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