Two systematic strategies, one fully transparent track record. The Orderflow Engine executes intraday futures with disciplined, rules-based precision; the Stock Engine allocates an equity portfolio under hard 1% daily-drawdown and 90% simultaneous gross-exposure limits. Every trade is auditable and every result reproducible, and both are ready for a controlled pilot you can verify from day one.
Two complementary, structurally different return streams — each with its own backtested edge, execution logic and scaling rules. Review them independently, then combine them into a single structured pilot built to scale with your capital.
The Orderflow Engine is backed by roughly thirteen months of futures replay; the Stock Engine by a current six-month equity record. Every figure — PnL, profit factor, drawdown, trade count and duration — sits side by side, so you can underwrite the opportunity rather than trust a headline.
Each engine plays a different role in the book — a futures execution model and an equity selection-and-allocation model — with its own controls, data and capacity. Together they diversify how and when the portfolio makes money.
Reads orderflow-style inputs — volume behavior, value-area/profile context and proven setup families — across a liquid futures universe. The Point Zero B-system replay is documented trade by trade, so the edge is visible and verifiable, never a black box.
Combines selected symbol systems under strict account-level risk control, sizing every position to the portfolio. The 100K allocation runs under hard 1% daily-drawdown and 90% gross-exposure limits, so return is generated inside the capital budget.
The next build is an automated scanner that continuously expands the equity universe, backtests new candidates, and proposes additions or swaps only when they measurably improve the portfolio — turning today's edge into a compounding, self-renewing pipeline.
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.
Full performance evidence, trade-level behavior and pilot readiness — with the strategy IP protected. You see the results and the proof, not the recipe.
The Stock section uses the selected trade CSV audit set. Headline PnL is shown for the 100K account allocation under the 1% daily-DD and 90% gross-exposure rules.
Allocation behavior, disciplined risk controls and clear room to expand into 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 risk-capped 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 | Peak Exposure | Exposure Use | 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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You get full visibility into trade distribution, timing, exits, symbol concentration and drawdown — the operating profile an allocator needs to underwrite and size a position. The strategy IP stays protected; the evidence does not.
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. Setup categories, outcomes and operating behavior are shown for review.
Every exit is rule-based - stop checks, partial management and dynamic exit logic - and the equity book is held to daily-drawdown and gross-exposure limits. Risk is engineered in, not bolted on.
The natural next step is a low-risk pilot — shadow or small-capital — where real fills, rejects, latency, slippage and drawdown are measured live against this backtested record. It is the fastest way to confirm the edge on your own terms, with capital you control. In parallel, the Stock Engine grows into a scanner-driven selection process.
Over time the equity infrastructure continuously scans a broader universe and proposes changes only when the evidence beats the current approved list — a portfolio that keeps sharpening itself.
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.