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

navi

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

See Also: ta.sma, ta.ema

atr

navi

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

See Also: ta.rma, ta.supertrend

bars_since

navi

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.

See Also: ta.highest_bars, ta.lowest_bars

bb

navi

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

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.

Examples

navi

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);

See Also: ta.bbw, ta.sma, ta.stdev

bbw

navi

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	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.

See Also: ta.bb, ta.stdev

cci

navi

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

See Also: ta.sma, ta.dev

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).

chop

navi

chop(length: simple int): series float

Choppiness Index (CHOP).

Quantifies how directional (trending) or sideways (choppy) the market is. Values near 100 signal maximum choppiness; values near the lower bound (≈ 100/log10(length)) signal strong trend. Formula: 100 * log10(sum(ATR(1), length) / (highest_high - lowest_low)) / log10(length).

Parameters

Name	Type	Default	Description
`length`	`simple int`		The lookback period (must be >= 2).

Returns: series float

cmf

navi

cmf(length: simple int): series float

Chaikin Money Flow (CMF).

Measures buying and selling pressure over length bars using the Money Flow Multiplier weighted by volume. Positive values indicate accumulation; negative values indicate distribution. Formula: sum(MFV, length) / sum(volume, length) where MFV = ((close - low) - (high - close)) / (high - low) * volume.

Parameters

Name	Type	Default	Description
`length`	`simple int`		The number of bars to accumulate.

Returns: series float

cmo

navi

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.

See Also: ta.change

cog

navi

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

navi

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	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

navi

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

See Also: ta.cross_over, ta.cross_under

cross_over

navi

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

navi

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);
}

See Also: ta.cross_under, ta.cross

cross_under

navi

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

navi

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);
}

See Also: ta.cross_over, ta.cross

cum

navi

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

dema

navi

dema(source: series float, length: simple int): series float

Double Exponential Moving Average (DEMA).

Reduces the lag of a standard EMA by subtracting an EMA of the EMA. Formula: 2 * EMA(source, length) - EMA(EMA(source, length), length).

Parameters

Name	Type	Default	Description
`source`	`series float`		The series to smooth.
`length`	`simple int`		The smoothing period.

Returns: series float

See Also: ta.ema, ta.tema

dev

navi

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

navi

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).

See Also: ta.atr, ta.rma

ema

navi

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

navi

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);

See Also: ta.sma, ta.wma, ta.rma, ta.dema, ta.tema

falling

navi

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

See Also: ta.rising

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

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.

hma

navi

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

See Also: ta.sma, ta.ema, ta.wma

kc

navi

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.

See Also: ta.kcw, ta.ema, ta.atr

kcw

navi

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.

See Also: ta.kc

linreg

navi

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	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

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.

macd

navi

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

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.

Examples

navi

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);

See Also: ta.ema

max

navi

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

navi

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

See Also: ta.mode

mfi

navi

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

navi

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

navi

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

See Also: ta.median

mom

navi

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

See Also: ta.change, ta.roc

percent_rank

navi

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

navi

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	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

See Also: ta.percentile_nearest_rank

percentile_nearest_rank

navi

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	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	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.

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.

pivot_low

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.
`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.

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.

pivot_point_levels

navi

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

navi

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

navi

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

navi

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

See Also: ta.falling

rma

navi

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

See Also: ta.ema

roc

navi

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].

See Also: ta.change, ta.mom

rsi

navi

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

navi

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);

See Also: ta.rma, ta.stoch

sar

navi

sar(start: simple float, inc: simple float, max: simple float): 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

navi

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

navi

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

See Also: ta.ema, ta.wma, ta.rma, ta.hma

stdev

navi

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

See Also: ta.variance, ta.bb

stoch

navi

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	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.

See Also: ta.rsi, ta.wpr

supertrend

navi

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).

See Also: ta.atr

swma

navi

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

tema

navi

tema(source: series float, length: simple int): series float

Triple Exponential Moving Average (TEMA).

Further reduces EMA lag using three layers of smoothing. Formula: 3*EMA1 - 3*EMA2 + EMA3 where each EMA is applied to the previous layer's output.

Parameters

Name	Type	Default	Description
`source`	`series float`		The series to smooth.
`length`	`simple int`		The smoothing period.

Returns: series float

See Also: ta.ema, ta.dema

tr

navi

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

navi

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

value_when

navi

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	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

navi

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

See Also: ta.stdev

vhf

navi

vhf(source: series float, length: simple int): series float

Vertical Horizontal Filter (VHF).

Identifies whether the market is trending or ranging by comparing the price range to the sum of absolute bar-to-bar changes. Higher values indicate a stronger trend; lower values indicate choppiness. Formula: (highest - lowest) / sum(|change|, length).

Parameters

Name	Type	Default	Description
`source`	`series float`		The price series to analyze.
`length`	`simple int`		The lookback period.

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

navi

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

navi

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

See Also: ta.sma, ta.ema, ta.hma

wpr

navi

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.

See Also: ta.stoch

ta ​

Types ​

Properties ​

accdist ​

iii ​

nvi ​

obv ​

pvi ​

pvt ​

tr ​

vwap ​

wad ​

wvad ​

Functions ​

alma ​

atr ​

bars_since ​

bb ​

bbw ​

cci ​

change ​

chop ​

cmf ​

cmo ​

cog ​

correlation ​

cross ​

cross_over ​

cross_under ​

cum ​

dema ​

dev ​

dmi ​

ema ​

falling ​

highest ​

highest_bars ​

hma ​

kc ​

kcw ​

linreg ​

lowest ​

lowest_bars ​

macd ​

max ​

median ​

mfi ​

min ​

mode ​

mom ​

percent_rank ​

percentile_linear_interpolation ​

percentile_nearest_rank ​

pivot_high ​

pivot_low ​

pivot_point_levels ​

range ​

rci ​

rising ​

rma ​

roc ​

rsi ​

sar ​

sma ​

stdev ​

stoch ​

supertrend ​

swma ​

tema ​

tr ​

tsi ​

value_when ​

variance ​

vhf ​

vwap ​

vwma ​

wma ​

wpr ​

ta

Types

Properties

accdist

iii

nvi

obv

pvi

pvt

tr

vwap

wad

wvad

Functions

alma

atr

bars_since

bb

bbw

cci

change

chop

cmf

cmo

cog

correlation

cross

cross_over

cross_under

cum

dema

dev

dmi

ema

falling

highest

highest_bars

hma

kc

kcw

linreg

lowest

lowest_bars

macd

max

median

mfi

min

mode

mom

percent_rank

percentile_linear_interpolation

percentile_nearest_rank

pivot_high

pivot_low

pivot_point_levels

range

rci

rising

rma

roc

rsi

sar

sma

stdev

stoch

supertrend

swma

tema

tr

tsi

value_when

variance

vhf

vwap

vwma

wma

wpr