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VALIDATION REPORT · XAUUSD · BLACKSYSTEM v3.0

Five years, eight months, out-of-sample.

This page publishes the validation of Black System over January 2021 – August 2026: methodology, results, Monte Carlo, robustness checks — and the limits. The same document every buyer receives, in the open.

BACKTEST 2021-01-04 → 2026-08-28 · REAL TICKS (72%) · 100,000 USD DEPOSIT · COMMISSIONS, SWAPS AND 100 MS EXECUTION DELAY INCLUDED · SIMULATED RESULTS
+521%
total return · CAGR 38%
-10.0%
max equity DD, floating incl.
1.92
profit factor · 9,738 trades
6/6
profitable years
3.19
sharpe (daily, annualised)
52/68
positive months
69%
win rate
13.3%
monte carlo 95th pct DD

What was tested, and how honestly

Black System is a four-module systematic portfolio on XAUUSD: a swing breakout engine (R), a slow trend-follower with volatility targeting (T), and two mean-reversion grids confined to dedicated capital pockets (Q, Z). The test period contains four distinct regimes: the 2021 post-peak consolidation, the 2022 bear market under Fed tightening, the 2023 range, and the 2024–26 rally.

Out-of-sample by construction. Module defaults were fixed on 2025–26 data; 2021–2024 was never seen by the system before this run. Parameters stay at their original or research-canonical values — the only parameter changed during development (the trend-follower lookback) was selected on a robustness comparison across three settings, all profitable. Costs are fully included: 19,089 USD of commissions, 31,751 USD of swaps, 100 ms execution delay with slippage emulation.

Year by year — four regimes

YearRegimeReturnRTQZ
2021Post-peak consolidation+20.3%+27,420-10,418+2,087+1,209
2022Bear market, Fed hiking+11.0%+5,292+5,973+320+1,606
2023Range, then Q4 breakout+37.7%+47,044-3,478+5,604+1,177
2024Trend resumes+29.7%+31,284+9,421+11,824+2,155
2025Strong rally+59.5%+70,641+34,711+28,352+8,278
2026Rally + volatility (8 mo)+63.3%+146,059+17,217+61,115+16,310
Total100,000 → 621,200 USD+521%+327,740+53,427+109,301+30,733

Returns on balance with compounding. 2022 is the test that matters: gold fell ~20% peak-to-trough while rates rose — R stays positive, T is short and profitable, the grids survive. T loses in the two range years (2021, 2023): the expected cost of a trend-follower, and the reason it's in the portfolio.

The four modules over 68 months

ModuleNet USDTradesWinPFMax DDYears +
R · Swing breakout+327,7405,13863%1.72-19,9916/6
T · Time-series momentum+53,42716756%2.22-17,8384/6
Q · Grid mean reversion+109,3013,77376%3.30-6,1246/6
Z · Prior-day levels+30,73366081%2.70-9,1986/6
Portfolio+521,2009,73869%1.92-17,1686/6

T is close to uncorrelated with everything (R–T monthly correlation 0.12): it is the portfolio's second leg, losing in ranges and paying in the bear year. R and Q are correlated (0.77) and treated as one risk block; budgets are set accordingly.

Drawdown, exactly

The binding figure is the relative equity drawdown of 10.04% — measured on the equity curve including floating P&L, peak to trough. It happened once in 68 months. Closed-trade (balance) drawdown peaked at 7.45%. The portfolio's hard limit is set exactly at 10%: on this history it would have been touched once.

Monte Carlo — 5,000 resampled paths

Method: block bootstrap (blocks of 20, preserving short-term dependence) with 10% of trades randomly skipped to mimic missed executions.

What was discarded

A module is admitted only if its thesis has support in the academic literature and it passes a criterion declared before testing (profit factor ≥ 1.2 in each year with one parameter set). Three strategies failed and were removed during development: an RSI recovery grid, a session breakout with too few trades, and a jump-detection module that proved a coin-flip in five configurations. We publish this because a portfolio is defined as much by what was cut as by what stayed.

Limits of this study — read before buying

Research foundation

Moskowitz, Ooi & Pedersen (2012), Time Series Momentum, JFE · Hurst, Ooi & Pedersen (2017), A Century of Evidence on Trend-Following · Moreira & Muir (2017), Volatility-Managed Portfolios, JoF · Corsi (2009), HAR-RV · Grossman & Zhou (1993), drawdown control · Crabel (1990), opening range breakout · Zarattini, Barbon & Aziz (2024), SFI · Leung & Li (2015), optimal mean reversion · Kaminski & Lo (2014), stop-loss rules · Bailey, Borwein, López de Prado & Zhu (2014), Probability of Backtest Overfitting · López de Prado (2018), Advances in Financial Machine Learning · Harvey, Liu & Zhu (2016), RFS.

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