Large Trade Frequency
Quick Reference
| Property | Value |
|---|---|
| Dimension | quality |
| Category | order_flow |
| Version | v1.0 |
| Output Column | large_trade_frequency |
Frequency of trades above a given size threshold 鈥?counts large trades per window
Formula
rolling_sum((size > size_threshold), window)
CDM Inputs
| Column | CDM Table | Description |
|---|---|---|
size | cdm_trade_enriched | Trade data enriched with bar context 鈥?price, volume, side, trade type |
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
size_threshold | float | 1000.0 | Minimum trade size to be considered large |
window | integer | 100 | Rolling window size (row count) for counting large trades |
Output
Column: large_trade_frequency
Count of trades above size threshold per rolling window
Market Intuition & Trading Rationale
Large trade frequency counts trades exceeding a size threshold per rolling window: rolling_sum(size > threshold, window). Large trades are the footprint of institutional activity 鈥?retail traders rarely execute in size. A spike in large trade frequency means institutions are active, and their direction (captured by signed_volume or trade_sign on those large trades) reveals informed positioning.
Large trades also consume more liquidity. When large_trade_frequency rises, market impact increases 鈥?these trades walk the book further. This makes it a useful leading indicator for execution costs: when institutions are active, your own execution costs will be higher because you're competing for the same liquidity.
Usage Cases
- Institutional activity detection: Rising large_trade_frequency signals institutional participation. Cross-reference with
signed_volumeon large trades 鈥?if institutions are predominantly buying, join the trend; if selling, fade or exit. - Execution cost forecasting: High large_trade_frequency 鈫?higher market impact for your orders. Widen your execution schedules or reduce order sizes during these periods.
- quality context: Used in
large_trade_pressurepack 鈥?large trade frequency provides the activity baseline; the pack's signal features (volume_above_percentile) capture the price impact of those large trades.
YAML Definition
name: large_trade_frequency
description: Frequency of trades above a given size threshold 鈥?counts large trades
per window
category: order_flow
dimension: quality
version: v0.9.0 (Beta)
required_inputs:
- size
output_column: large_trade_frequency
output_description: Count of trades above size threshold per rolling window
tags:
- quality
- flow
- volume
parameters:
size_threshold:
type: float
description: Minimum trade size to be considered large
required: false
default: 1000.0
window:
type: integer
description: Rolling window size (row count) for counting large trades
required: false
default: 100
formula: rolling_sum((size > size_threshold), window)