Study Reference

The scanner has 102 built-in studies in 9 groups. A study is a calculation on a stock's price or volume history, such as a moving average or RSI. Each entry gives the study's notation, the inputs it reads, and every setting with its default and allowed range. The settings carry the names the study editor shows.

Notation reads like a function call: SMA(c, period) is a simple moving average of the close over period bars. The glossary explains the shorthand under Notation.

Plans and lookback

Every plan can run every study. Free runs studies on the daily timeframe only. A study's lookback, the number of bars it reads, is capped by plan: 200 trading days on Free, 400 on Super, no cap on Super Pro. The cap counts trading days, so on a weekly timeframe Super can look back 80 bars. Some inputs need a paid plan; see Study inputs.

Overlap and moving averages

These studies sit on the price chart itself. Use them to read the direction of a trend and where price sits against it. 17 studies.

Bollinger Bands

Bollinger Bands are a technical indicator that plots two standard deviation bands around a moving average. The upper band is typically 2 standard deviations above the moving average, and the lower band is typically 2 standard deviations below the moving average. The middle band is typically the moving average.

BBANDS(c, period, nbdevup, nbdevdn, matype)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
  • NBDevUp: default 2, 0 to 200
  • NBDevDn: default 2, 0 to 200
  • MAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Outputs: Upper, Middle, Lower

Double exponential moving average

A trend-following indicator that reduces lag inherent in traditional moving averages by using a calculation that subtracts a double-smoothed EMA from twice the single-smoothed EMA.

DEMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: DEMA

Exponential moving average

A trend-following indicator that gives more weight to recent prices, making it more responsive to new information than a simple moving average.

EMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: EMA

Hilbert Transform - Instantaneous Trendline

Uses Hilbert Transform to generate a trendline that adapts to the dominant cycle in the data, providing a smoothed representation of price trends.

HT_TRENDLINE(c)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: HT_TRENDLINE

Kaufman Adaptive Moving Average

An adaptive moving average that dynamically adjusts its responsiveness based on market efficiency, following prices closely during trending markets and adjusting during choppy periods.

KAMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: KAMA

MESA Adaptive Moving Average

An adaptive moving average that adjusts based on the rate of change of phase as measured by the Hilbert Transform, featuring fast attack and slow decay to reduce whipsaw trades.

MAMA(c, fastlimit, slowlimit)

• Inputs: c close price
• Settings:
  • FastLimit: default 0.5, 0.01 to 0.99
  • SlowLimit: default 0.05, 0.01 to 0.99
• Outputs: MAMA, FAMA

MidPoint over period

Calculates the midpoint between the highest and lowest values over a specified period, useful for identifying the center of price action.

MIDPOINT(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: MIDPOINT

Midpoint Price over period

Calculates the midpoint between the highest high and lowest low over a specified period, representing the middle of the price range.

MIDPRICE(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 14, 0 to 200
• Output: MIDPRICE

Moving average

A versatile moving average that can be configured to use different calculation methods (SMA, EMA, WMA, etc.) to smooth price data and identify trends.

MA(c, period, matype)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
  • MAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Output: MA

Moving average with variable period

A moving average that allows for variable period lengths, adapting to market conditions by using different lookback periods over time. Takes more time to compute than other functions.

MAVP(c, periods, minperiod, maxperiod, matype)

• Inputs: c close price
• Settings:
  • Periods: default 9, 16, 28, 2 to 30
  • MAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Output: MAVP

Parabolic SAR

Parabolic Stop and Reverse indicator that provides potential reversal points, appearing as dots above or below price to indicate trend direction and potential exit points.

SAR(h, l, acceleration, maximum)

• Inputs: h high price, l low price
• Settings:
  • Acceleration: default 0, 0 to 200
  • Maximum: default 0, 0 to 200
• Output: SAR

Parabolic SAR Extended params

An extended version of Parabolic SAR with separate acceleration parameters for long and short positions, allowing for asymmetric tuning of trend sensitivity.

SAREXT(h, l, ...)

