For educational and research purposes only, not investment advice.
Trading Agents Lab
how it works

One ticker. Twelve specialists. Four phases.

A Diligence is not one prompt answered by one model. It is a structured sequence of independent agents, each with their own role, their own facts to look at first, and their own instruction to disagree with the others when it matters.

The result is a transcript you can read, audit, and learn from, not a black-box score. Below is the full pipeline as it ships in the codebase today.

phase_01

Analysts

  • market_analyst
    price action · volume
  • news_analyst
    recent headlines
  • fundamental_analyst
    metrics · context
  • sentiment_analyst
    social signal
phase_02

Researchers

  • bull_researcher
    thesis for
  • bear_researcher
    thesis against
  • research_manager
    arbitrates
phase_03

Trader

  • trader
    proposes position
phase_04

Risk

  • risk_aggressive
    upside view
  • risk_conservative
    downside view
  • risk_neutral
    middle path
  • portfolio_manager
    final call
phase_01

Analysts

Each analyst pulls live data from a single domain and writes what they see.

  • market_analyst

    Reads last price, multi-day price action, volume vs the 60-day average, and the recent range. Pulls from yfinance by default, or from Alpaca when keys are configured.

  • news_analyst

    Surfaces recent headlines about the ticker. Headlines flow into the transcript with source attribution so the reader can verify upstream.

  • fundamental_analyst

    Asset-class-aware context, equities get earnings/valuation framing, crypto gets supply/macro framing. Never asserts numbers it cannot ground.

  • sentiment_analyst

    Aggregates retail sentiment from StockTwits + the relevant subreddit (asset-class routed). Quantifies bullish vs bearish lean and notes message volume vs baseline.

phase_02

Researchers

Two researchers argue against each other; a manager arbitrates.

  • bull_researcher

    Builds the strongest case to own the ticker. Synthesises the analysts, surfaces catalysts, and addresses the most likely counter-arguments before they are raised.

  • bear_researcher

    Builds the strongest case against. Looks for confirmation bias in the bull thesis. Will name specific things that would falsify the trade.

  • research_manager

    Reads both, weighs the evidence, and writes a synthesis that names which arguments are load-bearing and which are noise.

phase_03

Trader

A single agent proposes a specific position, not just a direction.

  • trader

    Takes the research synthesis and writes a concrete trade plan: entry, sizing as a percentage of a hypothetical portfolio, and a stop. This is the only phase that proposes a number.

phase_04

Risk

Three risk seats stress-test the proposal from opposing angles, and a portfolio manager makes the final call.

  • risk_aggressive

    Argues the proposed sizing is too small for the asymmetry on offer. Bias: upside under-pricing.

  • risk_conservative

    Argues the position assumes the thesis is right and ignores tail risk. Bias: downside under-pricing.

  • risk_neutral

    Holds the line between the two. Bias: the median path is most likely.

  • portfolio_manager

    Reads all three risk seats plus the trader plan and writes the committee assessment the user sees: an analytical stance (Bullish through Bearish), a conviction score, bull and bear thesis strengths, and a risk level.

what the user sees

A streaming transcript, not a popup.

Each agent renders into the UI the moment they finish writing. You watch the debate build. A phase progress strip shows which phase is running and how many agents have spoken. A running cost meter shows token spend tick up.

When the portfolio manager finishes, a committee assessment materialises beneath the transcript with the stance, the conviction, the thesis strengths, and a one-paragraph rationale. You can copy the entire transcript as Markdown, or replay it later from the History page.

If you've configured webhooks, the assessment is also pushed to your endpoint of choice (Telegram, Slack, Discord, or your own JSON receiver with HMAC verification) the moment it lands.

one complete run

One ticker, start to finish.

Everything above, in a single real Diligence, exported straight from the app as a self-contained document. This is one full NVDA run, top to bottom: the data summary and headlines, all four analysts, the bull and bear researchers and their manager's synthesis, the trader's plan, the three risk seats, and the committee assessment the portfolio manager writes at the end. The text is selectable, so read it the way you would in the app, or open the transcript in its own tab.

One complete run · NVDA · twelve agents, start to finish
Educational and research purposes only. This is illustrative output from one Diligence run on one day; the numbers, dates, and assessment text are not investment advice, not a recommendation, and not a forecast. Past performance does not indicate future results, and historical references in a transcript are not predictive of future performance. Do not trade on anything shown here. You are solely responsible for your own decisions.
honest about ai

What the system cannot do, by design.

A Diligence does not predict the market. It does not guarantee outcomes. It is not investment advice. Agents are LLMs and can be confidently wrong; the entire point of running twelve of them is to make the disagreement visible to you, the reader.

Trading Agents Lab will not place a trade for you. It does not ship broker integrations. If you decide to act on the analysis, you do so on your own authorised brokerage account, via your own credentials, with your own responsibility. Read our positioning →