openInvest

A self-hosted investment decision engine built for modern AI agents. Multi-agent information isolation and cross-challenge protocol, providing an auditable decision trail (Audit Trail).

📚 Full Architecture Wiki · 🇨🇳 中文版

What is OpenInvest?

OpenInvest is a self-hosted investment decision engine built for modern AI agents.

It provides a verifiable investment committee, evidence-based reasoning, long-horizon backtesting, and auditable decision records. Instead of replacing Claude Code, Codex, Hermes, or OpenClaw, OpenInvest is designed to power them.

Live Performance & PnL

_{Data feed is automatically updated every 2 hours using `jobs/pnl_snapshot` and pushed to the pnl-data branch
Upper half: 30-day net asset value trend · Lower half: Net asset value comparison against 8 benchmark assets (transparent disclosure, not an alpha claim—the committee's proven value is discipline and transparency, not excess return, see ADR-023)
📌 Note: The current chart shows the author's live production portfolio. After self-hosting, the system will automatically render your own equity curve based on the holdings defined in your `memory/` directory.}

• Benchmark Portfolio: The system introduces 8 standard control benchmarks across 4 quadrants (AI advisors / Mutual funds / Wealth management / Broad market index). For details on the comparison methodology and data cleaning logic, see docs/wiki/README.md.

Research & Falsification

System Self-Disclosure: This system is an auditing tool to eliminate human investment cognitive biases and enforce reasoning transparency, not a return-amplifying black box. Latest automated audit (docs/verdict_accuracy.md): Directional verdicts (excluding HOLD) have a true hit rate of 42.2% (n=56, below random); HOLD accounts for 56% of all decisions. The system's value lies in transparency and discipline (mostly staying inactive, low turnover), not directional prediction. Detailed log stream can be found in docs/verdict_accuracy.md.

This project systematically attempts to falsify its own edge and publishes negative results as-is. The deterministic features the committee reads, and the timing signals around them, were tested against pre-registered statistical gates — none survived as tradable alpha.

Methodology: Newey-West HAC t-statistics, Deflated Sharpe Ratio (Bailey & López de Prado 2014, re-derived equation by equation), Holm correction, zero lookahead, and LLM training-cutoff probes.

Details: experiments/signal-eval/README.md · docs/verdict_accuracy.md · ADR-022 · ADR-023

Product Philosophy

Most AI investment assistants try to become better chatbots. OpenInvest instead builds a transparent, verifiable, and auditable decision engine that plugs into personal agents such as Claude Code, Codex, Hermes, and OpenClaw — every improvement in those agents automatically makes OpenInvest more capable.

The division of labor is deliberate: your agent handles long-term memory, natural conversation, and user understanding; OpenInvest handles the verifiable investment committee, evidence-based reasoning, long-horizon backtesting, and auditable decision records.

                   User
                     │
         ┌───────────┴───────────┐
         ▼                       ▼
    Your Agent             OpenInvest
(User Understanding)   (Market Understanding)
         │                       │
         └───────────┬───────────┘
                     ▼
            Better Investment Decisions

Your agent knows you. OpenInvest knows investing.

Avoiding User Ownership

OpenInvest intentionally avoids "owning" the user. Most AI products try to own everything—memory, persona, chat history, and workspaces. OpenInvest takes a back seat. It exposes clean APIs, CLI commands, and agent skills (Claude Code / Codex / Hermes / OpenClaw), letting your primary agent manage the conversation and context while OpenInvest powers the underlying investment intelligence.

Features

• Multi-Agent Investment Committee: Isolated analysis and round-rebuttal debate.
• Coordinator-Worker Architecture: Prevents context contamination and role hallucination.
• Information Isolation: Rigidly blocks quant and risk analysts from out-of-boundary contexts.
• Auditable Decision Trail: Clean logs showing exactly "why" each decision was made.
• Markdown-as-a-Database: Frontmatter (YAML) + Markdown (Body) as the single source of truth.
• Long-Horizon Backtesting: Built-in test harness with lookahead bias protections.
• Dreaming-Based Memory Consolidation: Nightly memory distillation to prevent context drift.
• Self-Hosted / Zero-Cost: Powered directly by your local agent's reasoning resources.
• Agent Skill: Lightweight plugin for Claude Code / Codex / Hermes / OpenClaw, with interactive bootstrap wizard.
• Automated Deployment: GitHub Actions workflow to run the committee and email reports daily.

Quick Start

1. Integrate with your agent (Recommended)

Add the lightweight skill from your agent's plugin registry. The host agent will automatically pull the core code and align dependencies on first run:

# Claude Code
/plugin marketplace add longsizhuo/openInvest
/plugin install invest@openinvest

# Codex
codex plugin marketplace add longsizhuo/openInvest

# Hermes Agent
hermes plugins install longsizhuo/openInvest --enable

# OpenClaw
openclaw plugins install clawhub:openinvest

Any other MCP client: register the MCP server from step 2 below (full walkthrough in the agent tutorial).

2. Standalone — MCP server or CLI (no clone needed)

The backend ships on PyPI; ~/openInvest holds only your data:

# MCP (18 tools, any MCP client; add --http for a remote streamable-HTTP server — BETA)
claude mcp add openinvest -e INVEST_HOME=~/openInvest -- uvx openinvest-mcp

# or plain CLI
INVEST_HOME=~/openInvest uvx openinvest status

Send set up invest (or 帮我初始化 invest) to any skill-enabled AI terminal. The system will trigger an interactive bootstrap wizard to guide you through:

1. Detecting the memory/ state storage path and .env configuration.
2. 5-dimensional profiling (Legal name, Risk capacity, Debt structure, Initial holdings, and optional keys).
3. Running static data migration to immediately generate your first asset exposure memo.

💡 Zero-Cost Execution: In skill interactive mode, the committee's underlying reasoning relies entirely on the host agent's (e.g. Claude Code) reasoning pipeline. No third-party API Key is consumed. You only need to configure an API key when setting up automated crons or calling independent Web APIs.

For self-hosting details, see docs/QUICK_START.md. (The bundled Web GUI was retired on 2026-07-05 — all capabilities are exposed via CLI/MCP; a standalone frontend may return later.)

3. Serverless Self-Hosting (GitHub Actions)

Run the committee automatically via GitHub Actions and receive daily digest emails.

⚠️ Fork must be set to Private: State files (holdings, verdicts) will be committed back to your fork. Public forks will leak your private financial information.