Get Bz News

Get Benzinga News

Fetch news where |daily_adj| >= threshold. Default threshold is 1.5σ of trailing adjusted volatility.

Arguments

$ARGUMENTS = TICKER START_DATE END_DATE [THRESHOLD]

• THRESHOLD optional: 1.5s (default), 2s, or fixed like 3 (percent)

Example: AAPL 2024-01-01T00:00:00 2024-04-01T00:00:00

Steps

Step 1: Calculate Volatility

MATCH (d:Date)-[r:HAS_PRICE]->(c:Company {ticker: $ticker})
WHERE d.date >= date($start) - duration('P365D') AND d.date < date($start)
MATCH (d)-[m:HAS_PRICE]->(idx:MarketIndex {ticker: 'SPY'})
WHERE r.daily_return IS NOT NULL AND m.daily_return IS NOT NULL
RETURN stdev(r.daily_return - m.daily_return) AS adj_vol, count(*) AS days

Fail if < 60 days: Return INSUFFICIENT_HISTORY: {days} days (need 60+)

Step 2: Compute Threshold

Parse THRESHOLD argument:

• 1.5s → threshold = 1.5 × adj_vol (default)
• 2s → threshold = 2.0 × adj_vol
• 3 → threshold = 3.0 (fixed percent, ignore volatility)

Step 3: Fetch News

Use threshold and adj_vol as literal parameters (no subquery):

MATCH (n:News)-[inf:INFLUENCES]->(c:Company {ticker: $ticker})
WHERE n.created >= $start AND n.created < $end
  AND inf.daily_stock IS NOT NULL AND inf.daily_macro IS NOT NULL
  AND abs(inf.daily_stock - inf.daily_macro) >= $threshold
RETURN n.id AS news_id,
       n.created AS date,
       n.title AS title,
       n.teaser AS teaser,
       n.body AS body,
       n.market_session AS market_session,
       inf.daily_stock AS daily_stock,
       (inf.daily_stock - inf.daily_macro) AS daily_adj,
       (inf.daily_stock - inf.daily_sector) AS sector_adj,
       (inf.daily_stock - inf.daily_industry) AS industry_adj,
       abs(inf.daily_stock - inf.daily_macro) / $adj_vol AS z_score
ORDER BY n.created ASC

Output

Return JSON with:

• query: parameters used (ticker, dates, threshold_pct, adj_vol)
• results: array of news items with z_score

If no results: NO_NEWS_FOUND