openfinclaw-quant-research

# OpenFinClaw Quant Research > Skill by [ara.so](https://ara.so) — Hermes Skills collection. OpenFinClaw is an AI-powered quantitative research platform that enables end-to-end quant workflows through natural language prompts. It provides 60+ built-in analysis skills covering technical, fundamental, sentiment, risk, and factor analysis across US equities, A-shares, HK, crypto, and forex markets. The platform integrates with 20+ AI agents via MCP (Model Context Protocol) and supports streaming research, strategy generation, backtesting, paper trading, and community strategy publishing. ## Installation ### Quick Install (Interactive Wizard) ```bash npx @openfinclaw/cli@latest install ``` The wizard will: - Guide you through API key setup - Configure MCP for detected AI agents - Register skill definitions for Claude Code/Cursor - Run connectivity checks ### Non-Interactive Install ```bash npx @openfinclaw/cli@latest install --yes \ --platforms cursor,claude-code \ --tool-groups deepagent,strategy \ --api-key $OPENFINCLAW_API_KEY \ --register-skill ``` ### Manual MCP Configuration Add to your AI agent's MCP config: **Claude Code** (`~/.claude/settings.json`): ```json { "mcpServers": { "openfinclaw": { "command": "npx", "args": ["@openfinclaw/cli", "serve", "--tools=deepagent,strategy"], "env": { "OPENFINCLAW_API_KEY": "fch_xxx" } } } } ``` **Cursor** (`.cursor/mcp.json`): ```json { "mcpServers": { "openfinclaw": { "command": "npx", "args": ["@openfinclaw/cli", "serve", "--tools=deepagent,strategy"], "env": { "OPENFINCLAW_API_KEY": "fch_xxx" } } } } ``` **VS Code Copilot** (`settings.json`): ```json { "github.copilot.chat.codeGeneration.instructions": [ { "file": "~/.claude/skills/openfinclaw/SKILL.md" } ], "mcp.servers": { "openfinclaw": { "command": "npx", "args": ["@openfinclaw/cli", "serve"] } } } ``` ## Core Commands ### DeepAgent (Research & Backtesting) ```bash # Stream research → strategy → backtest in one command openfinclaw deepagent +research "Find RSI divergence on NVDA in last 6 months" # Check available analysis skills openfinclaw deepagent skills # List research threads openfinclaw deepagent threads # Get thread messages openfinclaw deepagent messages --thread-id <id> # View backtests openfinclaw deepagent backtests --limit 10 # Download research package openfinclaw deepagent download --package-id <id> --output ./results ``` ### Strategy Management ```bash # Browse top community strategies openfinclaw leaderboard --limit 20 # Get strategy details openfinclaw strategy-info <strategy-id> # Fork a strategy locally openfinclaw fork <strategy-id> # List local strategies openfinclaw list-strategies # Validate FEP v2.0 compliance openfinclaw validate ./strategies/my-strategy # Publish to leaderboard openfinclaw publish ./my-strategy.zip # Check publish status openfinclaw publish-verify --submission-id <id> ``` ### System Commands ```bash # Health check openfinclaw doctor # Update to latest version openfinclaw update # View examples openfinclaw examples # Install skill definitions openfinclaw skill-install # Start MCP server manually openfinclaw serve --tools=deepagent,strategy ``` ### Raw API Access ```bash # Direct GET request openfinclaw api GET /api/v2/deepagent/threads # Direct POST request openfinclaw api POST /api/v2/deepagent/research/submit \ --json '{"query": "Analyze AAPL momentum", "skill_ids": ["technical_momentum"]}' ``` ## Configuration ### API Key Setup Get your API key from [hub.openfinclaw.ai](https://hub.openfinclaw.ai). **Environment Variable:** ```bash export OPENFINCLAW_API_KEY=fch_xxx ``` **Config File:** `~/.openfinclaw/config.json` ```json { "apiKey": "fch_xxx" } ``` **Command-line:** ```bash openfinclaw deepagent +research "query" --api-key