Quantitative Trading & Algorithmic Infrastructure

Autonomous Multi-Agent Alpha Generation

Our trading architecture breaks down the trading lifecycle into dedicated autonomous agents. Sentiment agents ingest macroeconomic feeds, quantitative agents run continuous time-series regression and factor modeling, and risk supervisor agents validate margin limits prior to order transmission.

This multi-agent consensus model minimizes emotional bias, mitigates tail risk, and executes systematic strategies in sub-millisecond cycles.

Institutional Brokerage & Schwab API Integration

Engineered with direct OAuth 2.0 integrations for institutional brokerage APIs, including Charles Schwab Trader API, Interactive Brokers, and FIX protocol gateways.

• Token refresh rotation and secure encrypted credential isolation via AWS KMS.
• Real-time websocket streaming for level-2 order book quotes and execution reports.
• Strict idempotency and order deduplication pipelines to prevent duplicate executions.
• Low-latency order routing with automated circuit breakers and slippage protection.

Institutional Security & Risk Engine

Capital protection is the primary constraint of our trading engine. We implement hard deterministic boundaries around autonomous agent actions, including max drawdown halts, exposure ceilings, and multi-factor authorization checkpoints.

All trade telemetry, agent deliberation logs, and fill timestamps are immutably recorded for regulatory audit and compliance inspection.

Cloud Infrastructure Architecture

Hosted on a dedicated AWS cloud cluster under app.amartian.tech. Isolated microservices manage market data ingest, strategy computation, and trade execution within a private VPC with sub-millisecond internal latency.

• AWS Cognito authenticated session management and RBAC.
• Automated OAuth handshake supporting production & local test callbacks.
• Multi-AZ high availability with zero-downtime hot failovers.