Strategy 1 - Supply versus Demand

Trade Control models supply and demand not as static records, but as recursive declarations embedded in the schema. Inspired by manufacturing scheduling algorithms, it treats financial flow as a dynamic allocation problem—where invoices declare demand, payments fulfil supply, and balances emerge from polarity-aware traversal.

Declarative Logic

Each transaction is a declaration:

• Invoices declare intent—Demand
• Payments fulfil obligation—Supply
• Opening balances set the initial state

These declarations are sequenced, polarised, and aggregated to form a live financial narrative. There is no need for journals, double-entry logic, or legacy constructs. Trade Control simply adds things up¹.

Recursive Traversal

The system traverses the transaction stream² to:

• Merge invoices and payments into a unified flow
• Apply polarity to calculate directional charges
• Sequence transactions per account
• Backfill opening balances
• Derive running balances through aggregation

This traversal gives you:

• Closing balance
• Debtors and creditors
• Liquidity position
• Fulfilment status

All calculated in milliseconds. Because computers are very good at adding up.

Schema-Native Insight

Trade Control reframes supply and demand:

Supply is not stock—it is capacity.
Demand is not prediction—it is intent.

By modelling these as declarations, not possessions, the system enables:

• Just-in-time orchestration
• Zero-inventory workflows
• Recursive fulfilment logic across distributed networks

This logic is not abstract—it is operational. It renders the financial interface with the same clarity as a manufacturing schedule.

Summary

Trade Control treats supply and demand as schema-native declarations. It models financial flow as a recursive traversal, where polarity drives fulfilment and balance emerges from structure. This enables real-time liquidity modelling, fulfilment tracking, and operational clarity—without relying on legacy accounting logic.