ta

Properties

accdist

Type: series float

Accumulation/Distribution Line (ADL).

It measures the cumulative flow of money into and out of a security.

iii

Type: series float

Intraday Intensity Index (III).

It measures the flow of volume into and out of a security.

nvi

Type: series float

Negative Volume Index (NVI).

It focuses on days when the volume decreases compared to the previous day.

obv

Type: const float

On-Balance Volume (OBV).

It measures buying and selling pressure as a cumulative indicator that adds volume on up days and subtracts volume on down days.

pvi

Type: const float

Positive Volume Index (PVI).

It focuses on days when the volume increases compared to the previous day.

pvt

Type: const float

Price Volume Trend (PVT).

It combines price and volume to determine the strength of price movements.

tr

Type: series float

True Range (TR) with na handling enabled.

Equivalent to ta.tr(handle_na = true).

vwap

Type: series float

Daily Volume Weighted Average Price using hlc3 as source.

Resets at the start of each day. This is the standard VWAP used on most trading platforms.

wad

Type: const float

Williams Accumulation/Distribution (WAD).

It measures buying and selling pressure by comparing the close price to the high-low range.

wvad

Type: const float

Williams Variable Accumulation/Distribution (WVAAD).

It adjusts the accumulation/distribution calculation by considering the position of the close price within the true range.

Functions

alma

pine

ta.alma(
    series float series,
    series int length,
    simple float offset,
    simple float sigma,
    simple bool floor = false
  ) → series float

Arnaud Legoux Moving Average.

It uses Gaussian distribution as weights for moving average.

Parameters

Name	Type	Default	Description
`series`	`series float`		Series of values to process.
`length`	`series int`		Number of bars (length).
`offset`	`simple float`		Controls tradeoff between smoothness (closer to 1) and responsiveness (closer to 0).
`sigma`	`simple float`		Changes the smoothness of ALMA. The larger sigma the smoother ALMA.
`floor`	`simple bool`	`false`	Specifies whether the offset calculation is floored before ALMA is calculated.

Returns: series float

atr

pine

ta.atr(simple int length) → series float

Calculates the Average True Range (ATR) of a financial instrument over a specified length.

Parameters

Name	Type	Default	Description
`length`	`simple int`		The number of bars for the ATR calculation.

Returns: series float

barssince

pine

ta.barssince(series bool condition) → series int

Counts the number of bars since the last time the condition was true.

If the condition has never been true, it returns na.

Parameters

Name	Type	Default	Description
`condition`	`series bool`		The boolean condition to check.

Returns: series int — The number of bars since the condition was last true, or na if it has never been true.

bb

pine

ta.bb(series float series, series int length, simple float mult)

Bollinger Bands (BB).

Parameters

Name	Type	Description
`series`	`series float`	The input series for BB calculation.
`length`	`series int`	The number of bars for the calculation.
`mult`	`simple float`	The multiplier for the standard deviation bands.

Returns: A tuple of [basis, upper, lower] where basis is the SMA, upper/lower are basis ± mult × stdev.

bbw

pine

ta.bbw(series float source, series int length, simple float mult) → series float

Bollinger Band Width (BBW).

It measures the width of the Bollinger Bands relative to the moving average.

Parameters

Name	Type	Description
`source`	`series float`	The input series for BBW calculation.
`length`	`series int`	The number of bars for the calculation.
`mult`	`simple float`	The multiplier for the standard deviation bands.

Returns: series float — The bandwidth as a percentage: (upper - lower) / basis × 100.

cci

pine

ta.cci(series float source, series int length) → series float

Commodity Channel Index (CCI).

It measures the deviation of the series series from its statistical mean.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

change

Calculates the difference between the current source value and its value length bars ago.

Useful for measuring momentum or rate of change.

Parameters

Name	Type	Default	Description
`source`	`series int`		The integer series to compare.
`length`	`series int`	`1`	Number of bars to look back. Defaults to 1 (previous bar).

Returns: series int — source - source[length].

Name	Type	Default	Description
`source`	`series float`		The float series to compare.
`length`	`series int`	`1`	Number of bars to look back. Defaults to 1 (previous bar).

