Free Insider Trading & Institutional Flow API
Track what company insiders and big institutions are doing with their own money. Our API aggregates SEC Form 4 insider transactions and 13F institutional filings into a single endpoint with buy/sell ratios and flow direction.
Endpoint
GET https://securitiesdb.com/api/v1/stocks/{ticker}/insider-activityWhy Insider Trading Data Matters
Company insiders — CEOs, CFOs, directors, and 10% owners — are required by SEC Rule 16a to disclose trades within 2 business days via Form 4. Academic research consistently shows insider purchases predict positive excess returns.
Cluster Buys: Multiple insiders buying within 30 days is a strong bullish signal
Officer Sells: Large sales by C-suite often precede underperformance
Sources: Lakonishok & Lee (2001), Jeng et al. (2003), Cohen et al. (2012)
Response Fields
| Field | Description |
|---|---|
| insider_transactions.net_buy_sell_ratio | Net ratio of insider buys to sells (>1 = net buying) |
| insider_transactions.recent[] | Array of recent Form 4 transactions with insider name, type, shares, value |
| institutional_flow[] | Top institutional position changes from 13F filings |
Python Example — Insider Cluster Buy Scanner
import requests
# Scan a watchlist for insider cluster buying
watchlist = ["AAPL", "GOOGL", "AMZN", "META", "TSLA", "NVDA", "JPM", "BAC"]
clusters = []
for ticker in watchlist:
r = requests.get(f"https://securitiesdb.com/api/v1/stocks/{ticker}/insider-activity")
if r.status_code != 200:
continue
data = r.json()["data"]
txns = data.get("insider_transactions", {})
ratio = txns.get("net_buy_sell_ratio", 0)
if ratio > 1.5: # Net buying exceeds selling by 50%+
clusters.append({
"ticker": ticker,
"ratio": ratio,
"recent_count": len(txns.get("recent", [])),
})
print(f"Insider cluster buying detected in {len(clusters)} stocks:")
for c in clusters:
print(f" {c['ticker']}: Buy/Sell ratio = {c['ratio']:.2f} "
f"({c['recent_count']} recent transactions)")