• Inputs: h high price, l low price
• Settings:
  • Startvalue: default 0, 0 to 200
  • Offsetonreverse: default 0, 0 to 200
  • Accelerationinitlong: default 0, 0 to 200
  • Accelerationlong: default 0, 0 to 200
  • Accelerationmaxlong: default 0, 0 to 200
  • Accelerationinitshort: default 0, 0 to 200
  • Accelerationshort: default 0, 0 to 200
  • Accelerationmaxshort: default 0, 0 to 200
• Output: SAREXT

Simple Moving Average

A simple average of prices over a specified period, giving equal weight to all values and commonly used to identify trend direction. DEPRECATED USAGE: SMA(fw_*, period=1) as an identity function to reach a raw feature-window column. It still works and existing saved scans are not broken, but it burns a talib dispatch per ticker to compute x -> x. Use the FeatureWindow scan category instead (ADR-0062), it compares the raw column directly and adds self-comparison across time, WithinAll, and the 3-way SessionZones control.

SMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 50, 0 to 200
• Output: SMA

Triangular Moving Average

A double-smoothed simple moving average that places more weight on the middle portion of the data, resulting in a very smooth trendline with significant lag.

TRIMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: TRIMA

Triple Exponential Moving Average

A trend-following indicator that applies triple exponential smoothing to reduce lag even further than DEMA while maintaining responsiveness to price changes.

TEMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: TEMA

Triple Exponential Moving Average (T3)

A smoothed moving average that applies exponential smoothing multiple times with a volume factor, designed to reduce lag while maintaining smoothness.

T3(c, period, vfactor)

• Inputs: c close price
• Settings:
  • Period: default 5, 0 to 200
  • Vfactor: default 0, 0 to 200
• Output: T3

Weighted Moving Average

A moving average that assigns linearly increasing weight to more recent data, making it more responsive to price changes than a simple moving average.

WMA(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: WMA

Momentum studies

Momentum studies measure how fast and how far price is moving, to spot overbought and oversold stocks and turns in a trend. 30 studies.

1-day Rate-Of-Change (ROC) of a Triple Smooth EMA

Shows the rate of change of a triple exponentially smoothed moving average, filtering out market noise to show longer-term trend direction.

TRIX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: TRIX

Absolute Price Oscillator

Displays the difference between two moving averages in absolute terms, useful for identifying momentum and potential trend changes.

APO(c, fastperiod, slowperiod, matype)

• Inputs: c close price
• Settings:
  • FastPeriod: default 12, 0 to 200
  • SlowPeriod: default 26, 0 to 200
  • MAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Output: APO

Aroon

Identifies the time elapsed since the highest high and lowest low over a period, with Aroon Up and Aroon Down lines indicating uptrend and downtrend strength respectively.

AROON(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 14, 0 to 200
• Outputs: Down, Up

Aroon Oscillator

The difference between Aroon Up and Aroon Down, oscillating between -100 and 100 to indicate trend direction and strength.

AROONOSC(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 14, 0 to 200
• Output: AROONOSC
• Values: -100 to 100

Average Directional Movement Index

Measures trend strength regardless of direction, with values above 25 indicating a strong trend and below 20 indicating a weak trend or ranging market.

ADX(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: ADX

Average Directional Movement Index Rating

A smoothed version of ADX that averages the current ADX with the ADX from a specified number of periods ago, providing a more stable trend strength measurement.

ADXR(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: ADXR

Balance Of Power

Measures the strength of buyers versus sellers by calculating where the close is relative to the range, with positive values indicating buyer dominance.

BOP(o, h, l, c)

• Inputs: o open price, h high price, l low price, c close price
• Settings: none
• Output: BOP
• Values: -1 to 1

Chande Momentum Oscillator

A momentum oscillator that measures the difference between the sum of gains and losses over a period, oscillating between -100 and +100.

CMO(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: CMO
• Values: -100 to 100

Commodity Channel Index

Measures the deviation of price from its statistical mean, with values above +100 indicating overbought conditions and below -100 indicating oversold conditions.

CCI(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: CCI

Directional Movement Index

Measures the strength of directional movement by comparing positive and negative directional indicators, used as a component in calculating ADX.

DX(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: DX

MACD with controllable MA type

An extended version of MACD that allows customization of the moving average types for fast, slow, and signal lines.

MACDEXT(c, fastperiod, fastmatype, slowperiod, slowmatype, signalperiod, signalmatype)

• Inputs: c close price
• Settings:
  • FastPeriod: default 12, 0 to 200
  • FastMAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
  • SlowPeriod: default 26, 0 to 200
  • SlowMAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
  • SignalPeriod: default 9, 0 to 200
  • SignalMAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Outputs: MACDEXT, Signal, MACDEXTHist

Minus Directional Indicator

Measures downward price movement as part of the Directional Movement System, used with Plus DI to assess trend direction.

