institutional-flow-tracker – OpenClaw Skill

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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.

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:

# Set environment variable (preferred)
export FMP_API_KEY=your_key_here

# Or provide when running scripts
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:

# Track Warren Buffett's Berkshire Hathaway
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001067983 \
  --name "Berkshire Hathaway"

# Track Cathie Wood's ARK Investment Management
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001579982 \
  --name "ARK Investment Management"

CIK (Central Index Key) lookup:

• Search at: https://www.sec.gov/cgi-bin/browse-edgar
• Or use FMP API institutional search

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 limitations
• references/institutional_investor_types.md - Different investor types and their strategies
• references/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:

1. Run institutional analysis on your stock idea
2. Look for confirmation (institutions also accumulating)
3. If strong bearish signals, reconsider or reduce position size
4. If strong bullish signals, gain confidence in thesis

For existing holdings:

1. Quarterly review after 13F filing deadlines
2. Monitor for distribution (early warning system)
3. If institutions are exiting, re-evaluate your thesis
4. Consider trimming if widespread institutional selling

Screening workflow integration:

1. Use Value Dividend Screener or other screeners to find candidates
2. Run Institutional Flow Tracker on top candidates
3. Prioritize stocks with institutional accumulation
4. 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:

1. Executive Summary (key findings)
2. Institutional Ownership Trend (current vs historical)
3. Top Holders and Changes
4. New Buyers vs Sellers
5. Concentration Analysis
6. Interpretation and Recommendations
7. 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

1. Quarterly Reviews: Set calendar reminders for 13F filing deadlines
2. Multi-Quarter Trends: Look for sustained trends (3+ quarters), not one-time changes
3. Quality Over Quantity: Berkshire adding > 100 small funds adding
4. Context Matters: Rising ownership in a falling stock may be value investors catching a falling knife
5. Combine Signals: Never use institutional flow in isolation
6. Update Your Data: Re-run analysis each quarter as new 13Fs are filed

Support & Resources

• FMP API Documentation: https://financialmodelingprep.com/developer/docs
• SEC 13F Filings Database: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&type=13F
• Institutional Investor Database: https://whalewisdom.com (free tier available)

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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.

Institutional Flow Tracker

Track institutional investor ownership changes and portfolio flows using 13F filings data to identify "smart money" accumulation and distribution patterns.

Overview

Institutional Flow Tracker analyzes SEC 13F filings to discover stocks where sophisticated investors (hedge funds, mutual funds, pension funds) are accumulating or distributing positions. By following where institutional money flows, you can:

• Discover opportunities before they become mainstream
• Validate investment ideas by checking if smart money agrees
• Get early warnings when quality investors exit positions
• Follow superinvestors like Warren Buffett, Seth Klarman, Bill Ackman

Key Insight: Institutional investors manage trillions of dollars and conduct extensive research. Their collective actions often precede major price movements by 1-3 quarters.

Features

✅ Stock Screening - Find stocks with significant institutional ownership changes (>10-15% QoQ) ✅ Deep Dive Analysis - Detailed quarterly trends, top holders, position changes for individual stocks ✅ Institution Tracking - Follow specific hedge funds/mutual funds portfolio moves ✅ Signal Quality Framework - Tier-based weighting system (superinvestors > active funds > index funds) ✅ Multi-Quarter Trends - Identify sustained accumulation/distribution (3+ quarters) ✅ Concentration Analysis - Assess ownership concentration risk ✅ FMP API Integration - Free tier (250 calls/day) sufficient for quarterly reviews

Prerequisites

Required: FMP API Key

This skill uses Financial Modeling Prep (FMP) API to access 13F filing data.

Setup:

# Set environment variable (recommended)
export FMP_API_KEY="your_key_here"

# Or provide via command-line when running scripts
python3 scripts/track_institutional_flow.py --api-key YOUR_KEY

Get API Key:

1. Visit: https://financialmodelingprep.com/developer/docs
2. Sign up for free account (250 requests/day)
3. Copy your API key

API Usage:

• Free tier: 250 requests/day (sufficient for analyzing 30-50 stocks quarterly)
• Each stock analysis uses 1-2 API calls
• Quarterly review workflow: ~50-100 API calls total

Installation

No installation required beyond Python 3 and the requests library:

pip install requests

Usage

1. Screen for Stocks with Institutional Changes

Find stocks with significant institutional activity:

