175 lines
4.2 KiB
Markdown
175 lines
4.2 KiB
Markdown
---
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name: openbb-research
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description: AI-powered investment research using OpenBB - comprehensive analysis, thesis generation, risk assessment, actionable insights
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---
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# OpenBB AI Investment Research
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AI-powered comprehensive investment research combining OpenBB data with Claude's analytical capabilities.
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## Usage
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```bash
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/openbb-research SYMBOL [--depth deep|quick] [--focus thesis|risks|opportunities]
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```
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## What This Command Does
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Conducts comprehensive AI-powered investment research by combining multiple OpenBB data sources with advanced analysis.
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## Workflow
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### 1. Data Aggregation
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```python
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from openbb import obb
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symbol = "AAPL"
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# Gather comprehensive data
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data = {
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"price": obb.equity.price.historical(symbol=symbol, period="1y"),
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"fundamentals": obb.equity.fundamental.metrics(symbol=symbol),
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"analyst": obb.equity.estimates.analyst(symbol=symbol),
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"news": obb.equity.news(symbol=symbol, limit=10),
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"peers": obb.equity.compare.peers(symbol=symbol),
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"insider": obb.equity.ownership.insider(symbol=symbol)
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}
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```
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### 2. Investment Thesis Generation
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```python
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print(f"\n📋 Investment Thesis for {symbol}")
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print(f"{'='*60}")
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# Business Analysis
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print(f"\n1. Business Quality:")
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print(f" - Competitive moats identified")
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print(f" - Revenue growth trajectory")
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print(f" - Margin trends and sustainability")
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print(f" - Market position and share")
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# Financial Health
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print(f"\n2. Financial Strength:")
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print(f" - Balance sheet assessment")
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print(f" - Cash flow generation")
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print(f" - Capital allocation efficiency")
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print(f" - Debt levels and coverage")
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# Valuation
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print(f"\n3. Valuation Assessment:")
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print(f" - P/E vs sector average")
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print(f" - PEG ratio analysis")
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print(f" - DCF model implications")
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print(f" - Historical valuation ranges")
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# Catalysts
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print(f"\n4. Key Catalysts:")
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print(f" - Upcoming earnings/events")
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print(f" - Product launches")
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print(f" - Regulatory developments")
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print(f" - Industry trends")
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```
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### 3. Risk Assessment
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```python
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print(f"\n⚠️ Risk Factors:")
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risks = []
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# Check technical risks
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if data["price"].rsi[-1] > 75:
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risks.append("Overbought conditions - potential pullback risk")
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# Check fundamental risks
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if data["fundamentals"].debt_to_equity > 1.5:
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risks.append("High leverage - financial risk elevated")
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# Check market risks
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if data["price"].volatility > 50:
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risks.append("High volatility - price uncertainty")
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for i, risk in enumerate(risks, 1):
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print(f" {i}. {risk}")
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```
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### 4. Opportunity Analysis
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```python
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print(f"\n💡 Investment Opportunities:")
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opportunities = []
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if data["analyst"].rating_score > 4.0:
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opportunities.append("Strong analyst support - positive sentiment")
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if data["insider"].net_buy_sell > 0:
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opportunities.append("Insider buying - management confidence")
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if data["fundamentals"].roe > 20:
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opportunities.append("High ROE - efficient capital use")
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for i, opp in enumerate(opportunities, 1):
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print(f" {i}. {opp}")
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```
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### 5. Actionable Recommendations
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```python
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print(f"\n🎯 Recommendation:")
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# Decision matrix
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score = 0
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score += 2 if data["analyst"].rating_score > 4.0 else 0
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score += 2 if data["fundamentals"].roe > 15 else 0
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score += 1 if data["price"].trend == "bullish" else 0
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score -= 1 if data["fundamentals"].pe_ratio > 30 else 0
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if score >= 4:
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rating = "BUY"
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action = "Consider accumulating position"
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elif score >= 2:
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rating = "HOLD"
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action = "Monitor closely, hold current position"
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else:
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rating = "AVOID"
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action = "Wait for better entry point"
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print(f" Rating: {rating}")
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print(f" Action: {action}")
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print(f" Confidence: {score}/5")
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```
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## Examples
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```bash
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# Deep research report
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/openbb-research AAPL --depth=deep
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# Quick thesis
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/openbb-research MSFT --depth=quick --focus=thesis
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# Risk analysis
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/openbb-research TSLA --focus=risks
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```
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## Output Format
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1. Executive Summary
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2. Investment Thesis
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3. Financial Analysis
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4. Valuation Assessment
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5. Risk Factors
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6. Opportunities
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7. Recommendation & Price Targets
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8. Monitoring Checklist
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## Integration
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- Export reports to PDF/Markdown
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- Track recommendations over time
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- Compare with analyst consensus
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- Portfolio integration via `/openbb-portfolio`
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