MINUS_DI(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: MINUS_DI

Minus Directional Movement

Calculates the smoothed difference between consecutive lows when the current low is lower than the previous low, indicating downward movement.

MINUS_DM(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 14, 0 to 200
• Output: MINUS_DM

Momentum

Calculates the difference between the current price and the price a specified number of periods ago, measuring the rate of price change.

MOM(c, period)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
• Output: MOM

Money Flow Index

A volume-weighted momentum indicator that measures buying and selling pressure, with values above 80 indicating overbought and below 20 indicating oversold.

MFI(h, l, c, v, period)

• Inputs: h high price, l low price, c close price, v volume
• Settings:
  • Period: default 14, 0 to 200
• Output: MFI
• Values: 0 to 100

Moving Average Convergence/Divergence

Shows the relationship between two moving averages, consisting of the MACD line, signal line, and histogram to identify momentum and potential trend reversals.

MACD(c, fastperiod, slowperiod, signalperiod)

• Inputs: c close price
• Settings:
  • FastPeriod: default 12, 0 to 200
  • SlowPeriod: default 26, 0 to 200
  • SignalPeriod: default 9, 0 to 200
• Outputs: MACD, Signal, MACDHist

Moving Average Convergence/Divergence Fix 12/26

MACD with fixed fast (12) and slow (26) periods, allowing only the signal period to be adjusted.

MACDFIX(c, signalperiod)

• Inputs: c close price
• Settings:
  • SignalPeriod: default 9, 0 to 200
• Outputs: MACDFIX, Signal, MACDFIXHist

Percentage Price Oscillator

Similar to MACD but expressed as a percentage, making it easier to compare across securities with different price levels.

PPO(c, fastperiod, slowperiod, matype)

• Inputs: c close price
• Settings:
  • FastPeriod: default 12, 0 to 200
  • SlowPeriod: default 26, 0 to 200
  • MAType: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Output: PPO

Plus Directional Indicator

Measures upward price movement as part of the Directional Movement System, used with Minus DI to assess trend direction.

PLUS_DI(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: PLUS_DI

Plus Directional Movement

Calculates the smoothed difference between consecutive highs when the current high is higher than the previous high, indicating upward movement.

PLUS_DM(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 14, 0 to 200
• Output: PLUS_DM

Rate of change

Measures the percentage change in price between the current price and the price n periods ago, used to identify momentum.

ROC(c, period)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
• Output: ROC

Rate of change Percentage

Calculates the rate of change as a decimal percentage, showing the proportion of change relative to the previous price.

ROCP(c, period)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
• Output: ROCP

Rate of change ratio

Calculates the rate of change as a ratio of current price to previous price, with values above 1 indicating upward movement.

ROCR(c, period)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
• Output: ROCR

Rate of change ratio 100 scale

Same as ROCR but scaled by 100, with values above 100 indicating upward movement and below 100 indicating downward movement.

ROCR100(c, period)

• Inputs: c close price
• Settings:
  • Period: default 10, 0 to 200
• Output: ROCR100

Relative Strength Index

A momentum oscillator that measures the speed and magnitude of price changes, with values above 70 typically indicating overbought conditions and below 30 indicating oversold.

RSI(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: RSI
• Values: 0 to 100

Stochastic

Compares the closing price to the price range over a period, generating %K and %D lines that oscillate between 0 and 100 to identify overbought and oversold levels.

STOCH(h, l, c, fastk_period, slowk_period, slowk_matype, slowd_period, slowd_matype)

• Inputs: h high price, l low price, c close price
• Settings:
  • Fastk_period: default 5, 0 to 200
  • Slowk_period: default 3, 0 to 200
  • Slowk_matype: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
  • Slowd_period: default 3, 0 to 200
  • Slowd_matype: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Outputs: SlowK, SlowD
• Values: 0 to 100

Stochastic Fast

A faster version of the Stochastic oscillator without additional smoothing, more sensitive to price changes and generating earlier signals.