Name	Type	Default	Description
`source`	`series bool`		The boolean series to compare.
`length`	`series int`	`1`	Number of bars to look back. Defaults to 1 (previous bar).

cmo

pine

ta.cmo(series float series, series int length) → series float

Chande Momentum Oscillator (CMO).

It measures the momentum of the series series over the specified length.

Parameters

Name	Type	Default	Description
`series`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float — A value between -100 and 100. Positive values indicate upward momentum, negative indicate downward.

cog

pine

ta.cog(series float source, series int length) → series float

Center of Gravity (COG).

It identifies the center of gravity of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

correlation

pine

ta.correlation(
    series float source1,
    series float source2,
    series int length
  ) → series float

Pearson Correlation Coefficient between two series over the specified length.

Parameters

Name	Type	Description
`source1`	`series float`	The first input series.
`source2`	`series float`	The second input series.
`length`	`series int`	The number of bars for the calculation.

Returns: series float — A value between -1.0 (perfectly negatively correlated) and 1.0 (perfectly positively correlated). 0.0 indicates no linear correlation.

cross

pine

ta.cross(series float source1, series float source2) → series bool

Detects if source1 has crossed source2 in either direction.

Parameters

Name	Type	Default	Description
`source1`	`series float`		The first series to compare.
`source2`	`series float`		The second series to compare.

Returns: series bool

crossover

pine

ta.crossover(series float source1, series float source2) → series bool

Detects if source1 has crossed over source2.

Parameters

Name	Type	Default	Description
`source1`	`series float`		The first series to compare.
`source2`	`series float`		The second series to compare.

Returns: series bool

crossunder

pine

ta.crossunder(series float source1, series float source2) → series bool

Detects if source1 has crossed under source2.

Parameters

Name	Type	Default	Description
`source1`	`series float`		The first series to compare.
`source2`	`series float`		The second series to compare.

Returns: series bool

cum

pine

ta.cum(series float source) → series float

Cumulative sum of the source series.

In other words it's a sum of all elements of the source series.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to accumulate.

Returns: series float

dev

pine

ta.dev(series float source, series int length) → series float

Mean Deviation of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

dmi

pine

ta.dmi(series float diLength, series int adxSmoothing)

Directional Movement Index (DMI).

Parameters

Name	Type	Default	Description
`diLength`	`series float`		The length for Directional Indicator calculation.
`adxSmoothing`	`series int`		The smoothing length for ADX calculation.

Returns: A tuple of [plus_di, minus_di, adx], all expressed as percentages (0–100).

ema

pine

ta.ema(series float source, simple int length) → series float

Exponential Moving Average (EMA).

It gives more weight to recent prices to make it more responsive to new information.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`simple int`		The number of bars for the calculation.

Returns: series float

falling

pine

ta.falling(series float source, series int length) → series bool

Checks if the source series is falling over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to check.
`length`	`series int`		The number of bars to check.

Returns: series bool

highest

Returns the highest value of the high series over the specified length.

Parameters

Name	Type	Default	Description
`length`	`series int`		The number of bars to check.

Returns: series float

highestbars

Returns the number of bars since the highest value of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars to check.

Returns: series int — A non-positive offset (0 if the highest is the current bar, negative otherwise), or na if any value in the window is na.

hma

pine

ta.hma(series float source, simple int length) → series float

Hull Moving Average (HMA).

It aims to reduce lag while maintaining a smooth curve.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`simple int`		The number of bars for the calculation.

Returns: series float

kc

pine

ta.kc(
    series float series,
    simple int length,
    simple float mult,
    simple bool useTrueRange = true
  )

Keltner Channels (KC).

Parameters

Name	Type	Default	Description
`series`	`series float`		The input series for KC calculation.
`length`	`simple int`		The number of bars for the calculation.
`mult`	`simple float`		The multiplier for the channel bands.
`useTrueRange`	`simple bool`	`true`	Whether to use True Range.

Returns: A tuple of [basis, upper, lower] where basis is the EMA, upper/lower are basis ± mult × range EMA.

kcw

pine

ta.kcw(
    series float series,
    simple int length,
    simple float mult,
    simple bool useTrueRange = true
  ) → series float

Keltner Channel Width (KCW).

It measures the width of the Keltner Channels relative to the moving average.

