors. This EA is designed to perform effectively in real market conditions . You are welcome to download the demo version and test it freely on a live market environment . If you encounter any issues or have questions during testing, please feel free to contact me directly for support .  https://www.mql5.com/en/messages/03
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