Optimization Analysis

Period Recommendation Report
June 04, 2026
OPT-20260604-030913
Spectrum Trend Pro EA
XAUUSD • H4
320 trades
1,247 days (3.4 years) analyzed
MT5 Report
01 Equity Projection 1,000 simulations · 187 trades forward · ~24.4 months
MONTE CARLO EQUITY PROJECTION — Spectrum Trend Pro EA Starting: $20,466.04
Historical equity
Simulation paths
Median (+118.2%)
Best case ($172,729)
Worst path (−46.4% DD)
5TH PCT
$24,234
+18.4%
25TH PCT
$34,922
+70.6%
MEDIAN
$44,648
+118.2%
75TH PCT
$59,578
+191.1%
95TH PCT
$91,493
+347.0%
95% DD CONFIDENCE
−31.2%
Worst DD in 95% of simulated paths
AVG RECOVERY
11 trades
Mean trades to recover from a DD episode
EST. DURATION
~24.4 mo
At current trade frequency (3.9 days/trade)
SIMULATIONS
1,000
Percentage-based resampling (exact method)
STATISTICAL OBSERVATIONS
DISTRIBUTION SHAPE
The outcome distribution is right-skewed — the upside range ($24,234–$91,493) spans $67,259. Adverse scenarios are bounded closer to the starting balance than favourable ones.
DRAWDOWN PROFILE
The 95% confidence drawdown of −31.2% is the stress-test reference — the worst expected drawdown in 19 out of 20 simulated scenarios. The median path experiences materially lower drawdowns.
TRADE FREQUENCY CONTEXT
At 3.9 days per trade, the 187-trade projection spans approximately 24.4 months. Actual duration varies with market conditions — lower-frequency periods extend the timeline without changing the statistical distribution.
RESAMPLING METHOD
Simulations use percentage-based resampling of historical trade returns. This preserves the return distribution but assumes trade independence. Structural regime changes may produce outcomes outside the simulated range.
Statistical context: Monte Carlo projections are probabilistic estimates based on historical trade return distributions. They do not predict future outcomes. Results should be interpreted as a statistical characterisation of the strategy's historical behaviour under resampling, not a forecast. Past simulation results are not indicative of future performance.
BACKTEST WINDOW ANALYSIS
Recommended Period
1484 days
4.1 years
Statistical + Academic + Bootstrap

What This Means

Based on analysis of your strategy's characteristics on XAUUSD H4 trading systems, we recommend using 1,484 days (4.1 years) of historical data for optimization and backtesting.

This period balances having enough data for statistical significance while avoiding outdated market conditions. The recommendation is synthesised from three independent methods: rolling-variance statistical analysis (409 days (1.1 years)), literature-informed period benchmarks (3,421 days (9.4 years)), and Politis-Romano block bootstrap spectral analysis (623 days (1.7 years)).

02Analysis Metrics
Statistical Period
409 days (1.1 years)
Academic Period
3,421 days (9.4 years)
Bootstrap Period
623 days (1.7 years)
Sharpe Ratio
2.61
Max Drawdown
-22.8%
Recovery Factor
8.7
Volatility Ratio
0.49x
Confidence Level
HIGH
Re-opt Frequency
Semi-annual ↓ (low vol)
Regime Changes
2
Profit Factor
1.69
Win Rate
65.9%
03Three-Method Synthesis

📈 Statistical Analysis

Rolling-variance stability test finds the lookback window where your strategy's return distribution is most stable and least regime-dependent.

Optimal period found409 days (1.1 years)
Regime changes detected2
Volatility adjustment0.49× current/historical

📚 Literature Benchmarks

Period benchmarks for XAUUSD H4 strategies, informed by asset class volatility profiles and FX market microstructure research. These are calibrated heuristics, not direct citations.

