| name | institutional-flow-tracker |
| description | Use this skill to track institutional investor ownership changes and portfolio flows using 13F filings data. Analyzes hedge funds, mutual funds, and other institutional holders to identify stocks with significant smart money accumulation or distribution. Helps discover stocks before major moves by following where sophisticated investors are deploying capital. |
| allowed-tools | ["Bash(python3:*)"] |
Institutional Flow Tracker
Overview
This skill tracks institutional investor activity through 13F SEC filings to identify "smart money" flows into and out of stocks. By analyzing quarterly changes in institutional ownership, you can discover stocks that sophisticated investors are accumulating before major price moves, or identify potential risks when institutions are reducing positions.
Key Insight: Institutional investors (hedge funds, pension funds, mutual funds) manage trillions of dollars and conduct extensive research. Their collective buying/selling patterns often precede significant price movements by 1-3 quarters.
When to Use This Skill
Use this skill when:
- Validating investment ideas (checking if smart money agrees with your thesis)
- Discovering new opportunities (finding stocks institutions are accumulating)
- Risk assessment (identifying stocks institutions are exiting)
- Portfolio monitoring (tracking institutional support for your holdings)
- Following specific investors (tracking Warren Buffett, Cathie Wood, etc.)
- Sector rotation analysis (identifying where institutions are rotating capital)
Do NOT use when:
- Seeking real-time intraday signals (13F data has 45-day reporting lag)
- Analyzing micro-cap stocks (<$100M market cap with limited institutional interest)
- Looking for short-term trading signals (<3 months horizon)
Data Sources & Requirements
Required: FMP API Key
This skill uses Financial Modeling Prep (FMP) API to access 13F filing data:
Setup:
export FMP_API_KEY=your_key_here
python3 scripts/track_institutional_flow.py --api-key YOUR_KEY
API Tier Requirements:
- Free Tier: 250 requests/day (sufficient for analyzing 20-30 stocks quarterly)
- Paid Tiers: Higher limits for extensive screening
13F Filing Schedule:
- Filed quarterly within 45 days after quarter end
- Q1 (Jan-Mar): Filed by mid-May
- Q2 (Apr-Jun): Filed by mid-August
- Q3 (Jul-Sep): Filed by mid-November
- Q4 (Oct-Dec): Filed by mid-February
Analysis Workflow
Step 1: Identify Stocks with Significant Institutional Changes
Execute the main screening script to find stocks with notable institutional activity:
Quick scan (top 50 stocks by institutional change):
python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
--top 50 \
--min-change-percent 10
Sector-focused scan:
python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
--sector Technology \
--min-institutions 20
Custom screening:
python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
--min-market-cap 2000000000 \
--min-change-percent 15 \
--top 100 \
--output institutional_flow_results.json
Output includes:
- Stock ticker and company name
- Current institutional ownership % (of shares outstanding)
- Quarter-over-quarter change in shares held
- Number of institutions holding
- Change in number of institutions (new buyers vs sellers)
- Top institutional holders
- Aggregate dollar value change
Step 2: Deep Dive on Specific Stocks
For detailed analysis of a specific stock's institutional ownership:
python3 institutional-flow-tracker/scripts/analyze_single_stock.py AAPL
This generates:
- Historical institutional ownership trend (8 quarters)
- List of all institutional holders with position changes
- Concentration analysis (top 10 holders' % of total institutional ownership)
- New positions vs increased vs decreased vs closed positions
- Quarterly flow chart (net shares added/removed)
- Comparison to sector average institutional ownership
Key metrics to evaluate:
- Ownership %: Higher institutional ownership (>70%) = more stability but limited upside
- Ownership Trend: Rising ownership = bullish, falling = bearish
- Concentration: High concentration (top 10 > 50%) = risk if they sell
- Quality of Holders: Presence of quality long-term investors (Berkshire, Fidelity) vs momentum funds
Step 3: Track Specific Institutional Investors
Follow the portfolio moves of specific hedge funds or investment firms:
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
--cik 0001067983 \
--name "Berkshire Hathaway"
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
--cik 0001579982 \
--name "ARK Investment Management"
CIK (Central Index Key) lookup:
Analysis output:
- Current portfolio holdings (top 50 positions)
- New positions added this quarter
- Positions completely sold
- Largest increases/decreases in existing positions
- Portfolio concentration and sector allocation changes
- Historical performance of their top picks
Step 4: Interpretation and Action
Read the references for interpretation guidance:
references/13f_filings_guide.md - Understanding 13F data and limitationsreferences/institutional_investor_types.md - Different investor types and their strategiesreferences/interpretation_framework.md - How to interpret institutional flow signals
Signal Strength Framework:
Strong Bullish (Consider buying):
- Institutional ownership increasing >15% QoQ
- Number of institutions increasing >10%
- Quality long-term investors adding positions
- Low current ownership (<40%) with room to grow
- Accumulation happening across multiple quarters
Moderate Bullish:
- Institutional ownership increasing 5-15% QoQ
- Mix of new buyers and sellers, net positive
- Current ownership 40-70%
Neutral:
- Minimal change in ownership (<5%)
- Similar number of buyers and sellers
- Stable institutional base
Moderate Bearish:
- Institutional ownership decreasing 5-15% QoQ
- More sellers than buyers
- High ownership (>80%) limiting new buyers
Strong Bearish (Consider selling/avoiding):
- Institutional ownership decreasing >15% QoQ
- Number of institutions decreasing >10%
- Quality investors exiting positions
