+1934.7%
Total Return
16.2%
Annual CAGR
6.9%
Max Drawdown
2.4×
Calmar Ratio
58.9%
Win Rate
0.504R
Expectancy
1.55:1
Reward:Risk
9.57
T-Statistic
This system demonstrates a statistically confirmed positive expectancy across 20.08 years of backtest data encompassing 1,068 closed positions on MULTI MIXED. The strategy achieves 1.55:1 reward-to-risk, operating 19.7 percentage points above its mathematical breakeven threshold of 39.2%. Annualised CAGR of 16.2% relative to 6.9% maximum drawdown yields a Calmar ratio of 2.4×, below the professional benchmark range of 3–5×. Monte Carlo validation across 2,000 block-bootstrap simulations confirms structural consistency under adverse trade sequencing. 19 of 19 validation tests pass. All tests clear the 70-point validation threshold.
Section I
Analytical Findings & Observations
F.1
Statistical Significance Strength
The strongest dimension is Stat Significance (100/100). T-statistic of 9.57 exceeds the 99% two-tailed significance threshold of 2.576. (p = 0) Probability of results arising by chance is below 0.1%. The edge is statistically real given this 1059-trade sample. This test applies a Welch t-test on the profit distribution and requires the mean return to be significantly different from zero.
F.2
Tail Risk Elevation Finding
CVaR (95%) measures 2.44× the average loss — within acceptable range. The worst 53 trades (5% of sample) average $884.37 against a $362.79 mean loss. CVaR 99%: 2.95× average loss. Tail risk level: MODERATE. This elevation is partially structural: with a 1.55× RR ratio, the absolute average loss is modest, making tail events appear proportionally larger in ratio terms. Active monitoring of worst-case trade magnitude under live conditions is advisable.
F.3
MC Drawdown Envelope Observation
Block-bootstrap Monte Carlo (2,000 simulations, block size 15, AC lag-1: 0.083) produces a 95th-percentile maximum drawdown of 38.8% — approximately 5.6× the historical 6.9%. P50: 16.1%, P99: 54.6%. The historical sequence sits at the 2th percentile of the simulated distribution, confirming results were not predicated on an unusually favourable trade ordering. Risk management sizing against the MC P95 envelope rather than historical DD is advisable for live deployment.
F.4
Execution Sensitivity Observation
Under 10% execution degradation (wider spreads, adverse fills), expectancy retains 0.74× of its backtest level. At 0.504R base expectancy, the strategy remains profitable under this stress test. Forward testing under broker-accurate spread conditions is standard practice before capital deployment.
Development Considerations
Areas for Further Development
Capital Efficiency
Capital Efficiency scored 70/100. CAGR of 16.2% with a 6.9% max DD yields a Calmar of 2.4×. The risk management is sound but absolute returns are modest relative to the strategy's risk capacity. The primary lever is trade frequency — at 4.4 trades/month, even small improvements to entry filter selectivity compound materially over time. Review whether there are recurring low-quality setups that could be filtered out to improve average expectancy per trade.
Monte Carlo Robustness
MC Robustness scored 72/100. Block-bootstrap CV of 0.124 indicates moderate sequence dependency. MC P95 DD of 38.8% vs historical 6.9% (5.6× expansion). Position sizing should be calibrated against the MC P95 envelope, not the historical DD. At 1% risk per trade, the P95 scenario implies up to 39.0% account drawdown — ensure capital allocation accounts for this rather than the 6.9% historical figure.
Tail Risk Reduction
Expected Shortfall scored 72/100. The worst 53 trades (5% of sample) average $884.37 against a $362.79 mean loss — a 2.4× ratio. CVaR 99% is 3.0×. Examine whether these outlier losses share a common trigger: specific session, news window, or spread spike. Adding a maximum per-trade loss cap at 2× average loss would eliminate the tail without affecting the remaining 95% of trades.
Section II
Validation Test Results
97
Temporal
100
Statistical
90
Drawdown
70
Capital
96
Edge
95
Edge
86
Concentration
100
Ulcer
99
Sample
94
Return
91
MC
89
Consecutive
99
Cliff
72
MC
85
DD
94
Execution
97
Holding
82
Edge
72
Expected
Temporal Stability
97
EXCELLENT — All 10 periods profitable
All 10 of 10 equal calendar periods generated positive returns across the backtest horizon. No losing period detected. Return consistency CV of 0.71 confirms profitability is spread evenly, not concentrated in a single regime window. This score measures temporal robustness — a strategy that only profits in one or two periods may be regime-dependent rather than exhibiting a repeatable edge.