Parameters

Name	Type	Default	Description
`series`	`series float`		The input series for KCW calculation.
`length`	`simple int`		The number of bars for the calculation.
`mult`	`simple float`		The multiplier for the channel bands.
`useTrueRange`	`simple bool`	`true`	Whether to use True Range.

Returns: series float — The channel width as a ratio: (upper - lower) / basis.

linreg

pine

ta.linreg(
    series float source,
    series int length,
    simple int offset
  ) → series float

Linear Regression (LINREG).

It fits a linear regression line to the source series over the specified length and returns the value at the given offset.

Parameters

Name	Type	Description
`source`	`series float`	The input series for the calculation.
`length`	`series int`	The number of bars for the regression.
`offset`	`simple int`	The offset for the regression line (future bar offset).

Returns: series float

lowest

Returns the lowest value of the low series over the specified length.

Parameters

Name	Type	Default	Description
`length`	`series int`		The number of bars to check.

Returns: series float

lowestbars

Returns the number of bars since the lowest value of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars to check.

Returns: series int — A non-positive offset (0 if the lowest is the current bar, negative otherwise), or na if any value in the window is na.

macd

pine

ta.macd(
    series float source,
    simple int fast_length,
    simple int slow_length,
    simple int signal_length
  )

Moving Average Convergence Divergence (MACD).

Parameters

Name	Type	Description
`source`	`series float`	The input series for the calculation.
`fast_length`	`simple int`	The length for the fast EMA.
`slow_length`	`simple int`	The length for the slow EMA.
`signal_length`	`simple int`	The length for the signal line EMA.

Returns: A tuple of [macd_line, signal_line, histogram] where histogram = macd_line − signal_line.

max

pine

ta.max(series float source) → series float

Returns the maximum value of the source series.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.

Returns: series float

median

pine

ta.median(series float source, series int length) → series float

Returns the median value of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

mfi

pine

ta.mfi(series float series, series int length) → series float

Money Flow Index (MFI).

It measures the inflow and outflow of money into an asset over the specified length.

Parameters

Name	Type	Default	Description
`series`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float — A value between 0 and 100. Values above 80 indicate overbought conditions, below 20 indicate oversold.

min

pine

ta.min(series float source) → series float

Returns the minimum value of the source series.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.

Returns: series float

mode

pine

ta.mode(series float source, series int length) → series float

Returns the mode (most frequently occurring value) of the series series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

mom

pine

ta.mom(series float source, series int length) → series float

Calculates the momentum of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

percentile_linear_interpolation

pine

ta.percentile_linear_interpolation(
    series float source,
    series int length,
    simple float percentage
  ) → series float

Returns the percentile value of the source series over the specified length using linear interpolation.

Parameters

Name	Type	Description
`source`	`series float`	The input series to evaluate.
`length`	`series int`	The number of bars for the calculation.
`percentage`	`simple float`	The percentile value (0-100).

Returns: series float

percentile_nearest_rank

pine

ta.percentile_nearest_rank(
    series float source,
    series int length,
    simple float percentage
  ) → series float

Returns the percentile value of the source series over the specified length using the nearest-rank method.

Parameters

Name	Type	Description
`source`	`series float`	The input series to evaluate.
`length`	`series int`	The number of bars for the calculation.
`percentage`	`simple float`	The percentile value (0-100).

Returns: series float

percentrank

pine

ta.percentrank(series float source, series int length) → series float

Returns the percentile rank of the current value in the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars for the calculation.

Returns: series float — A value between 0 and 100 indicating the percentage of values that are less than or equal to the current value.

pivothigh

Returns the price of the pivot high point.

It returns 'NaN', if there was no pivot high point.

Parameters

Name	Type	Description
`source`	`series float`	The input series to analyze.
`leftbars`	`series int`	The number of bars to the left to check.
`rightbars`	`series int`	The number of bars to the right to check.

Returns: series float — The pivot high price (offset by rightbars), or na if no pivot is found at that point.

Name	Type	Default	Description
`leftbars`	`series int`		The number of bars to the left to check.
`rightbars`	`series int`		The number of bars to the right to check.

pivotlow

Returns the price of the pivot low point.

It returns 'NaN', if there was no pivot low point.

Parameters

Name	Type	Description
`source`	`series float`	The input series to analyze.
`leftbars`	`series int`	The number of bars to the left to check.
`rightbars`	`series int`	The number of bars to the right to check.

