output/luxalgo-buyer-assets/pinescripts/power-hour-prior-sweep.lux.pine
Tier B funded/eval research
Power Hour Prior Sweep
A 1-minute power-hour prior-day-low sweep reclaim model with strong funded-mode survival and solid evaluation pass behavior.
Trades860.57 per week
Win rate62.8%10k validated
Target RR1.0Rdefault model
Expectancy+0.226Rper trade
Profit factor1.60gross wins / losses
Max DD4.75Rhistorical path
Eval pass91.5%10,000 paths
Eval fail8.5%trailing/DD fail
Median pass26 daysp25 18 / p75 37
Funded payout100.0%modeled eligibility
Historical Equity Curveclosed-trade R path
Exact operating profile
Entry, stop, target, and governor logic
The public page shows the research-grade operating shape. Source code, alert wiring, and platform-specific automation files remain private until unlock.
| Item | Validated rule | Execution note |
|---|---|---|
| Chart | 1-minute execution chart | The validated candidate is a 1-minute power-hour model. |
| Market | MES/MNQ micro futures | Micro sizing first because sweeps can slip around prior-day levels. |
| Direction | Long only | The validated candidate is a prior-day-low reclaim, not a short model. |
| Session | Power hour | The edge is concentrated late in RTH. Do not move it to the open without retesting. |
| Setup | Sweep below prior day low, then close back above it | This is a failed breakdown / liquidity sweep reclaim. |
| Trend filter | Price must be above EMA200 | Keeps the reclaim aligned with broader trend context. |
| RSI filter | RSI below 52 at signal | Avoids chasing after full momentum recovery. |
| Entry | Closed-bar signal, next-bar/market style entry in the approximation | Backtest used next-bar replay execution. |
| Stop | Max of structure risk and 1.0 ATR, with minimum-risk floor | Stop is attached immediately. No averaging down. |
| Target | Fixed 1.0R target | Bracketed target. |
| Time exit | 12 bars on the validated 1-minute model | Exit if neither stop nor target resolves inside horizon. |
| Governor | Funded add-on or patient evaluation module | Frequency is low, so it should not be the only fast-pass engine. |
Fast-pass governor frontier
Speed versus survival settings
These rows keep the same signal logic and only change risk dollars plus daily lockouts. Faster pass settings raise drawdown failure risk, so they belong in demo first.
| Mode | Risk | Daily stop | Daily lock | Pass | Fail | Median | P75 | Avg DD |
|---|---|---|---|---|---|---|---|---|
| Governor optimizer pending for this strategy. | ||||||||
TradingView package
PineScript approximation staged privately.
This is a market-structure sweep reclaim package. It is slower than Speed Pass, but the prop/funded survival math is cleaner than most high-frequency candidates.
Buy arrows, stop line, target line, session controls, and alert conditions are included in the staged script.
The script is private buyer/testing code and has not been published to the TradingView public library.
Sources and testing protocol
What this validation is based on
The page is a research summary, not audited live performance. These are the internal files and rule assumptions behind the published metrics.
| Area | Source | Test note |
|---|---|---|
| Market data | Normalized MES/MNQ continuous-contract intraday bars from work/databento_validation_normalized. | Coverage checked from source CSVs: 2023-06-01 through 2026-05-29. |
| Replay engine | work/drawing_board_edge_hunt_20260624.py plus work/prop_alpha_expanded_tournament.py. | 1-minute bars are resampled into the tested 2-minute and 5-minute execution views before signals are replayed. |
| Validation files | work/prop_alpha_expanded_validation_20260625 and work/prop_alpha_portfolio_validation_20260625. | Promoted candidates were rerun through 10,000 Monte Carlo prop-firm paths. |
| Rule template | Topstep-style 50K Combine/XFA simulator, verified from official Topstep help pages on 2026-06-25. | Includes MLL, optional DLL, contract limits, micro ratio, consistency, payout-day, and automation caveats. |
| Costs | $1.24 commission per side and 1 tick slippage per side in the current simulator template. | Live fills must be audited before scaling. If costs drift, the strategy is paused. |
Risk note
Strategy research is educational software and trading research, not financial advice. Backtests and Monte Carlo simulations can fail in live markets due to fees, slippage, latency, platform behavior, regime changes, and user execution.