Statistical Significance
100
Highly significant edge (t=9.57, 99% confidence)
T-statistic of 9.57 exceeds the 99% two-tailed significance threshold of 2.576. (p = 0) Probability of results arising by chance is below 0.1%. The edge is statistically real given this 1059-trade sample. This test applies a Welch t-test on the profit distribution and requires the mean return to be significantly different from zero.
Drawdown Analysis
90
MINIMAL drawdown (6.9% max, 1.6% avg episode)
Maximum drawdown of 6.9% with an average episode depth of 1.6%. The median recovery speed is 5.8 days per 1% of drawdown. 133 drawdown episodes were detected. No single episode dominates the overall drawdown profile, indicating consistent rather than event-driven risk. This test scores three components: max DD depth (50%), average episode depth (30%), and recovery quality in days per 1% of DD (20%).
Capital Efficiency
70
FAIR — 16.2% annual, Calmar 2.4
Compound annual growth rate of 16.2% against 6.9% maximum drawdown. Calmar ratio of 2.4× falls below the professional benchmark of 3–5×. CAGR is computed using true compound growth (end equity / start equity)^(1/20.08 years), not simple annualisation. Capital efficiency rewards strategies that generate high risk-adjusted returns relative to their worst historical loss.
Edge Temporal Decay
96
STABLE — Edge is consistent with no meaningful decay
Rolling expectancy regression slope is positive (normalised +1.36), indicating the edge has strengthened over the backtest horizon. Second-half expectancy exceeds first-half by 141% (ratio 2.41). Profit factor across four quartiles (2.174, 2.077, 2.526, 2.14) is approximately stable (normalised slope 0.05). This test detects whether a strategy's edge is eroding over time — a critical check for curve-fitted systems that perform well historically but deteriorate as market conditions evolve.
Edge Consistency
95
EXCELLENT — Edge performs consistently across all conditions
Win rate variance across weekdays falls within acceptable bounds. No structurally unprofitable weekday detected. Profit factor log-variance of 0.1494 and day-of-week variance of 7.4237 indicate edge quality does not fluctuate meaningfully by session day. This test checks whether the strategy's edge is consistent across all trading sessions or is heavily dependent on specific days or conditions.
Concentration Risk
86
EXCELLENT — Well distributed
Top 10% of winning trades account for 29.7% of total profit — well within the 30% ideal-diversification threshold. The largest single winner represents 0.7% of total profit, confirming no individual trade disproportionately sustains the overall result. Profit distribution is scored on two components: top-decile share (80%) and single largest winner share (20%). A well-distributed profit profile indicates genuine repeatable edge rather than lottery-dependent returns.
Ulcer Index
100
Excellent drawdown profile (UI: 1.4%)
Ulcer Index of 1.4% represents minimal cumulative drawdown pain. Max DD: 6.9%, avg DD: 0.89%, time underwater: 50.6%. Unlike maximum drawdown which captures a single worst point, the Ulcer Index integrates both depth and duration of all underwater periods — a UI below 5% indicates drawdowns are shallow, brief, and recover quickly.
Sample Adequacy
99
EXCELLENT — 1068 trades over 20.1y exceeds requirements
1068 trades over 20.1 years exceeds the academic minimum of 125 trades. MinTRL (minimum track record length) statistic: 30. Confidence factor applied to all other tests: 1. Sample adequacy is the foundational test — a backtest with insufficient trades cannot produce statistically valid conclusions regardless of how impressive the individual metrics appear.
Return Autocorrelation
94
Returns are independent (AC: 0.081)
Lag-1 autocorrelation of 0.081 (lag-2: 0.049) — no meaningful serial dependence. Ljung-Box Q-statistic (12.29) reaches statistical significance at short lags, though the AC magnitude (0.081) is too small to have practical trading significance. Returns are effectively independent. No martingale signature or hidden clustering pattern detected. Significant autocorrelation can indicate position-sizing escalation or regime-dependent behaviour that inflates backtest results.
MC DD Stability
91
EXCELLENT — Highly stable under randomization
Under 1,000 permutation shuffles of the exact trade sequence, the 95th-percentile maximum drawdown reaches 10.1% — a 1.5× expansion from the 6.9% historical figure. 99th percentile: 11.6%. A ratio below 2.0× confirms the strategy does not rely on a particularly favourable trade ordering. This test measures whether the backtest drawdown is structurally representative or a statistical artefact of a lucky sequence of trades.