Returns: series float — The pivot low price (offset by rightbars), or na if no pivot is found at that point.

Name	Type	Default	Description
`leftbars`	`series int`		The number of bars to the left to check.
`rightbars`	`series int`		The number of bars to the right to check.

range

pine

ta.range(series float source, series int length) → series float

Returns the range (difference between highest and lowest) of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to evaluate.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

rci

pine

ta.rci(series float source, simple int length) → series float

Rank Correlation Index (RCI).

It measures the strength and direction of a linear relationship between the ranks of two variables over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`simple int`		The number of bars for the calculation.

Returns: series float — A value between -100 and 100. +100 means prices are perfectly rising, -100 means perfectly falling.

rising

pine

ta.rising(series float source, series int length) → series bool

Checks if the source series is rising over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series to check.
`length`	`series int`		The number of bars to check.

Returns: series bool

rma

pine

ta.rma(series float source, series int length) → series float

Recursive Moving Average (RMA).

It is similar to an Exponential Moving Average (EMA) but uses a different smoothing factor.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The length for the RMA calculation.

Returns: series float

roc

pine

ta.roc(series float source, series int length) → series float

Rate of Change (ROC).

It measures the percentage change between the current value and the value length bars ago.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the comparison.

Returns: series float — The percentage change: 100 × (source − source[length]) / source[length].

rsi

pine

ta.rsi(series float source, series int length) → series float

Relative Strength Index (RSI).

It measures the speed and change of price movements over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float — A value between 0 and 100. Values above 70 typically indicate overbought, below 30 oversold.

sar

pine

ta.sar(simple float start, simple float inc, simple float max) → series float

Parabolic SAR.

Parameters

Name	Type	Description
`start`	`simple float`	The starting acceleration factor.
`inc`	`simple float`	The increment for the acceleration factor.
`max`	`simple float`	The maximum acceleration factor.

Returns: series float — The SAR value for the current bar.

sma

pine

ta.sma(series float source, series int length) → series float

Simple Moving Average (SMA).

Calculates the average of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

stdev

pine

ta.stdev(
    series float source,
    series int length,
    series bool biased = true
  ) → series float

Calculates the standard deviation of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.
`biased`	`series bool`	`true`	If true, function will calculate using a biased estimate of the entire population, if false - unbiased estimate of a sample.

Returns: series float

stoch

pine

ta.stoch(
    series float source,
    series float high,
    series float low,
    series int length
  ) → series float

Stochastic Oscillator (STOCH).

It compares the source series to its price range over the specified length.

Parameters

Name	Type	Description
`source`	`series float`	The input series for the calculation.
`high`	`series float`	The high series for the range.
`low`	`series float`	The low series for the range.
`length`	`series int`	The number of bars for the calculation.

Returns: series float — A value between 0 and 100 representing the position of the source within the high-low range.

supertrend

pine

ta.supertrend(series float factor, simple int atrPeriod)

SuperTrend indicator.

Parameters

Name	Type	Default	Description
`factor`	`series float`		The multiplier for ATR in the SuperTrend calculation.
`atrPeriod`	`simple int`		The period for ATR calculation.

Returns: A tuple of [super_trend, direction] where direction is -1 (uptrend/bullish) or 1 (downtrend/bearish).

swma

pine

ta.swma(series float source) → series float

Smoothed Weighted Moving Average (SWMA).

It applies weighted moving average smoothing to the source series.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.

Returns: series float

tr

pine

ta.tr(simple bool handle_na) → series float

True Range (TR).

Measures volatility by accounting for gaps between bars. TR is the greatest of: (high - low), |high - previous close|, |low - previous close|. This captures overnight gaps and limit moves that high-low alone would miss.

Parameters

Name	Type	Default	Description
`handle_na`	`simple bool`		If true and previous close is `na` (first bar), uses `high - low` as TR. If false, returns `na` in that case.

Returns: series float

tsi

pine

ta.tsi(
    series float source,
    simple int short_length,
    simple int long_length
  ) → series float

True Strength Index (TSI).

Parameters

Name	Type	Description
`source`	`series float`	The input series for the calculation.
`short_length`	`simple int`	The short EMA length for TSI calculation.
`long_length`	`simple int`	The long EMA length for TSI calculation.

