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Optimization Analysis

Period Recommendation Report

June 03, 2026

OPT-20260603-003942

Advanced Index Trader Pro

USTEC • H1

1,001 trades

2,443 days (6.7 years) analyzed

MT5 Report

01 Equity Projection 1,000 simulations · 470 trades forward · ~36.5 months

MONTE CARLO EQUITY PROJECTION — Advanced Index Trader Pro Starting: $45,145.93

Historical equity

Simulation paths

Median (+96.9%)

Best case ($182,622)

Worst path (−29.4% DD)

5TH PCT

$62,662

+38.8%

25TH PCT

$78,023

+72.8%

MEDIAN

$88,905

+96.9%

75TH PCT

$101,196

+124.2%

95TH PCT

$124,575

+175.9%

95% DD CONFIDENCE

−17.2%

Worst DD in 95% of simulated paths

AVG RECOVERY

10 trades

Mean trades to recover from a DD episode

EST. DURATION

~36.5 mo

At current trade frequency (2.3 days/trade)

SIMULATIONS

1,000

Percentage-based resampling (exact method)

STATISTICAL OBSERVATIONS

DISTRIBUTION SHAPE

The outcome distribution is right-skewed — the upside range ($62,662–$124,575) spans $61,913. Adverse scenarios are bounded closer to the starting balance than favourable ones.

DRAWDOWN PROFILE

The 95% confidence drawdown of −17.2% 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 2.3 days per trade, the 470-trade projection spans approximately 36.5 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

1373 days

3.8 years

Statistical + Academic + Bootstrap

What This Means

Based on analysis of your strategy's characteristics on USTEC H1 trading systems, we recommend using 1,373 days (3.8 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 (776 days (2.1 years)), literature-informed period benchmarks (2,737 days (7.5 years)), and Politis-Romano block bootstrap spectral analysis (606 days (1.7 years)).

02Analysis Metrics

Statistical Period

776 days (2.1 years)

Academic Period

2,737 days (7.5 years)

Bootstrap Period

606 days (1.7 years)

Sharpe Ratio

2.29

Max Drawdown

-13.6%

Recovery Factor

12.5

Volatility Ratio

0.69x

Confidence Level

MEDIUM

Re-opt Frequency

Semi-annual ↓ (low vol)

Regime Changes

Profit Factor

1.53

Win Rate

63.5%

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 found	776 days (2.1 years)
Regime changes detected	8
Volatility adjustment	0.69× current/historical

📚 Literature Benchmarks

Period benchmarks for USTEC H1 strategies, informed by asset class volatility profiles and FX market microstructure research. These are calibrated heuristics, not direct citations.

Base period (USTEC H1)	2,737 days (7.5 years)
Volatility adjustment	↓ low vol
Adjusted period	2,737 days (7.5 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 period	606 days (1.7 years)
Method	Politis-Romano stationary bootstrap
Combined (all three)	1,373 days (3.8 years)

04Why This Period Works

Interpreting the Optimal Range

Too short (under 892 days (2.4 years)): Not enough data to capture full market cycles. Results are statistically unreliable and prone to overfitting to a single regime.

Above range (over 1,990 days (5.4 years)): The window extends beyond the calculated optimal range. Older data points contribute proportionally less signal in recent-regime models.

The sweet spot (892 days (2.4 years) – 1,990 days (5.4 years) for USTEC H1): Provides enough trades for statistical confidence while focusing on recent, relevant market conditions.

The three-method synthesis gives 1,373 days (3.8 years) — averaged from rolling-variance statistical analysis (776 days (2.1 years)), literature-informed period benchmarks (2,737 days (7.5 years)), and Politis-Romano block bootstrap spectral analysis (606 days (1.7 years)).

05Your Backtest Period Diagnostic

◉

Period Assessment

ABOVE RANGE

The backtest window is moderately longer than the calculated optimal range.

Period Coverage

178%

2,443 days (6.7 years) of 1,373 days (3.8 years) optimal

Trade Coverage

500%

1,001 of 200 estimated minimum

Detailed Findings

Backtest window above calculated range — 2,443 days (6.7 years) vs 1,373 days (3.8 years) optimal

The backtest window differs from the calculated optimal by 1,070 days (2.9 years).

⚠️ 8 Regime Changes Detected

Multiple structural shifts detected in the analysis window. Consider walk-forward analysis to confirm parameter robustness across different regimes.

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 Type	Days	Use Case
Minimum Acceptable	892 days (2.4 years)	Quick tests, high-frequency strategies
Recommended	1,373 days (3.8 years)	Calculated optimal — three-method average
Maximum Useful	1,990 days (5.4 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 1,373 days (3.8 years) window keeps strategy parameters aligned with current market conditions.

REGIME CHANGES DETECTED

8

Multiple shifts — walk-forward testing advised

VOLATILITY REGIME

0.69×

Low vol — extend lookback

08How to Apply These Results

💡 Practical Recommendations

Set Your Backtest Period

When running backtests, use approximately 1,373 days (3.8 years) of historical data. This gives enough trades for statistical validity while focusing on current market conditions.

Re-optimise Semi-annual ↓ (low vol)

Markets change over time. Re-run optimisation semi-annual ↓ (low vol) using the most recent 1,373 days (3.8 years) window to ensure parameters stay relevant to current market conditions.

Use Walk-Forward Testing

For robust validation: optimise on 1,373 days (3.8 years), test on the next 453 days (1.2 years), then roll forward and repeat. This prevents overfitting and validates parameter stability across time.

Use 95% DD (17.2%) as Your Risk Budget

Monte Carlo simulation projects that in the worst 5% of scenarios, maximum drawdown reaches 17.2%. Size your position so this drawdown is within your risk tolerance before allocating capital.