Signals

ROC — Rate of Change

Measure percentage price acceleration over a configurable lookback.

What it is

Rate of Change measures percentage price change versus a prior bar. Positive values signal acceleration higher; negative values signal deceleration or outright downside momentum.

When to use it

Ranking symbols by medium-term momentum strength.
Comparing price acceleration across sectors or factor baskets.
Filtering out breakouts that lack meaningful follow-through.

The maths

ROC(N) = ((close[t] - close[t-N]) / close[t-N]) × 100 This is the percentage change over N bars.

What it tells you

Positive ROC signals upward price acceleration. Crossing zero from below can mark a bullish shift, and divergence from price is a classic momentum warning signal.

REST example

python

import os
import requests

response = requests.get(
  'https://api.financedata.com/v1/signals/ROC/QQQ',
  params={'start_date': '2025-01-01', 'end_date': '2025-04-30', 'period': 12},
  headers={'X-API-Key': os.environ['FDA_KEY']},
  timeout=30,
)
response.raise_for_status()
print(response.json())

MCP example

Tool call body

{
"name": "run_signals",
"arguments": {
  "symbols": ["QQQ"],
  "signal_names": ["ROC"],
  "start_date": "2025-01-01",
  "end_date": "2025-04-30",
  "signal_parameters": {
    "ROC": { "period": 12 }
  }
}
}

ROC is especially useful in MCP batches when you want one clean percentage-momentum series that can be compared across several symbols.

Agent prompt that triggers it

Run 12-day ROC for QQQ and summarize whether momentum is accelerating, fading, or flipping negative into the latest bar.