- Distribution happening across multiple quarters
- Concentration risk (top holder selling large position)
Step 5: Portfolio Application
For new positions:
- Run institutional analysis on your stock idea
- Look for confirmation (institutions also accumulating)
- If strong bearish signals, reconsider or reduce position size
- If strong bullish signals, gain confidence in thesis
For existing holdings:
- Quarterly review after 13F filing deadlines
- Monitor for distribution (early warning system)
- If institutions are exiting, re-evaluate your thesis
- Consider trimming if widespread institutional selling
Screening workflow integration:
- Use Value Dividend Screener or other screeners to find candidates
- Run Institutional Flow Tracker on top candidates
- Prioritize stocks with institutional accumulation
- Avoid stocks with institutional distribution
Output Format
All analysis generates structured markdown reports saved to repository root:
Filename convention: institutional_flow_analysis_<TICKER/THEME>_<DATE>.md
Report sections:
- Executive Summary (key findings)
- Institutional Ownership Trend (current vs historical)
- Top Holders and Changes
- New Buyers vs Sellers
- Concentration Analysis
- Interpretation and Recommendations
- Data Sources and Timestamp
Limitations and Caveats
Data Lag:
- 13F filings have 45-day reporting delay
- Positions may have changed since filing date
- Use as confirming indicator, not leading signal
Coverage:
- Only institutions managing >$100M are required to file
- Excludes individual investors and smaller funds
- International institutions may not file 13F
Reporting Rules:
- Only long equity positions reported (no shorts, options, bonds)
- Holdings as of quarter-end snapshot
- Some positions may be confidential (delayed reporting)
Interpretation:
- Correlation ≠ causation (stocks can fall despite institutional buying)
- Consider overall market environment and fundamentals
- Combine with technical analysis and other skills
Advanced Use Cases
Insider + Institutional Combo:
- Look for stocks where both insiders AND institutions are buying
- Particularly powerful signal when aligned
Sector Rotation Detection:
- Track aggregate institutional flows by sector
- Identify early rotation trends before they appear in price
Contrarian Plays:
- Find quality stocks institutions are selling (potential value)
- Requires strong fundamental conviction
Smart Money Validation:
- Before major position, check if smart money agrees
- Gain confidence or find overlooked risks
References
The references/ folder contains detailed guides:
- 13f_filings_guide.md - Comprehensive guide to 13F SEC filings, what they include, reporting requirements, and data quality considerations
- institutional_investor_types.md - Different types of institutional investors (hedge funds, mutual funds, pension funds, etc.), their typical strategies, and how to interpret their moves
- interpretation_framework.md - Detailed framework for interpreting institutional ownership changes, signal quality assessment, and integration with other analysis
Script Parameters
track_institutional_flow.py
Main screening script for finding stocks with significant institutional changes.
Required:
--api-key: FMP API key (or set FMP_API_KEY environment variable)
Optional:
--top N: Return top N stocks by institutional change (default: 50)--min-change-percent X: Minimum % change in institutional ownership (default: 10)--min-market-cap X: Minimum market cap in dollars (default: 1B)--sector NAME: Filter by specific sector--min-institutions N: Minimum number of institutional holders (default: 10)--output FILE: Output JSON file path (default: institutional_flow_results.json)--sort-by FIELD: Sort by 'ownership_change', 'institution_count_change', 'dollar_value_change'
analyze_single_stock.py
Deep dive analysis on a specific stock's institutional ownership.
Required:
- Ticker symbol (positional argument)
--api-key: FMP API key (or set FMP_API_KEY environment variable)
Optional:
--quarters N: Number of quarters to analyze (default: 8, i.e., 2 years)--output FILE: Output markdown report path--compare-to TICKER: Compare institutional ownership to another stock
track_institution_portfolio.py
Track a specific institutional investor's portfolio changes.
Required:
--cik CIK: Central Index Key of the institution--name NAME: Institution name for report--api-key: FMP API key (or set FMP_API_KEY environment variable)
Optional:
--top N: Show top N holdings (default: 50)--min-position-value X: Minimum position value to include (default: 10M)--output FILE: Output markdown report path
Integration with Other Skills
Value Dividend Screener + Institutional Flow:
1. Run Value Dividend Screener to find candidates
2. For each candidate, check institutional flow
3. Prioritize stocks with rising institutional ownership
US Stock Analysis + Institutional Flow:
1. Run comprehensive fundamental analysis
2. Validate with institutional ownership trends
3. If institutions are selling, investigate why
Portfolio Manager + Institutional Flow:
1. Fetch current portfolio via Alpaca
2. Run institutional analysis on each holding
3. Flag positions with deteriorating institutional support
4. Consider rebalancing away from distribution
Technical Analyst + Institutional Flow:
1. Identify technical setup (e.g., breakout)
2. Check if institutional buying confirms
3. Higher conviction if both align
Best Practices
- Quarterly Reviews: Set calendar reminders for 13F filing deadlines
- Multi-Quarter Trends: Look for sustained trends (3+ quarters), not one-time changes
- Quality Over Quantity: Berkshire adding > 100 small funds adding
- Context Matters: Rising ownership in a falling stock may be value investors catching a falling knife
- Combine Signals: Never use institutional flow in isolation
- Update Your Data: Re-run analysis each quarter as new 13Fs are filed
Support & Resources
Note: This skill is designed for long-term investors (3-12 month horizon). For short-term trading, combine with technical analysis and other momentum indicators.