Quick scan (top 50 stocks):

python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
  --top 50 \
  --min-change-percent 10

Sector-focused screening:

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_results.json

Output: Markdown report with top accumulators/distributors, detailed metrics, interpretation guide

2. Deep Dive on Specific Stock

Comprehensive analysis of institutional ownership for a single stock:

python3 institutional-flow-tracker/scripts/analyze_single_stock.py AAPL

Extended history (12 quarters):

python3 institutional-flow-tracker/scripts/analyze_single_stock.py MSFT --quarters 12

Output: Detailed report with quarterly trends, new/increased/decreased/closed positions, concentration analysis

3. Track Specific Institutional Investors

Follow portfolio changes of specific hedge funds or investment firms:

# Track Warren Buffett's Berkshire Hathaway
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001067983 \
  --name "Berkshire Hathaway"

# Track Cathie Wood's ARK Investment Management
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001579982 \
  --name "ARK Investment Management"

Finding CIK (Central Index Key):

• Search SEC EDGAR: https://www.sec.gov/cgi-bin/browse-edgar
• Or use FMP API institutional search

Output: Current portfolio holdings, new positions, exits, largest changes

Signal Interpretation Framework

Strong Buy Signal (95th percentile)

Criteria:

• Institutional ownership increasing >15% QoQ
• 3+ consecutive quarters of accumulation
• Multiple Tier 1/2 investors buying (clustering score >60)
• Quality long-term investors adding positions

Action: BUY with conviction (2-5% portfolio position)

Moderate Buy Signal (75th percentile)

Criteria:

• Institutional ownership increasing 7-15% QoQ
• 2 consecutive quarters of accumulation
• Mix of quality buyers

Action: BUY with moderate conviction (1-3% position)

Neutral Signal

Criteria:

• Institutional ownership change <5% QoQ
• No clear trend
• Mixed buyer/seller activity

Action: HOLD or decide based on other factors

Moderate/Strong Sell Signal

Criteria:

• Institutional ownership decreasing 7-15% QoQ (moderate) or >15% (strong)
• 2-3+ consecutive quarters of distribution
• Quality investors exiting

Action: TRIM/SELL positions, avoid new entries

Institutional Investor Quality Tiers

Tier 1 - Superinvestors (Weight: 3.0-3.5x):

• Warren Buffett (Berkshire Hathaway)
• Seth Klarman (Baupost Group)
• Bill Ackman (Pershing Square)
• David Tepper (Appaloosa Management)
• Patient capital, long-term oriented, concentrated portfolios

Tier 2 - Quality Active Managers (Weight: 2.0-2.5x):

• Fidelity Management & Research
• T. Rowe Price Associates
• Dodge & Cox
• Wellington Management
• Research-driven, solid track records

Tier 3 - Average Institutional (Weight: 1.0-1.5x):

• Regional mutual funds
• Most pension funds
• Benchmark-aware, committee-driven

Tier 4 - Passive/Mechanical (Weight: 0.0-0.5x):

• Index funds (Vanguard, BlackRock, State Street)
• Momentum/quant funds
• No fundamental views, follow index/price action

Workflow Examples

Quarterly Portfolio Review

Objective: Monitor institutional support for your holdings

1. Run institutional analysis on each holding after 13F filing deadlines
2. Flag positions with deteriorating institutional support
3. Re-evaluate thesis for positions showing Strong Sell signals
4. Consider trimming/exiting if quality investors are distributing

13F Filing Deadlines:

• Q1 (Jan-Mar): Mid-May
• Q2 (Apr-Jun): Mid-August
• Q3 (Jul-Sep): Mid-November
• Q4 (Oct-Dec): Mid-February

New Position Validation

Objective: Validate stock ideas with institutional data

1. Run fundamental analysis on stock candidate
2. Check institutional flow signal (accumulation or distribution?)
3. If Strong Buy signal: Gain confidence, initiate position
4. If Strong Sell signal: Reconsider or avoid
5. If Neutral: Decide based on fundamentals and technicals

Smart Money Replication

Objective: Follow superinvestor portfolio moves

1. Track Berkshire Hathaway, Baupost, other Tier 1 investors quarterly
2. Identify new positions or significant increases
3. Research the stock to understand their thesis
4. Initiate positions in highest-conviction ideas

