Multi-Agent Quant Infrastructure

A trading brain that reasons, backtests, and executes.

LiquidVenture.ai fuses a multi-agent research pipeline with Python-native, millisecond-grade order routing across QuantConnect and Interactive Brokers.

alpha-engine // console
LIVE

Strategies live

42

+6 this quarter

Order latency

3.2ms

median, IBKR route

Agents online

11

local + external

Sharpe (blended)

2.14

trailing 12m

Backtest vs. live, normalized to 100

Agent activity

  • data-agentRestored 3,412 missing OHLCV bars · AAPL 2011–2013
  • factor-agentIsolated MA(50) attribution — dropped default fallback
  • exec-agentRouted 128 orders via IBKR · median 3.1ms
  • risk-agentMOD3 exit triggered on SWING-07 · drawdown capped 2.4%
  • research-agentParsed 47 analyst reports · 6 factor candidates flagged

Four systems, one engine

From raw data restoration to isolated-variable backtesting and live execution — every layer is decoupled and auditable.

/trading

Quant Execution

Python core with deep QuantConnect + Interactive Brokers integration for millisecond order routing.

/research

AI Research Brain

Multi-agent workflows ingest research, clean and restore missing data, and mine factors automatically.

/modules

Strategy & Risk

Decoupled strategy library with pluggable exits like MOD3 and a statistical loss-analysis framework.

governance

Isolated Testing

Strip multi-factor noise to attribute a single variable — no misleading default-parameter conclusions.

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