fch_xxx ``` Resolution order: `--api-key` → `OPENFINCLAW_API_KEY` → config file ### Tool Groups Optimize token usage by loading only needed tools: ```bash # DeepAgent only (~1,400 tokens) openfinclaw serve --tools=deepagent # Strategy only (~1,000 tokens) openfinclaw serve --tools=strategy # Both groups (default) openfinclaw serve ``` ## Common Research Patterns ### Technical Analysis ```typescript // Find RSI divergence signals const query = "Find RSI divergence signals on NVDA in the last 6 months, then backtest them"; // Bollinger Bands comparison const query = "Compare a Bollinger Bands strategy on TSLA vs AAPL over 1 year — which wins?"; // Golden cross screening const query = "Screen the S&P 500 for golden-cross signals this month"; // Moving average crossover backtest const query = "Backtest a 50/200 SMA crossover on SPY from 2015. Include costs and slippage"; ``` ### Fundamental Analysis ```typescript // Quarterly financials trend const query = "Pull Apple's last 8 quarters of revenue, margins, and guidance. Summarize the trend"; // Earnings driver analysis const query = "What's driving the NVDA move this quarter — earnings, guidance, or narrative?"; // Peer comparison const query = "Compare AMD / INTC / NVDA on growth, margin, and valuation"; ``` ### Strategy Generation ```typescript // Momentum strategy with constraints const query = "Design a momentum strategy on US mega-cap tech. Backtest 2y. Tell me where it breaks"; // Mean reversion with stress testing const query = "Write a mean-reversion strategy on BTC and show drawdown behavior through 2022"; // Chinese market rotation strategy const query = "A-shares 沪深 300 日内轮动策略，年化目标 15%，最大回撤 < 10%"; ``` ## MCP Tool Reference ### DeepAgent Tools (14 total) ```typescript // Health check fin_deepagent_health() // List available analysis skills fin_deepagent_skills() // Submit research (async) fin_deepagent_research_submit({ query: string, skill_ids?: string[] }) // Poll research status fin_deepagent_research_poll({ submission_id: string }) // Finalize and get results fin_deepagent_research_finalize({ submission_id: string }) // Get task status fin_deepagent_status({ task_id: string }) // Cancel task fin_deepagent_cancel({ task_id: string }) // List threads fin_deepagent_threads({ limit?: number, offset?: number }) // Get thread messages fin_deepagent_messages({ thread_id: string }) // List backtests fin_deepagent_backtests({ limit?: number, offset?: number }) // Get backtest result fin_deepagent_backtest_result({ backtest_id: string }) // List packages fin_deepagent_packages({ limit?: number }) // Get package metadata fin_deepagent_package_meta({ package_id: string }) // Download package fin_deepagent_download_package({ package_id: string, output_path: string }) ``` ### Strategy Tools (7 total) ```typescript // Browse leaderboard strategy_leaderboard({ limit?: number, offset?: number }) // Get strategy details strategy_get_info({ strategy_id: string }) // Fork strategy strategy_fork({ strategy_id: string, output_dir?: string }) // List local strategies strategy_list_local({ strategies_dir?: string }) // Validate FEP v2.0 compliance strategy_validate({ strategy_path: string }) // Publish strategy strategy_publish({ strategy_path: string }) // Verify publish status strategy_publish_verify({ submission_id: string }) ``` ## Strategy Development Workflow ### 1. Fork and Customize ```bash # Find a strategy on the leaderboard openfinclaw leaderboard # Fork it locally openfinclaw fork strat_abc123 # This creates: ./strategies/strat_abc123/ # ├── strategy.py # ├── fep.yaml # └── README.md ``` ### 2. Edit Strategy **strategy.py** (Python): ```python from openfinclaw import Strategy, Signal class MyStrategy(Strategy): def __init__(self): self.rsi_period = 14 