STOCHF(h, l, c, fastk_period, fastd_period, fastd_matype)

• Inputs: h high price, l low price, c close price
• Settings:
  • Fastk_period: default 5, 0 to 200
  • Fastd_period: default 3, 0 to 200
  • Fastd_matype: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Outputs: FastK, FastD
• Values: 0 to 100

Stochastic Relative Strength Index

Applies the Stochastic formula to RSI values rather than price, creating a more sensitive oscillator that identifies overbought and oversold RSI levels.

STOCHRSI(c, period, fastk_period, fastd_period, fastd_matype)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
  • Fastk_period: default 5, 0 to 200
  • Fastd_period: default 3, 0 to 200
  • Fastd_matype: default SMA; one of SMA, EMA, WMA, DEMA, TEMA, TRIMA, KAMA, MAMA, T3
• Outputs: FastK, FastD
• Values: 0 to 100

Ultimate Oscillator

Combines three different timeframes of buying pressure to reduce false signals, with values above 70 indicating overbought and below 30 indicating oversold.

ULTOSC(h, l, c, timeperiod1, timeperiod2, timeperiod3)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period1: default 7, 0 to 200
  • Period2: default 14, 0 to 200
  • Period3: default 28, 0 to 200
• Output: ULTOSC
• Values: 0 to 100

Williams %R

A momentum indicator that measures overbought and oversold levels, oscillating between -100 and 0, with values above -20 considered overbought and below -80 oversold.

WILLR(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: WILLR
• Values: -100 to 0

Volume

Volume studies read buying and selling pressure from traded volume, to confirm or question a price move. 6 studies.

Chaikin A/D Line

Accumulation/Distribution Line measures the cumulative flow of money into and out of a security by considering both price location and volume.

AD(h, l, c, v)

• Inputs: h high price, l low price, c close price, v volume
• Settings: none
• Output: AD

Chaikin A/D Oscillator

An oscillator derived from the Accumulation/Distribution Line, showing the difference between fast and slow EMAs of the A/D Line to identify momentum shifts.

ADOSC(h, l, c, v, fastperiod, slowperiod)

• Inputs: h high price, l low price, c close price, v volume
• Settings:
  • FastPeriod: default 3, 0 to 200
  • SlowPeriod: default 10, 0 to 200
• Output: ADOSC

Directional Relative Volume

Relative volume with a direction attached, computed from bars alone. Returns three plots: ZVOL is the volume z-score over Length bars (identical to RELVOL_STDDEV), CONVICTION is how decisively the bar resolved in [-1, +1] (a blend of the signed body ratio and the close location value, weighted by WeightBody), and DIRVOL is max(ZVOL, 0) x CONVICTION. Gate ZVOL and CONVICTION separately to express states DIRVOL alone cannot: high ZVOL with CONVICTION near zero is heavy volume that resolved nothing, a churn or absorption bar.

RELVOL_DIRECTIONAL(o, h, l, c, v, length, w_body)

• Inputs: o open price, h high price, l low price, c close price, v volume
• Settings:
  • Length: default 60, 0 to 200
  • WeightBody: default 50, 0 to 100. Percent weight on the signed body ratio; the remainder goes to the close location value.
• Outputs: DIRVOL, ZVOL, CONVICTION

On Balance Volume

A cumulative volume-based indicator that adds volume on up days and subtracts on down days, measuring buying and selling pressure.

OBV(c, v)

• Inputs: c close price, v volume
• Settings: none
• Output: OBV

Relative Volume Standard Deviation

Measures how many standard deviations the current volume is from its historical average, useful for identifying unusual volume activity.

RELVOL_STDDEV(v, length)

• Inputs: v volume
• Settings:
  • Length: default 60, 0 to 200
• Output: VALUE

Volume Frontload Strength

Signed strength score combining z-scores of volume, dollar volume, trade count, average trade size, Lee-Ready ask/bid skew, aggression, block-trade intensity, and trade impact. Positive values indicate bullish frontload (aggressive buying); negative values indicate bearish dump. Weights are 0-100 (percent). Set RequireAgreement=1 to zero-out the result when price direction and order-flow direction disagree.