Consecutive Loss
89
MINIMAL — Statistically normal streak behavior
Maximum consecutive losing streak of 7 trades against a statistically expected maximum of 7.9 (ratio 0.88×). Loss clustering ratio of 0.97 — losses are not grouping more frequently than random distribution predicts. Worst streak required approximately 14 average wins to fully recover (damage ratio 7.6×). This test checks four dimensions: observed vs expected streak length (30%), loss clustering (25%), worst streak damage (25%), and recovery speed (20%).
Cliff Ratio
99
EXCELLENT — Healthy risk profile
95th-percentile loss of $943.79 is 1.68× the average win of $562.95 — a healthy ratio indicating tail losses are not catastrophically larger than typical wins. Average loss: $362.79. Single largest loss ($1121) is 1.19× above the P95 level — no structural outlier. This test uses the 95th-percentile loss rather than the single largest loss as the primary metric, making the score more robust to one-off broker anomalies while still flagging structural outliers separately.
MC Robustness
72
FAIR — Sequence-independent results confirmed
Block-bootstrap Monte Carlo (2,000 simulations, block size 15 preserving serial structure, AC lag-1: 0.083) produces a survival rate of 100.0% across all simulations. Coefficient of variation: 0.124. MC DD envelope — P50: 16.1%, P95: 38.8%. No position-scaling pattern detected — the strategy applies approximately uniform lot sizing regardless of recent outcomes. Block bootstrap preserves the serial correlation structure of returns (unlike naive IID resampling), producing more realistic stress scenarios.
DD Endurance
85
RESILIENT (1.0x penance, 47% underwater)
Median penance ratio of 1.01× substantially outperforms the theoretical IID expectation of 3.0× (Bailey & López de Prado, 2014). A ratio below 1.0 means recovery consistently takes less time than the drawdown formation period — a strong signal of genuine edge. Time spent underwater: 47.4%. Longest DD episode: 281d 5h 17m (3.8% of backtest). Longest recovery: 247d 21h 0m. 133 episodes detected. Scored on four components: penance ratio (35%), longest DD as % of backtest (25%), % time underwater (25%), and recovery consistency CV (15%).
Execution Cost Sensitivity
94
GOOD — Edge moderately affected by degradation
Under a 10% uniform execution degradation scenario (wins reduced 10%, losses increased 10%), per-trade expectancy retains 0.74× of its backtest level. Original expectancy: $181.15 → degraded: $133.48 (26.3% impact). Strategy remains profitable under this stress test. At 0.504R base expectancy, the strategy retains meaningful cushion against real-world execution costs.
Holding Time
97
EXCELLENT — Winners held 1.6x longer than losers
Winners are held 1.59× longer than losers on average (winners: 140.2h, losers: 88.4h). This is a positive pattern — the strategy allows profitable trades to run while cutting losses relatively quickly. Discipline tier: EXCELLENT. Median ratio: 0.57×. At the current 0.504R expectancy, this does not materially impact performance.
Edge Quality
82
GOOD — Strong statistical edge
Expectancy of 0.504R per trade reflects a genuine and strong edge. Win rate of 58.9% operates 19.7 percentage points above the mathematical breakeven of 39.2%. Largest win is 4.48× the average win — some concentration in large outlier wins. Edge quality is scored on four dimensions: expectancy (35%), repeatability (30%), win rate margin (15%), and execution decay (20%).
Expected Shortfall
72
FAIR — Moderate tail risk present (ES ratio: 2.4x avg loss)
CVaR (95%) measures 2.44× the average loss — within acceptable range. The worst 53 trades (5% of sample) average $884.37 against a $362.79 mean loss. CVaR 99%: 2.95× average loss. Tail risk level: MODERATE. This elevation is partially structural: with a 1.55× RR ratio, the absolute average loss is modest, making tail events appear proportionally larger in ratio terms. Active monitoring of worst-case trade magnitude under live conditions is advisable.
Section III
Portfolio Composition
This report evaluates a combined portfolio of the following constituent backtests. All validation metrics above are computed on the combined, chronologically-merged trade stream.
| # | Strategy | Symbol | Timeframe | Trades |
|---|---|---|---|---|
| 1 | Powerful Price Action EA AI 70.0 | USDJPY | H4 | 315 |
| 2 | Powerful Price Action EA AI 70.0 | USDCHF | H4 | 146 |
| 3 | Powerful Price Action EA AI 70.0 | USDCAD | H4 | 205 |
| 4 | Powerful Price Action EA AI 70.0 | GBPUSD | H4 | 188 |
| 5 | Powerful Price Action EA AI 70.0 | EURUSD | H4 | 205 |
| Total · 5 strategies | 1,059 |