DOCUMENTATION / v0.1

Architecture

Jensen Agent is designed as a narrow, auditable NVDA trading system. The objective is not to make a language model guess prices; it is to combine structured research, quantitative features, deterministic risk policy and verifiable execution records.

1. Design thesis

Specialization over generalization. One asset universe creates a cleaner data model, clearer risk assumptions, more interpretable attribution and an easier public proof surface.

2. System layers

Intelligence layer

Transforms unstructured NVIDIA-related information into structured event features. It should not directly hold brokerage credentials or bypass risk policy.

Quantitative engine

Builds market state, calculates features and produces expiring trade candidates with normalized confidence.

Risk engine

Applies deterministic constraints to every candidate. Approval is machine-verifiable and independent from model rhetoric.

Execution infrastructure

Translates approved orders to broker instructions, listens for fills, reconciles positions and writes ledger events.

3. Trade object

trade {
  id
  strategy_version
  asset
  side
  candidate_created_at
  signal_snapshot
  risk_snapshot
  order_ids[]
  fills[]
  average_entry
  average_exit
  fees
  gross_pnl
  net_pnl
  exit_reason
  status
  reconciled_at
}

4. Production rules

Auditability

Every state transition gets a timestamped event. Never silently edit historical trade results.

Isolation

Research/model services do not get unrestricted access to treasury or brokerage credentials.

Fail closed

Missing feed, stale state, reconciliation mismatch or policy uncertainty should prevent new execution.

5. Disclosure

Jensen Agent is an independent experimental project inspired by Jensen Huang's public persona and NVIDIA's role in AI computing. It is not affiliated with, endorsed by, or operated by Jensen Huang or NVIDIA. Any future live deployment should clearly separate verified results from simulated, backtested or demo data.