Returns: series float — A value between -1.0 and 1.0 representing momentum strength and direction.

valuewhen

pine

ta.valuewhen(
    series bool condition,
    series T source,
    simple int occurrence
  ) → series T

Returns the value of the source series at the time when the condition was true for the specified occurrence.

The occurrence parameter selects which match to return: 0 for the most recent, 1 for the one before that, etc.

Parameters

Name	Type	Description
`condition`	`series bool`	The condition to evaluate.
`source`	`series T`	The series to retrieve the value from.
`occurrence`	`simple int`	Which occurrence to retrieve (0 for the most recent).

Returns: series T — The source value at the specified occurrence, or na if fewer matches have occurred.

variance

pine

ta.variance(
    series float source,
    series int length,
    series bool biased = true
  ) → series float

Variance of the source series over the specified length.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.
`biased`	`series bool`	`true`	If true, uses biased estimation; if false, uses unbiased estimation.

Returns: series float

vwap

Volume Weighted Average Price with optional standard deviation bands.

VWAP accumulates since the anchor resets (typically daily) and weights price by volume, giving a benchmark that institutions often use. Returns a tuple of [vwap, upper_band, lower_band] where bands are vwap +/- stdev_mult * stddev.

Parameters

Name	Type	Description
`source`	`series float`	The price series (commonly hlc3).
`anchor`	`series bool`	When true, resets the VWAP calculation. Typically `timeframe.change("1D")`.
`stdev_mult`	`series float`	Multiplier for standard deviation bands. Use `na` to disable bands.

Returns: A tuple of [vwap, upper_band, lower_band]. Bands are na when stdev_mult is na.

vwma

pine

ta.vwma(series float source, series int length) → series float

Volume Weighted Moving Average (VWMA).

It gives more weight to periods with higher volume.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

wma

pine

ta.wma(series float source, series int length) → series float

Weighted Moving Average (WMA).

It assigns more weight to recent data points.

Parameters

Name	Type	Default	Description
`source`	`series float`		The input series for the calculation.
`length`	`series int`		The number of bars for the calculation.

Returns: series float

wpr

pine

ta.wpr(series int length) → series float

Williams Percent Range (WPR).

It measures overbought and oversold levels by comparing the close price to the high-low range over the specified length.

Parameters

Name	Type	Default	Description
`length`	`series int`		The number of bars for the calculation.

Returns: series float — A value between -100 and 0. Values above -20 indicate overbought, below -80 indicate oversold.

ta ​

Properties ​

accdist ​

iii ​

nvi ​

obv ​

pvi ​

pvt ​

tr ​

vwap ​

wad ​

wvad ​

Functions ​

alma ​

atr ​

barssince ​

bb ​

bbw ​

cci ​

change ​

cmo ​

cog ​

correlation ​

cross ​

crossover ​

crossunder ​

cum ​

dev ​

dmi ​

ema ​

falling ​

highest ​

highestbars ​

hma ​

kc ​

kcw ​

linreg ​

lowest ​

lowestbars ​

macd ​

max ​

median ​

mfi ​

min ​

mode ​

mom ​

percentile_linear_interpolation ​

percentile_nearest_rank ​

percentrank ​

pivothigh ​

pivotlow ​

range ​

rci ​

rising ​

rma ​

roc ​

rsi ​

sar ​

sma ​

stdev ​

stoch ​

supertrend ​

swma ​

tr ​

tsi ​

valuewhen ​

variance ​

vwap ​

vwma ​

wma ​

wpr ​

ta

Properties

accdist

iii

nvi

obv

pvi

pvt

tr

vwap

wad

wvad

Functions

alma

atr

barssince

bb

bbw

cci

change

cmo

cog

correlation

cross

crossover

crossunder

cum

dev

dmi

ema

falling

highest

highestbars

hma

kc

kcw

linreg

lowest

lowestbars

macd

max

median

mfi

min

mode

mom

percentile_linear_interpolation

percentile_nearest_rank

percentrank

pivothigh

pivotlow

range

rci

rising

rma

roc

rsi

sar

sma

stdev

stoch

supertrend

swma

tr

tsi

valuewhen

variance

vwap

vwma

wma

wpr