VOL_FRONTLOAD(v, c, o, tt, ats, tta, ttb, agg, bti, tir, length)

• Inputs: v volume, c close price, o open price, tt total trades in feature window, ats average trade size, tta trades on ask side (buy aggressor), ttb trades on bid side (sell aggressor), agg aggression factor (normalized), bti block trade intensity (normalized), tir trade impact ratio (normalized)
• Settings:
  • Length: default 60, 0 to 200
  • MinDollarVolume: default 0, 0 to 1000000000
  • RequireAgreement: default 1, 0 to 1. Whether the price and order-flow direction must agree.
  • WeightDollarVolume: default 25, 0 to 100
  • WeightAggression: default 20, 0 to 100
  • WeightLeeReadySkew: default 15, 0 to 100
  • WeightAvgSize: default 15, 0 to 100
  • WeightTradeCount: default 10, 0 to 100
  • WeightBlockIntensity: default 10, 0 to 100
  • WeightImpact: default 5, 0 to 100
• Output: STRENGTH

Volatility

Volatility studies measure how much price swings. Use them to size stops and positions and to find stocks coiling before a breakout. 5 studies.

Average Daily Range

Average of the intraday high-to-low range over a period, published both in price units (ADR) and as the swing-trader percentage (ADRPercent = 100 x (mean(high/low) - 1)). Unlike ATR it ignores the previous close, so an overnight gap does not inflate it, it measures how far a stock travels once it is open.

ADR(h, l, period)

• Inputs: h high price, l low price
• Settings:
  • Period: default 20, 0 to 200
• Outputs: ADR, ADRPercent

Average True Range

Measures market volatility by calculating the average of true ranges over a period, with higher values indicating greater volatility.

ATR(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: ATR

Normalized Average True Range

ATR expressed as a percentage of the closing price, allowing volatility comparison across different price levels.

NATR(h, l, c, period)

• Inputs: h high price, l low price, c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: NATR

Squeeze (Compression + Expansion)

Coiled-spring compression and its release, as one study. COMPRESSION is the percentile rank of ATR(Length)/close over the trailing Lookback bars (0-100; low = coiled, this is the PCTRANK modifier's exact kernel, so it shares that floor of 100/Lookback and never reaches exactly 0). SQUEEZE_ON is 1 when Bollinger(Length, 2 stddev) sits entirely inside Keltner(Length EMA, 1.5x ATR(Length)), 0 when it does not, and NaN during warmup (never read a NaN bar as "not squeezed"). EXPANSION is ATR(5)/ATR(Length), the release trigger, values above roughly 1.3 following a low COMPRESSION reading are the tradable signal; compression alone is a weak, mostly-autocorrelated signal and should not be filtered without also gating EXPANSION. COMPRESSION is a weak rank (matches PCTRANK, ADR-0112): it never reaches exactly 0, floors at 100/Lookback (~0.4 at the default 252), and is not uniformly distributed. SQUEEZE_ON reads NaN (dropped by comparators, not matched as false) until Length+Lookback bars of history exist. EXPANSION is an unguarded ratio: a halted or limit-locked name (zero-range ATR) yields inf or NaN rather than a clamped value, matching the DIVIDE modifier's documented zero-denominator behaviour (ADR-0110). Filtering COMPRESSION alone, without also gating EXPANSION, is the overfit trap this study's own gate ruled out, see docs/lev-272-squeeze-gate.md.

SQUEEZE(h, l, c, length, lookback)

• Inputs: h high price, l low price, c close price
• Settings:
  • Length: default 20, 0 to 200
  • Lookback: default 252, 0 to 504
• Outputs: COMPRESSION, SQUEEZEON, EXPANSION

True Range

Measures the greatest of: current high minus current low, absolute value of current high minus previous close, or absolute value of current low minus previous close.

TRANGE(h, l, c)

• Inputs: h high price, l low price, c close price
• Settings: none
• Output: TRANGE

Price transforms

Price transforms combine a bar's open, high, low and close into a single price you can run other studies on. 4 studies.

Average Price

The average of a bar's open, high, low and close, (O + H + L + C) / 4. A single-bar smoothing of price that is less sensitive to a volatile close than the close alone.

AVGPRICE(o, h, l, c)

• Inputs: o open price, h high price, l low price, c close price
• Settings: none
• Output: AVGPRICE

Median Price

The midpoint of a bar's range, (H + L) / 2. Represents the bar's central price independently of where it opened or closed.

MEDPRICE(h, l)

• Inputs: h high price, l low price
• Settings: none
• Output: MEDPRICE

Typical Price

The average of a bar's high, low and close, (H + L + C) / 3. The price input CCI and MFI are built on, and the per-bar term inside a VWAP calculation.

