Utility Functions - kScript Functions

Quick Jump:

lowest()highest()sum()stddev()donchian()crossover()crossunder()cross()isnan()isnum()

Overview

Statistical Functions

Calculate statistical measures like standard deviation, highest/lowest values, and sums over specified periods for robust technical analysis.

• Standard deviation • Min/max values • Period sums

Cross Detection

Detect when time series cross above, below, or in either direction to identify trend changes and generate trading signals.

• Crossover detection • Crossunder detection • Bidirectional crosses

Support/Resistance Levels

Identify key price levels using mathematical functions that track highest highs and lowest lows over specified periods for breakout and reversal analysis.

• Dynamic channels • Breakout identification • Level confirmation

Type Checking

Validate data integrity and handle edge cases by checking for NaN values and ensuring numeric validity before performing calculations.

• NaN detection • Numeric validation • Error prevention

Functions Reference

lowest - find lowest value over specified period

lowest(source: TimeSeries, period?: number = 12, priceIndex?: number = 3): number

Parameters:

source (TimeSeries) - Source data series
period (number) - Number of periods to look back (default: 12)
priceIndex (number) - Index of price data (default: 3 for low)

Returns:

number (lowest value in the specified period)

Code Example:

highest - find highest value over specified period

highest(source: TimeSeries, period?: number = 12, priceIndex?: number = 2): number

Parameters:

source (TimeSeries) - Source data series
period (number) - Number of periods to look back (default: 12)
priceIndex (number) - Index of price data (default: 2 for high)

Returns:

number (highest value in the specified period)

Code Example:

sum - calculate sum of values over specified period

sum(source: TimeSeries, period?: number = 12, priceIndex?: number = 1): number

Parameters:

source (TimeSeries) - Source data series
period (number) - Number of periods to sum (default: 12)
priceIndex (number) - Index of price data (default: 1)

Returns:

number (sum of values in the specified period)

Code Example:

stddev - calculate standard deviation of values

stddev(source: TimeSeries, period?: number = 12, priceIndex?: number = 1): number

Parameters:

source (TimeSeries) - Source data series
period (number) - Number of periods for calculation (default: 12)
priceIndex (number) - Index of price data (default: 1)

Returns:

number (standard deviation value)

Code Example:

donchian - Donchian Channel midpoint calculation

donchian(source: TimeSeries, period?: number = 12): number

Parameters:

source (TimeSeries) - Source data series
period (number) - Number of periods (default: 12)

Returns:

number (Donchian Channel midpoint value)

Code Example:

crossover - detect when series A crosses above series B

crossover(seriesA: TimeSeries, seriesB: TimeSeries): boolean

Parameters:

seriesA (TimeSeries) - First series (e.g., fast moving average)
seriesB (TimeSeries) - Second series (e.g., slow moving average)

Returns:

boolean (true if A crosses above B at the current bar)

Code Example:

crossunder - detect when series A crosses below series B

crossunder(seriesA: TimeSeries, seriesB: TimeSeries): boolean

Parameters:

seriesA (TimeSeries) - First series
seriesB (TimeSeries) - Second series

Returns:

boolean (true when A crosses below B)

Code Example:

cross - detect when series A crosses series B in either direction

cross(seriesA: TimeSeries, seriesB: TimeSeries): boolean

Parameters:

seriesA (TimeSeries) - First series
seriesB (TimeSeries) - Second series

Returns:

boolean (true when any cross occurs)

Code Example:

isnan - check if a value is NaN (Not a Number)

isnan(value: any): boolean

Parameters:

value (any) - Value to check for NaN

Returns:

boolean (true if value is NaN, false otherwise)

Code Example:

isnum - check if a value is a valid finite number

isnum(value: any): boolean

Parameters:

value (any) - Value to check for numeric validity

Returns:

boolean (true if value is a valid finite number, false otherwise)

Code Example:

Best Practices

📊

Lookback Periods

Choose appropriate lookback periods based on your timeframe. Shorter periods for scalping, longer periods for swing trading.

⚡

Performance

Statistical functions can be computationally expensive. Cache results when calculating multiple statistics on the same data.

🎯

Cross Detection

Use crossover() for bullish signals, crossunder() for bearish signals, and cross() when you need to detect any direction change. Always combine with trend confirmation.

📈

Donchian Channels

Donchian channels work best in trending markets for breakout strategies. In ranging markets, use them as support/resistance levels rather than breakout signals.

⚠️

False Signals

Cross functions can generate false signals in choppy markets. Use additional filters like volume confirmation or trend direction to improve signal quality.

🔍

Data Validation

Always validate data using isnan() and isnum() before performing calculations. Invalid data can propagate through indicators and cause incorrect results.