Sector Rotation Detection

Objective: Identify early sector rotation trends

1. Calculate aggregate institutional flow by sector
2. Rank sectors by net institutional inflow/outflow
3. Compare to expected patterns based on economic cycle
4. Overweight sectors with institutional accumulation
5. Underweight/avoid sectors with distribution

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 Strong Buy institutional signal

US Stock Analysis + Institutional Flow:

1. Run comprehensive fundamental analysis
2. Validate with institutional ownership trends
3. If institutions selling despite strong fundamentals: investigate discrepancy

Portfolio Manager + Institutional Flow:

1. Fetch current portfolio via Alpaca
2. Run institutional analysis on each holding quarterly
3. Flag positions with deteriorating institutional support
4. Rebalance away from Strong Sell signals

Technical Analyst + Institutional Flow:

1. Identify technical setup (e.g., breakout, basing pattern)
2. Check if institutional buying confirms
3. Higher conviction if both technical + institutional signals align

Data Limitations

Reporting Lag:

• 13F filings due 45 days after quarter end
• Positions as of quarter-end snapshot
• Current positions may have changed since filing

Coverage:

• Only institutions managing >$100M file 13F
• Excludes individual investors and smaller funds
• Only long equity positions (no shorts, options, bonds)

Best Practices:

• Use as confirming indicator, not leading signal
• Look for multi-quarter trends (3+ quarters)
• Weight quality institutions heavily (Tier 1 > Tier 4)
• Combine with fundamental and technical analysis
• Update quarterly, not daily

Reference Materials

The references/ folder contains comprehensive guides:

• 13f_filings_guide.md - Understanding 13F SEC filings, reporting requirements, data quality considerations, common pitfalls
• institutional_investor_types.md - Different investor types (hedge funds, mutual funds, etc.), their strategies, quality tiers, weighting framework
• interpretation_framework.md - Systematic approach to interpreting signals, decision trees, multi-factor integration

Script Parameters Reference

track_institutional_flow.py

Required:

• --api-key or FMP_API_KEY environment variable

Optional:

• --top N - Return top N stocks (default: 50)
• --min-change-percent X - Minimum % ownership change (default: 10)
• --min-market-cap X - Minimum market cap in dollars (default: 1B)
• --sector NAME - Filter by sector
• --min-institutions N - Minimum institutional holders (default: 10)
• --sort-by FIELD - Sort by ownership_change/institution_count_change/dollar_value_change
• --output FILE - Output JSON file

analyze_single_stock.py

Required:

• Stock ticker symbol (positional argument)
• --api-key or FMP_API_KEY environment variable

Optional:

• --quarters N - Number of quarters to analyze (default: 8)
• --output FILE - Output markdown report path

track_institution_portfolio.py

Required:

• --cik CIK - Central Index Key of institution
• --name NAME - Institution name for report
• --api-key or FMP_API_KEY environment variable

Optional:

• --top N - Show top N holdings (default: 50)
• --output FILE - Output markdown report path

Notable Institutional Investors to Track

Tier 1 Superinvestors

Investor	CIK	Strategy	Track Because
Berkshire Hathaway (Warren Buffett)	0001067983	Value/Quality	Long-term compounders, patient capital
Baupost Group (Seth Klarman)	0001061768	Deep Value	Distressed opportunities, contrarian
Pershing Square (Bill Ackman)	0001336528	Activist/Value	Catalytic events, concentrated bets
Appaloosa Management (David Tepper)	0001079114	Value	Contrarian, high conviction
Third Point (Dan Loeb)	0001040273	Event-Driven	Catalyst-driven, activism

Tier 2 Quality Active Managers

Fund Family	CIK	Strategy	Track Because
Fidelity Management	0000315066	Growth & Value	Large analyst team, quality research
T. Rowe Price	0001113169	Growth	Bottom-up research, growth focus
Dodge & Cox	0000922614	Deep Value	Contrarian, value-oriented
ARK Investment (Cathie Wood)	0001579982	Disruptive Innovation	High-conviction tech/innovation bets

Support & Resources

• FMP API Documentation: https://financialmodelingprep.com/developer/docs
• SEC 13F Filings Database: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&type=13F
• WhaleWisdom (free tier): https://whalewisdom.com

License

Educational and research purposes. See repository license for details.