Trade Intensity

Quick Reference

Property	Value
Dimension	execution
Category	order_flow
Version	v0.9.0 (Beta)
Output Column	trade_intensity

Trade intensity: rolling count of trades - how frequently the market is executing transactions

Formula

rolling_sum(trade_count, window)

CDM Inputs

Column	CDM Table	Description
trade_count	cdm_trade_enriched	Trade data enriched with bar context 鈥?price, volume, side, trade type

Parameters

Parameter	Type	Default	Description
window	integer [1, 1000]	30	Rolling window size for trade counting

Output

Column: trade_intensity

Number of trades over the rolling window

Market Intuition & Trading Rationale

Trade intensity counts how many trades execute over a rolling window 鈥?it measures the pace of market activity independent of volume. A market can have high volume but low intensity (a few very large trades) or low volume but high intensity (many small trades). Intensity captures the fragmentation and arrival rate of orders, which volume alone misses.

High intensity with normal volume means the order flow is fragmented 鈥?many small participants trading. This is typical of retail-heavy periods or algorithmic market making activity. Low intensity with normal volume means concentrated flow 鈥?a few large institutional orders dominating. High intensity with high volume means broad participation 鈥?many traders across all size ranges, typical of news events and open/close auctions.

Intensity correlates with information arrival. When new information hits the market, trade intensity spikes before volume and volatility adjust 鈥?everyone wants to trade immediately. This makes trade intensity a leading indicator for volatility and a useful input for regime detection.

Usage Cases

• Volume confirmation: Use trade_intensity alongside volume-based features. High volume with high intensity = broad participation (more reliable signal). High volume with low intensity = concentrated flow (potential large trader 鈥?be cautious of adverse selection).
• Execution timing: Schedule executions during high-intensity periods 鈥?more counterparties means less slippage per order. Avoid low-intensity periods where your order may be the only significant flow and will have outsized impact.
• Toxicity context: In the trade_toxicity feature set, trade_intensity provides the activity baseline for VPIN calculation. VPIN divides volume into buckets 鈥?intensity determines how quickly buckets fill and thus how frequently VPIN updates.
• Regime transition early warning: Trade intensity often spikes before volatility regimes change. A sudden intensity surge with normal volatility suggests information is arriving but hasn't yet been priced 鈥?a potential entry signal.

YAML Definition

name: trade_intensity
description: 'Trade intensity: rolling count of trades - how frequently the market
  is executing transactions'
category: order_flow
version: v0.9.0 (Beta)
dimension: execution
status: Pre-release
required_inputs:
- trade_count
output_column: trade_intensity
output_description: Number of trades over the rolling window
parameters:
  window:
    type: integer
    description: Rolling window size for trade counting
    required: false
    default: 30
    constraints:
      min: 1
      max: 1000
formula: rolling_sum(trade_count, window)