concept
Multi-Agent Finance Workflows
Multi-Agent Finance Workflows
Concrete preset shapes for multi-agent systems in finance — investment, trading, and risk. Pulled from vibe-trading‘s 29 swarm presets as a reference catalog. Useful even outside trading: same shapes apply to any “team of specialists → consensus → sign-off” workflow.
Preset Shapes
Investment Committee
Bull researcher ─┐
├─→ Risk reviewer ─→ PM (final call)
Bear researcher ─┘
Pattern: adversarial debate → mediator → decision-maker. Two parallel agents with opposing biases force the mediator to surface real disagreements.
Global Equities Desk
A-share researcher ─┐
HK/US researcher ─┼─→ Global strategist
Crypto researcher ─┘
Pattern: parallel domain specialists → cross-market synthesizer. Each researcher uses domain-specific data sources (e.g. AKShare for A-share, yfinance for HK/US, CCXT for crypto). The strategist’s job is only synthesis — it doesn’t fetch raw data itself.
Crypto Trading Desk
Funding/basis ─┐
Liquidation ─┼─→ Risk manager
Flow analyst ─┘
Pattern: feature-specific signal generators → risk gate. Each signal agent has a narrow read on the market; the risk manager decides whether the combined signal clears the trading bar.
Earnings Research Desk
Fundamental analyst ─┐
Estimate revisions ─┼─→ Earnings strategist
Options pricing ─┘
Pattern: same as global equities but along the earnings-event axis (fundamentals + sell-side revisions + implied vol).
Macro Rates/FX Desk
Rates analyst ─┐
FX analyst ─┼─→ Macro PM
Commodity analyst ─┘
Quant Strategy Desk
Screener → Factor researcher → Backtest engine → Risk audit
Pattern: sequential pipeline (not parallel debate). Each step has a deterministic-ish output the next step consumes. More like LangGraph Multi-Agent Patterns#1. Handoffs than the parallel-debate shape above.
Technical Analysis Panel
Classic TA ─┐
Ichimoku ─┤
Harmonic ─┼─→ Consensus aggregator
Elliott ─┤
SMC ─┘
Pattern: ensemble of methodologies → vote/consensus. Useful when there’s no single right answer; the disagreement among methods is the signal.
Risk Committee
Drawdown reviewer ─┐
Tail-risk ─┼─→ Sign-off
Regime reviewer ─┘
Architectural Insights
DAG, not chain
All shapes are DAGs (directed acyclic graphs) with parallel-then-merge structure. Pure linear chains (handoff → handoff → handoff) are rare. The merge step is where the real reasoning happens; parallel branches are just specialized data gathering.
Two roles in every team
- Specialists — narrow scope, deep tool access, cheap to scale
- Synthesizer — broad scope, no raw-data tools, expensive thinking model
The cost-control trick: run specialists on a “sweet spot” tier model (e.g. deepseek-v3.2), reserve the synthesizer slot for a top-tier model (Claude Opus, GPT-5) where reasoning quality compounds.
Adversarial vs ensemble
- Adversarial (bull/bear): two specialists with mandated opposing priors. Surfaces hidden assumptions.
- Ensemble (TA panel): N specialists with different methodologies, no mandated priors. Surfaces method disagreement.
- Pick adversarial when the question has a binary answer; ensemble when it’s continuous (signal strength, regime probability).
Variant: Persona Specialists (instead of Role Specialists)
ai-hedge-fund uses a different shape of specialists: each agent is a famous investor (Buffett, Munger, Cathie Wood, Burry, Taleb…) rather than a functional role (“macro analyst”, “sector analyst”). 14 personas + 4 conventional analysts → risk manager → portfolio manager. Same DAG topology (parallel fan-out → fan-in), different identity model.
The persona shape works when the domain has well-known thought leaders with distinguishable, ideally contradictory positions. See Agent Persona Pattern for when to reach for this vs. role specialists.
Application Beyond Finance
These shapes generalize. For fajb-next:
- Investment committee → Article publish committee: factual reviewer + style reviewer → editor sign-off
- TA panel → Source verification panel: archive search + web search + cross-reference → confidence score
- Quant pipeline → RFP pipeline (in manzas): screen requirements → analyze fit → draft response → review
Related
- LangGraph Multi-Agent Patterns — the formal patterns underneath these shapes
- AI Agent Architectures — decision framework for picking patterns
- LangGraph Skills Pattern — how each specialist composes its tools
- vibe-trading — concrete implementation of all 29 presets (role specialists)
- ai-hedge-fund — concrete implementation of 14 personas + 4 analysts
- Agent Persona Pattern — the persona variant of multi-agent specialization
- Backtest Engines — what the quant pipeline feeds into