ta

Types

Name	Description
PivotType	Pivot point calculation method for ta.pivot_point_levels.

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

ta.alma(
    series: series float,
    length: series int,
    offset: simple float,
    sigma: simple float,
    floor: simple bool = 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

ta.atr(length: simple int): 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

---

bars_since

ta.bars_since(condition: series bool): 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

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

Bollinger Bands (BB).

Parameters

Name	Type	Default	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.

Examples

let (bbBasis, bbUpper, bbLower) = ta.bb(close, 20, 2.0);
plot(bbBasis, title: "BB Basis", color: color.ORANGE);
plot(bbUpper, title: "BB Upper", color: color.BLUE);
plot(bbLower, title: "BB Lower", color: color.BLUE);

---

bbw

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

Bollinger Band Width (BBW).

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

Parameters

Name	Type	Default	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

ta.cci(source: series float, length: series int): 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].

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

Parameters

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).

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

Detects if a boolean value has changed from its value length bars ago.

Useful for detecting state transitions (e.g., signal flips).

Parameters

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).

Returns: series bool — true if the current value differs from the historical value, false otherwise.

---

cmo

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

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

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

Pearson Correlation Coefficient between two series over the specified length.

Parameters

Name	Type	Default	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

ta.cross(source1: series float, source2: series float): 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

---

cross_over

ta.cross_over(source1: series float, source2: series float): 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

Examples

let fastEma = ta.ema(close, 9);
let slowEma = ta.ema(close, 21);
if ta.cross_over(fastEma, slowEma) {
label.new(bar_index, low, "Buy", style: LabelStyle.Up);
}

---

cross_under

ta.cross_under(source1: series float, source2: series float): 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

Examples

let fastEma = ta.ema(close, 9);
let slowEma = ta.ema(close, 21);
if ta.cross_under(fastEma, slowEma) {
label.new(bar_index, high, "Sell", style: LabelStyle.Down);
}

---

cum

ta.cum(source: series float): 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

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

ta.dmi(di_length: simple int, adx_smoothing: simple int)

Directional Movement Index (DMI).

Parameters

Name	Type	Default	Description
di_length	simple int		The length for Directional Indicator calculation.
adx_smoothing	simple int		The smoothing length for ADX calculation.

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

---

ema

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

Examples

let ema12 = ta.ema(close, 12);
let ema26 = ta.ema(close, 26);
plot(ema12, title: "EMA 12", color: color.GREEN);
plot(ema26, title: "EMA 26", color: color.RED);

---

falling

ta.falling(source: series float, length: series int): 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

Returns 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 float

Examples

let highestHigh = ta.highest(high, 20);
plot(highestHigh, title: "20-bar High", color: color.RED,
style: PlotStyle.Stepline);

---

highest_bars

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.

Returns the number of bars since 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 int

---

hma

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

ta.kc(
    series: series float,
    length: simple int,
    mult: simple float,
    use_true_range: simple bool = 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.
use_true_range	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

ta.kcw(
    series: series float,
    length: simple int,
    mult: simple float,
    use_true_range: simple bool = 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.
use_true_range	simple bool	true	Whether to use True Range.

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

---

linreg

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

Returns 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 float

---

lowest_bars

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.

Returns the number of bars since 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 int

---

macd

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

Moving Average Convergence Divergence (MACD).

Parameters

Name	Type	Default	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.

Examples

let (macdLine, signalLine, histLine) = ta.macd(close, 12, 26, 9);
plot(macdLine,   title: "MACD",     color: color.BLUE);
plot(signalLine, title: "Signal",   color: color.ORANGE);
plot(histLine, title: "Hist", color: color.GRAY, style: PlotStyle.Histogram);

---

max

ta.max(source: series float): 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

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

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

ta.min(source: series float): 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

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

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

---

percent_rank

ta.percent_rank(source: series float, length: series int): 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.

---

percentile_linear_interpolation

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

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

Parameters

Name	Type	Default	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

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

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

Parameters

Name	Type	Default	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

---

pivot_high

Returns the price of the pivot high point.

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

Parameters

Name	Type	Default	Description
source	series float		The input series to analyze.
left_bars	series int		The number of bars to the left to check.
right_bars	series int		The number of bars to the right to check.

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

Returns the price of the pivot high point.

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

Parameters

Name	Type	Default	Description
left_bars	series int		The number of bars to the left to check.
right_bars	series int		The number of bars to the right to check.

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

---

pivot_low

Returns the price of the pivot low point.

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

Parameters

Name	Type	Default	Description
source	series float		The input series to analyze.
left_bars	series int		The number of bars to the left to check.
right_bars	series int		The number of bars to the right to check.

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

Returns the price of the pivot low point.

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

Parameters

Name	Type	Default	Description
left_bars	series int		The number of bars to the left to check.
right_bars	series int		The number of bars to the right to check.

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

---

pivot_point_levels

ta.pivot_point_levels(
    type: series PivotType,
    change: series bool
  ): series Array<float>

Returns an array of pivot point levels for the specified pivot type.

The returned array contains up to 11 values in the order: [P, S1, R1, S2, R2, S3, R3, S4, R4, S5, R5]. Levels that do not apply for the chosen type are na.

Parameters

Name	Type	Default	Description
type	series PivotType		The pivot calculation method.
change	series bool		true on the first bar of a new pivot period.

Returns: series Array<float>

---

range

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

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

ta.rising(source: series float, length: series int): 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

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

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

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

Examples

let rsiValue = ta.rsi(close, 14);
plot(rsiValue, title: "RSI", color: color.PURPLE);
hline(70, "Overbought", color: color.RED);
hline(30, "Oversold", color: color.GREEN);

---

sar

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

Parabolic SAR.

Parameters

Name	Type	Default	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

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

Examples

let sma20 = ta.sma(close, 20);
plot(sma20, title: "SMA 20", color: color.BLUE);

---

stdev

ta.stdev(
    source: series float,
    length: series int,
    biased: series bool = 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

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

Stochastic Oscillator (STOCH).

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

Parameters

Name	Type	Default	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

ta.supertrend(factor: series float, atr_period: simple int)

SuperTrend indicator.

Parameters

Name	Type	Default	Description
factor	series float		The multiplier for ATR in the SuperTrend calculation.
atr_period	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

ta.swma(source: series float): 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

ta.tr(handle_na: simple bool): 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

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

True Strength Index (TSI).

Parameters

Name	Type	Default	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.

---

value_when

ta.value_when(
    condition: series bool,
    source: series T,
    occurrence: simple int
  ): 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	Default	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

ta.variance(
    source: series float,
    length: series int,
    biased: series bool = 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

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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	Default	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.

Volume Weighted Average Price without bands.

Parameters

Name	Type	Default	Description
source	series float		The price series (commonly hlc3).
anchor	series bool	timeframe.change("1D")	When true, resets the VWAP. Defaults to daily reset (timeframe.change("1D")).

Returns: series float — A single VWAP series that resets when anchor is true.

---

vwma

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

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

ta.wpr(length: series int): 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.