TYPPRICE(h, l, c)

• Inputs: h high price, l low price, c close price
• Settings: none
• Output: TYPPRICE

Weighted Close Price

A bar's high, low and close averaged with double weight on the close, (H + L + 2C) / 4. Like Typical Price but leaning on where the bar settled.

WCLPRICE(h, l, c)

• Inputs: h high price, l low price, c close price
• Settings: none
• Output: WCLPRICE

Statistics

Statistical studies measure dispersion, correlation and regression over a window of bars. 9 studies.

Beta

Measures the volatility of a security relative to another security or benchmark over a specified period.

BETA(c0, c1, period)

• Inputs: c0 first series, typically closing price, c1 second series, typically closing price of benchmark
• Settings:
  • Period: default 5, 0 to 200
• Output: BETA

Linear Regression

Fits a linear regression line to price data over a period and returns the current endpoint value, useful for identifying trend direction.

LINEARREG(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: LINEARREG

Linear Regression Angle

Returns the angle of the linear regression line in degrees, helping to quantify trend steepness and strength.

LINEARREG_ANGLE(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: LINEARREG_ANGLE

Linear Regression Intercept

Returns the y-intercept of the linear regression line fitted to price data, useful for identifying support/resistance levels.

LINEARREG_INTERCEPT(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: LINEARREG_INTERCEPT

Linear Regression Slope

Returns the slope of the linear regression line, indicating the rate of price change and trend strength.

LINEARREG_SLOPE(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: LINEARREG_SLOPE

Pearson's Correlation Coefficient

Calculates the correlation coefficient between two price series over a period, ranging from -1 to +1 to measure their relationship strength.

CORREL(c0, c1, period)

• Inputs: c0 first series, typically closing price, c1 second series, typically closing price of comparison security
• Settings:
  • Period: default 30, 0 to 200
• Output: CORREL
• Values: -1 to 1

Standard Deviation

Measures the dispersion of price values from their mean, with higher values indicating greater volatility.

STDDEV(c, period, nbdev)

• Inputs: c close price
• Settings:
  • Period: default 5, 0 to 200
  • NbDev: default 1, 0 to 10
• Output: STDDEV

Time Series Forecast

Extends the linear regression line one period into the future to forecast the next expected price value.

TSF(c, period)

• Inputs: c close price
• Settings:
  • Period: default 14, 0 to 200
• Output: TSF

Variance

Calculates the variance of price values over a period, measuring the average squared deviation from the mean.

VAR(c, period, nbdev)

• Inputs: c close price
• Settings:
  • Period: default 5, 0 to 200
  • NbDev: default 1, 0 to 10
• Output: VAR

Cycle

Cycle studies use the Hilbert transform to estimate the length and phase of a price cycle, and whether price is trending or cycling. 5 studies.

Hilbert Transform - Dominant Cycle Period

Estimates the length, in bars, of the dominant price cycle currently present in the series. Used to size other indicators adaptively rather than fixing a period by hand.

HT_DCPERIOD(c)

• Inputs: c close price
• Settings: none
• Output: HT_DCPERIOD

Hilbert Transform - Dominant Cycle Phase

Reports how far through the dominant cycle price currently is, in degrees. Reading it alongside HT_DCPERIOD tells you where in a cycle a move is occurring, not just that one is.

HT_DCPHASE(c)

• Inputs: c close price
• Settings: none
• Output: HT_DCPHASE

Hilbert Transform - Phasor Components

Decomposes price into the two quadrature components of its analytic signal. Their relative magnitude is the raw material HT_DCPHASE and HT_SINE are derived from.

HT_PHASOR(c)

• Inputs: c close price
• Settings: none
• Outputs: InPhase, Quadrature

Hilbert Transform - SineWave

Plots the dominant cycle as a sine wave against a 45°-advanced lead wave. Crossings of the two are the conventional cycle-turn signal, and they separate cleanly only while the market is actually cycling, pair with HT_TRENDMODE.

HT_SINE(c)

• Inputs: c close price
• Settings: none
• Outputs: Sine, LeadSine

Hilbert Transform - Trend vs Cycle Mode

A 0/1 classifier: 1 when the series is trending, 0 when it is cycling. Intended as a gate on cycle studies, HT_SINE crossovers are only meaningful in cycle mode.