Base period (XAUUSD H4)3,421 days (9.4 years)
Volatility adjustment↓ low vol
Adjusted period3,421 days (9.4 years)

🔬 Block Bootstrap — Politis-Romano (1994)

Spectral autocorrelation analysis estimates the memory structure in your returns using block resampling. Accounts for serial dependence that rolling-variance methods miss.

Bootstrap spectral period623 days (1.7 years)
MethodPolitis-Romano stationary bootstrap
Combined (all three)1,484 days (4.1 years)
04Why This Period Works

Interpreting the Optimal Range

Too short (under 964 days (2.6 years)): Not enough data to capture full market cycles. Results are statistically unreliable and prone to overfitting to a single regime.

Above range (over 2,151 days (5.9 years)): The window extends beyond the calculated optimal range. Older data points contribute proportionally less signal in recent-regime models.

The sweet spot (964 days (2.6 years) – 2,151 days (5.9 years) for XAUUSD H4): Provides enough trades for statistical confidence while focusing on recent, relevant market conditions.

The three-method synthesis gives 1,484 days (4.1 years) — averaged from rolling-variance statistical analysis (409 days (1.1 years)), literature-informed period benchmarks (3,421 days (9.4 years)), and Politis-Romano block bootstrap spectral analysis (623 days (1.7 years)).
05Your Backtest Period Diagnostic
◉
Period Assessment
WITHIN RANGE
The backtest window falls within the calculated optimal range.
Period Coverage
84%
1,247 days (3.4 years) of 1,484 days (4.1 years) optimal
Trade Coverage
256%
320 of 125 estimated minimum
Detailed Findings
✅ 2 Regime Changes Detected — Low structural risk
Minimal regime shifts in the analysis window indicate parameter stability. The strategy has operated in a consistent market environment.
References

Bailey, D. et al. (2014) "The Deflated Sharpe Ratio" — Minimum track record length, multiple testing correction
López de Prado, M. (2014) "The Deflated Sharpe Ratio" — MinTRL formula, Sharpe standard error at finite samples
Politis, D. & Romano, J. (1994) "The Stationary Bootstrap" — Block resampling for serially dependent data
Pardo, R. (2008) "The Evaluation and Optimization of Trading Strategies" — Walk-forward, regime-based optimization

06Acceptable Period Ranges
Range TypeDaysUse Case
Minimum Acceptable964 days (2.6 years)Quick tests, high-frequency strategies
Recommended1,484 days (4.1 years)Calculated optimal — three-method average
Maximum Useful2,151 days (5.9 years)Conservative analysis, lower-frequency strategies
07 Re-optimisation Frequency
Recommended
Semi-annual ↓
(low vol avg)
Derived from optimal period
The re-optimisation frequency is derived from the recommended period and your timeframe's typical regime change rate. Re-running optimisation semi-annual ↓ using a rolling 1,484 days (4.1 years) window keeps strategy parameters aligned with current market conditions.
REGIME CHANGES DETECTED
2
Low structural risk — stable parameters
VOLATILITY REGIME
0.49×
Low vol — extend lookback
08How to Apply These Results

💡 Practical Recommendations

1
Set Your Backtest Period
When running backtests, use approximately 1,484 days (4.1 years) of historical data. This gives enough trades for statistical validity while focusing on current market conditions.
2
Re-optimise Semi-annual ↓ (low vol)
Markets change over time. Re-run optimisation semi-annual ↓ (low vol) using the most recent 1,484 days (4.1 years) window to ensure parameters stay relevant to current market conditions.
3
Use Walk-Forward Testing
For robust validation: optimise on 1,484 days (4.1 years), test on the next 489 days (1.3 years), then roll forward and repeat. This prevents overfitting and validates parameter stability across time.
4
Use 95% DD (31.2%) as Your Risk Budget
Monte Carlo simulation projects that in the worst 5% of scenarios, maximum drawdown reaches 31.2%. Size your position so this drawdown is within your risk tolerance before allocating capital.