Orderbook Functions - kScript Functions

Quick Jump:

sumBids()sumAsks()maxBidAmount()maxAskAmount()minBidAmount()minAskAmount()

Overview

Volume Analysis

Sum bid and ask volumes within specified depth percentages to gauge buying and selling pressure at different price levels.

• Total bid volume • Total ask volume • Depth filtering

Order Size Analysis

Identify maximum and minimum order sizes within the orderbook to spot large players and market microstructure patterns.

• Largest orders • Smallest orders • Size distribution

Market Depth

Analyze orderbook depth and liquidity distribution to understand support/resistance levels and potential price impact.

• Depth percentage • Liquidity zones • Order clustering

Functions Reference

sumBids - calculate total bid volume within depth

sumBids(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (total bid volume within depth)

Code Example:

sumAsks - calculate total ask volume within depth

sumAsks(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (total ask volume within depth)

Code Example:

maxBidAmount - find largest bid order within depth

maxBidAmount(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (largest bid order size within depth)

Code Example:

maxAskAmount - find largest ask order within depth

maxAskAmount(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (largest ask order size within depth)

Code Example:

minBidAmount - find smallest bid order within depth

minBidAmount(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (smallest bid order size within depth)

Code Example:

minAskAmount - find smallest ask order within depth

minAskAmount(source: TimeSeries, depthPct?: number = 10): number

Parameters:

source (TimeSeries) - Source orderbook data series
depthPct (number) - Depth percentage (default: 10)

Returns:

number (smallest ask order size within depth)

Code Example:

Best Practices

📊

Depth Analysis

Use smaller depth percentages (1-5%) to focus on top-of-book activity, larger percentages (10-20%) for overall market depth analysis.

⚖️

Volume Imbalance

Significant bid/ask volume imbalances often precede price movements. High bid volume suggests upward pressure, high ask volume suggests downward pressure.

🎯

Large Order Impact

Monitor maximum order sizes for signs of institutional activity. Sudden appearance of large orders can indicate significant market events.