self.overbought = 70 self.oversold = 30 def on_bar(self, bar): rsi = self.indicators.rsi(self.rsi_period) if rsi < self.oversold and not self.position: return Signal.BUY elif rsi > self.overbought and self.position: return Signal.SELL return Signal.HOLD ``` **fep.yaml** (FEP v2.0 metadata): ```yaml version: "2.0" strategy: name: "RSI Mean Reversion" description: "Buy oversold, sell overbought" author: "your_username" tags: ["technical", "rsi", "mean-reversion"] parameters: rsi_period: 14 overbought: 70 oversold: 30 backtest: start_date: "2020-01-01" end_date: "2023-12-31" initial_capital: 100000 symbols: ["AAPL", "MSFT", "GOOGL"] ``` ### 3. Validate and Publish ```bash # Validate FEP compliance openfinclaw validate ./strategies/strat_abc123 # Zip and publish cd strategies/strat_abc123 zip -r ../../my-strategy.zip . cd ../.. openfinclaw publish ./my-strategy.zip # Track backtest progress openfinclaw publish-verify --submission-id sub_xyz789 ``` ## Streaming vs. Polling Patterns ### Streaming (Human-Friendly CLI) ```bash # Single command, real-time output openfinclaw deepagent +research "Analyze TSLA momentum indicators" ``` Output streams token-by-token with progress indicators. ### Polling (Agent/Script Integration) ```bash # Submit SUBMISSION_ID=$(openfinclaw api POST /api/v2/deepagent/research/submit \ --json '{"query":"Analyze TSLA"}' | jq -r .submission_id) # Poll until complete while true; do STATUS=$(openfinclaw api GET /api/v2/deepagent/research/poll/$SUBMISSION_ID \ | jq -r .status) [[ "$STATUS" == "completed" ]] && break sleep 2 done # Finalize openfinclaw api GET /api/v2/deepagent/research/finalize/$SUBMISSION_ID ``` ## Prompt Engineering Tips ### Effective Research Queries **✅ Good:** - "Find RSI divergence on NVDA last 6 months, then backtest with 2% stop-loss" - "Compare Bollinger Bands vs RSI on AAPL 2020-2023, which has better Sharpe ratio?" - "Screen S&P 500 for MACD golden cross this week, rank by volume" **❌ Too Vague:** - "Analyze stocks" - "Good trading ideas" - "What should I buy?" ### Include Constraints ```typescript // Specify timeframe "Backtest momentum strategy on TSLA Jan 2022 - Dec 2023" // Risk parameters "Mean reversion BTC, max drawdown < 15%, position size 10%" // Performance targets "Design strategy: 15% annual return, Sharpe > 1.5, max 10% drawdown" ``` ### Multi-Step Workflows ```typescript // Research → Strategy → Backtest → Optimize const query = ` 1. Analyze AAPL price action last 2 years 2. Design a momentum strategy based on findings 3. Backtest with transaction costs 4. Suggest parameter optimizations `; ``` ## Troubleshooting ### API Key Issues ```bash # Check current config cat ~/.openfinclaw/config.json # Verify key works openfinclaw doctor # Re-run wizard openfinclaw install --yes --api-key $OPENFINCLAW_API_KEY ``` ### MCP Connection Failed ```bash # Check MCP server starts npx @openfinclaw/cli serve --tools=deepagent # Verify config path for your agent # Claude Code: ~/.claude/settings.json # Cursor: .cursor/mcp.json # VS Code: settings.json # Check logs tail -f ~/.openfinclaw/logs/mcp-server.log ``` ### Strategy Validation Errors ```bash # Common FEP v2.0 issues: # - Missing fep.yaml # - Invalid version (must be "2.0") # - Missing required fields: name, description, author # Validate before publishing openfinclaw validate ./my-strategy # Check example strategies openfinclaw leaderboard openfinclaw fork <top-strategy-id> # Use as template ``` ### Backtest Timeout ```bash # For long-running backtests, use polling pattern: SUBMISSION_ID=$(openfinclaw deepagent research-submit \ --query "Long backtest query" --json | jq -r .submission_id) # Check status periodically openfinclaw deepagent research-poll --submission-id $SUBMISSION_ID # Download when complete