HT_TRENDMODE(c)

• Inputs: c close price
• Settings: none
• Output: HT_TRENDMODE

Math transforms

Math transforms apply one function to every value of a series. They are building blocks for study comparisons. 15 studies.

Arc Cosine

Applies the arc cosine (inverse cosine) mathematical transformation to price values.

ACOS(c)

• Inputs: c close price
• Settings: none
• Output: Value

Arc Sine

Applies the arc sine (inverse sine) mathematical transformation to price values.

ASIN(c)

• Inputs: c close price
• Settings: none
• Output: Value

Arc Tangent

Applies the arc tangent (inverse tangent) mathematical transformation to price values.

ATAN(c)

• Inputs: c close price
• Settings: none
• Output: Value

Base-10 Logarithm

Applies the base-10 logarithm mathematical transformation to price values.

LOG10(c)

• Inputs: c close price
• Settings: none
• Output: Value

Ceiling

Rounds price values up to the nearest integer.

CEIL(c)

• Inputs: c close price
• Settings: none
• Output: Value

Cosine

Applies the cosine mathematical transformation to price values.

COS(c)

• Inputs: c close price
• Settings: none
• Output: Value

Exponential

Applies the exponential (e^x) mathematical transformation to price values.

EXP(c)

• Inputs: c close price
• Settings: none
• Output: Value

Floor

Rounds price values down to the nearest integer.

FLOOR(c)

• Inputs: c close price
• Settings: none
• Output: Value

Hyperbolic Cosine

Applies the hyperbolic cosine mathematical transformation to price values.

COSH(c)

• Inputs: c close price
• Settings: none
• Output: Value

Hyperbolic Sine

Applies the hyperbolic sine mathematical transformation to price values.

SINH(c)

• Inputs: c close price
• Settings: none
• Output: Value

Hyperbolic Tangent

Applies the hyperbolic tangent mathematical transformation to price values.

TANH(c)

• Inputs: c close price
• Settings: none
• Output: Value

Natural Logarithm

Applies the natural logarithm (base e) mathematical transformation to price values.

LN(c)

• Inputs: c close price
• Settings: none
• Output: Value

Sine

Applies the sine mathematical transformation to price values.

SIN(c)

• Inputs: c close price
• Settings: none
• Output: Value

Square Root

Applies the square root mathematical transformation to price values.

SQRT(c)

• Inputs: c close price
• Settings: none
• Output: Value

Tangent

Applies the tangent mathematical transformation to price values.

TAN(c)

• Inputs: c close price
• Settings: none
• Output: Value

Math operators

Math operators combine two series, or roll one series over a window, so you can build a composite of your own. 11 studies.

Highest value over a specified period

Returns the highest value in the data series over a specified period.

MAX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: MAX

Index of highest value over a specified period

Returns the index (position) of the highest value in the data series over a specified period.

MAXINDEX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: MAXINDEX

Index of lowest value over a specified period

Returns the index (position) of the lowest value in the data series over a specified period.

MININDEX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: MININDEX

Indexes of lowest and highest values over a specified period

Returns both the index of the lowest and highest values in the data series over a specified period.

MINMAXINDEX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Outputs: MinIndex, MaxIndex

Lowest and highest values over a specified period

Returns both the lowest and highest values in the data series over a specified period.

MINMAX(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Outputs: Min, Max

Lowest value over a specified period

Returns the lowest value in the data series over a specified period.

MIN(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: MIN

Summation

Returns the sum of all values in the data series over a specified period.

SUM(c, period)

• Inputs: c close price
• Settings:
  • Period: default 30, 0 to 200
• Output: SUM

Vector Arithmetic Add

Performs element-wise addition of two data series.

ADD(c0, c1)

• Inputs: c0 first series, typically closing price, c1 second series to add
• Settings: none
• Output: ADD

Vector Arithmetic Division

Performs element-wise division of two data series.

DIV(c0, c1)

• Inputs: c0 numerator series, typically closing price, c1 denominator series
• Settings: none
• Output: DIV

Vector Arithmetic Multiplication

Performs element-wise multiplication of two data series.

MULT(c0, c1)

• Inputs: c0 first series, typically closing price, c1 second series to multiply
• Settings: none
• Output: MULT

Vector Arithmetic Subtraction

Performs element-wise subtraction of two data series.

SUB(c0, c1)

• Inputs: c0 first series, typically closing price, c1 second series to subtract
• Settings: none
• Output: SUB

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