Two systematic strategy lines presented for pilot evaluation. The Orderflow Engine targets intraday futures execution; the Stock Engine manages equity portfolio allocation. Together they provide a clear performance record, trade-level transparency and a practical path toward a controlled test.
The page presents two complementary model tracks with separate backtest windows, execution logic and scaling rules. Each track can be reviewed independently, then combined into a structured pilot program.
Orderflow spans roughly thirteen months of futures replay data. Stock spans the current six-month equity export set. PnL is therefore shown alongside PF, DD, trade count and duration for a balanced allocation review.
The presentation separates two portfolio roles: a futures execution model and an equity selection and allocation model, each with its own controls, data requirements and capacity profile.
Uses orderflow-style inputs, volume behavior, value-area/profile context and setup families across the current futures universe. The presentation highlights Point Zero B-system replay behavior and trade-level auditability.
Uses selected stock trade exports and account-level risk constraints to size and combine symbol systems. The presentation highlights the 100K account allocation under the 1% daily drawdown rule.
The next infrastructure step is an automated scanner that expands the equity universe, tests candidates, and proposes replacements or additions when a stock improves the portfolio profile.
Continuously screen candidate stocks for liquidity, volume behavior, volatility profile and strategy fit.
Run the Stock Engine across candidates and compare PF, drawdown, PnL, trade count and overlap against the current list.
Recommend adds, removals or caps only when a candidate improves the portfolio under the same risk rules.
Review proposed changes in shadow mode before promotion to the approved trade universe.
The Orderflow section covers PZ B1000, B1200, B1400 and B1700 across MNQ, MGC, MCL, MES and M2K using the internal replay export.
The review package focuses on performance evidence, trade behavior and pilot readiness while preserving strategy IP.
The Stock section uses the selected trade CSV audit set. Headline PnL is shown for the 100K account allocation under the 1% daily-DD rule.
The equity review highlights allocation behavior, risk controls and expansion potential for a broader stock universe.
Select a B-system to update the metrics, symbol contribution, calendar and trade table. The data is loaded from the internal Orderflow replay export.
| System | Trades | PnL | Max DD | PF | Win | Days |
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| Symbol | Trades | PnL | Max DD | PF | Win |
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| Month | Days | Trades | PnL | Wins | Losses |
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| Date | Symbol | Dir | Lots | Setup | Score | Entry | Exit | Dur | Pts | PnL | Exit reason |
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Stock results are the current published uncapped portfolio set. Headline KPIs use the 100K account allocation; the complete trade log below remains the selected system CSV audit view.
| Symbol | Family | Trades | PnL | PF | Max daily DD | Overall DD |
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| Mode | Account | PnL | Max Daily DD | PF | Trades | Max concurrent |
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| Month | Days | Trades | PnL | Wins | Losses |
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| Date | Symbol | Family | Dir | Setup | Score | Entry | Exit | Bars | R | PnL @100 | Exit reason |
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The package gives a clear view of trade distribution, timing, exits, symbol concentration and drawdown behavior. Strategy IP remains protected while the measurable operating profile is available for allocator review.
Orderflow bars, volume behavior, market context, value-area/profile levels and multi-timeframe structure. Stock data is modeled from aggregated bid/ask volumetric bars.
Candidate setups are scored, filtered and handled by system families. The presentation shows setup categories, outcomes and operating behavior for review.
Replay exits include stop checks, partial/management behavior and dynamic exit reasons. Stock allocation is constrained by a hard daily drawdown rule.
The right next step is a shadow or small-capital evaluation where fills, rejected trades, latency, slippage and drawdown behavior are measured against this backtest story. In parallel, the Stock Engine can evolve into a scanner-driven portfolio selection process.
The long-term equity infrastructure can continuously evaluate a broader universe and propose portfolio changes when the evidence beats the current approved list.
Identify candidate stocks that meet liquidity, activity and tradability filters.
Run the same Stock Engine logic and risk rules across new candidates.
Rank candidates against the current list by PF, DD, PnL, trades and overlap.
Suggest adds, removals or caps for human approval before deployment.