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Phase 6 is a genuinely orthogonal mechanism — liquidity/imbalance geometry rather than the volatility-momentum family — so it's worth a clean test. Before results, one methodological caveat I must state plainly: this strategy carries a large number of discretionary geometric rules (peak-prominence threshold, block-boundary definition, which node is target vs protective, FVG proximity, buffers). Each is a free parameter, which makes it the most overfitting-prone design we have built, and this is now the sixth distinct hypothesis on the same data, so project-level multiple testing is severe. I will therefore fix all parameters a priori, run once with no tuning, and stress-test any positive result on the fresh names.
Let me implement the engine (order blocks, FVG detection, block-to-block execution) with strict no-look-ahead.Analyzing catastrophic Phase 6 trading results and metricsAnalyzing catastrophic Phase 6 trading results and metricsA missing import in the appended code. Quick fix.Diagnosed trading strategy failure through reward-to-risk analysisDiagnosed trading strategy failure through reward-to-risk analysisThe results are decisive and, importantly, fail for the precise opposite of the intended reason. Let me quantify the mechanism before reporting, because the diagnosis matters more than the headline.Ran 2 commandsRan 2 commandsThe strategy is implemented, validated, and run on the full basket at both M30 and H1 with the same 0.18% round-trip costs. The direct answer is no — and the way it fails is the instructive part, because it fails for the exact opposite of the reason you expected.
Results
N tradesNetMaxDDPFWinM30, all 57,296−92.6%−92.6%0.5852.8%M30, fresh 45,899−94.0%−94.0%0.5552.2%H1, all 53,827−66.2%−66.3%0.6655.8%H1, fresh 43,177−69.4%−69.4%0.6555.2%
Every ticker is deeply negative on both timeframes, the pooled t-statistic is around −14 (M30) and −9 (H1), and the fresh-only result is no better than the all-five result. SMLT is no longer even a flattering outlier here. This is not a borderline case requiring deflation for multiple testing; it is an unambiguous, statistically overwhelming loss.
Why it fails — the wide stop inverted the reward-to-risk
The notable detail is that the win rate is above 50% (52–56%), and on M30 there are far more take-profit exits than stop exits (4,682 TP versus 2,611 SL). The strategy is right more often than it is wrong, yet it loses catastrophically. The diagnostic explains it: on the fresh names the average win is +15.1 against an average loss of −29.8, a realized reward-to-risk ratio of 0.51. Each winner is worth roughly half a loser.
This is a direct consequence of the geometry you specified. The protective block sits below the imbalance and the stop is placed below that block, so the risk leg (entry to stop) is wide. The target is the POC of the opposite node, which on average sits much closer to the entry than the protective block does. The result is a structure where you routinely risk a large amount to capture a small one. A 52% win rate at a 0.51 reward-to-risk ratio is a mathematically guaranteed loser before costs even enter, and the strategy fires roughly 1,474 times per name over four and a half years, so the 0.18% round trip then compounds the damage.
In other words, the premise — "wide stops behind blocks mean transaction costs stop dominating" — is correct about costs but introduces a worse problem. Widening the stop without a correspondingly distant target does not protect expectancy; it destroys the payoff ratio. Phase 5 failed because the POC stop was too tight (whipsaw); Phase 6 fails because the block stop is too wide relative to its target. Neither tight nor wide stops rescue the underlying signal, which is the more fundamental point.
Synthesis across the full investigation
We have now tested this family from six structurally distinct angles, and each failed for its own clear, mechanistic reason rather than for a single repeated flaw:
The M5 directional system died from transaction costs against a coin-flip direction. The M15 swing version regressed to a pooled profit factor near 1.1 with no significance. The three-predictor directional engine left the hit-rate at roughly 49% and its apparent significance was carried entirely by the contaminated SMLT. The raw forward-return study established that the breakout direction is statistically indistinguishable from noise and that only the volatility-expansion fact is real. The non-directional breakout box converted that volatility fact into a 28% win rate, which is exactly the gross break-even for a 2.5:1 payoff, so costs pushed it negative. And the block-to-block imbalance strategy, despite a genuinely orthogonal premise, produced a 0.51 reward-to-risk ratio and lost decisively.
The honest conclusion is that the volume-profile and order-block family, as a source of tradeable directional or volatility expectancy on liquid MOEX equities net of realistic costs, is now comprehensively closed. The one verified asset — that AVVM detects elevated future absolute movement — is real but modest, and we have demonstrated that no stop-based equity execution we have tried can monetize it. The only framework in which a known volatility-expansion premium is paid directly is options, where the question becomes whether realized volatility after a compression signal exceeds the implied volatility priced into the straddle. That requires options and implied-volatility data, a different cost model, and is a separate project that this sandbox cannot source.
What remains durable is the harness itself: a leak-free pipeline, walk-forward and multi-ticker pooling, overlap-corrected bootstrap and forward-prediction testing, and now three distinct execution engines. It has done its job repeatedly, which is to reach a defensible verdict cheaply before any capital is risked. If you wish to bring an orthogonal, non-price-derived predictor — order-flow imbalance, options skew, or a cross-asset signal — or to pivot the volatility finding toward an options framework, the infrastructure is ready to evaluate it with the same discipline. My recommendation, stated plainly, is not to attempt a seventh variation of price-and-volume geometry; the accumulated evidence against an edge in that family is now strong enough that further iteration would more likely manufacture an overfit artifact than discover a real signal.