Class TechnicalAnalysisMethods

Contains various helper methods for technical analysis calculations.

Hierarchy

TechnicalAnalysisMethods

Index

Constructors

Methods

Constructors

constructor

new TechnicalAnalysisMethods(priceChart): TechnicalAnalysisMethods
Parameters
- priceChart: TradingChart
Returns TechnicalAnalysisMethods

Methods

calculateAccumulationDistribution

calculateAccumulationDistribution(closeValues, highValues, lowValues, volumes): number[]
Calculates Accumulation/distribution indicator (A/D) values based on given OHLC and Volume values.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
Returns number[]
An array of Accumulation/Distribution values, or null if calculations are not possible with given values.

calculateAccumulativeSwingIndex

calculateAccumulativeSwingIndex(openValues, highValues, lowValues, closeValues, limitMoveValue): number[]
Calculates Accumulative Swing Index (ASI) values using given data and maximum price change (limit move) values.
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- closeValues: number[]
  
  OHLC-data Close values.
- limitMoveValue: number
  
  Maximum price change in one direction.
Returns number[]
An array of Accumulative Swing Index values, or null if calculations are not possible with given values.

calculateAroon

calculateAroon(highValues, lowValues, n): number[][]
Calculates Aroon Up and Aroon Down values using given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Time period count.
Returns number[][]
An array containing two arrays, the first one has Aroon Up values and the second one Aroon Down values. Returns null if calculations are not possible with given values.

calculateAroonOscillator

calculateAroonOscillator(highValues, lowValues, n): number[]
Calculates Aroon Oscillator values using given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values
- n: number
  
  Time period count.
Returns number[]
An array of Aroon Oscillator values, or null if calculations are not possible with given values.

calculateAverageDailyRange

calculateAverageDailyRange(highValues, lowValues, n): number[]
Calculates Average Daily Range values using given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Time period count.
Returns number[]
An array of Average Daily Range values, or null if calculations are not possible with given values.

calculateAverageDirectionalIndex

calculateAverageDirectionalIndex(closeValues, highValues, lowValues, n): number[][]
Calculates Average Directional Index (ADX) values. Returns also values for Directional Movement Indicators (-DI and +DI).
Parameters
- closeValues: number[]
  
  OHLC data Close values.
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Period count.
Returns number[][]
An array containing three arrays, the first one has ADX values, the second one -DI values, and the third one +DI values. Returns null if calculations are not possible with given values.

calculateAverageTrueRange

calculateAverageTrueRange(closeValues, highValues, lowValues, n): number[]
Calculates Average True Range values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC data Close values.
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Period count.
Returns number[]
An array of Average True Range values, or null if calculations are not possible with given values.

calculateAwesomeOscillator

calculateAwesomeOscillator(highValues, lowValues, shortPeriodCount, longPeriodCount): number[]
Calculates Awesome Oscillator values using given short-term and long-term time period counts.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- shortPeriodCount: number
  
  Short-term period count.
- longPeriodCount: number
  
  Long-term period count.
Returns number[]
An array of Awesome Oscillator values, or null if calculations are not possible with given values.

calculateBalanceOfPower

calculateBalanceOfPower(openValues, highValues, lowValues, closeValues, n, movingAverageType): number[]
Calculates Balance of Power (BOP) values using given moving average type and number of time periods (n) for smoothing.
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- closeValues: number[]
  
  OHLC-data Close values.
- n: number
  
  Time period count.
- movingAverageType: MovingAverageType
  
  Moving average type used for smoothing the indicator values.
Returns number[]
An array of Balance of Power values, or null if calculations are not possible with given values.

calculateBollingerBand

calculateBollingerBand(sourceValues, closeValues, highValues, lowValues, n, standardDeviationMultiplier): number[][]
Calculates Bollinger Band values based on given number of time periods.
Parameters
- sourceValues: number[]
  
  Data values used as a basis for calculations, most commonly OHLC-data Close values.
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Period count.
- standardDeviationMultiplier: number
  
  Number of standard deviations between the moving average line and the upper and the lower bands.
Returns number[][]
An array containing three arrays. The first array has the middle band values, the second has the upper band values, and the third one the lower band values. Returns null if calculations are not possible with given parameters.

calculateCenterOfGravity

calculateCenterOfGravity(dataValues, n, signalPeriods): number[][]
Calculates Center of Gravity (COG) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- signalPeriods: number
  
  Period count for the Signal line.
Returns number[][]
An array containing two arrays: the first one has COG values and the second one Signal values.

calculateChaikinMoneyFlow

calculateChaikinMoneyFlow(closeValues, highValues, lowValues, volumes, periodCount): number[]
Calculates Chaikin Money Flow values using given number of time periods.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- periodCount: number
  
  Period count.
Returns number[]
An array of Chaikin Money Flow values, or null if calculations are not possible with given values.

calculateChaikinOscillator

calculateChaikinOscillator(closeValues, highValues, lowValues, volumes, fastPeriodCount, slowPeriodCount): number[]
Calculates Chaikin Oscillator values using given number of fast and slow time periods.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- fastPeriodCount: number
  
  Fast period count.
- slowPeriodCount: number
  
  Slow period count.
Returns number[]
An array of Chaikin Oscillator values, or null if calculations are not possible with given values.

calculateChaikinVolatility

calculateChaikinVolatility(highValues, lowValues, periodCount, periodCountMA, movingAverageType): number[]
Calculates Chaikin Volatility using given values and moving average.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  Period count for Chaikin Volatility.
- periodCountMA: number
  
  Period count for the moving average used in calculations.
- movingAverageType: MovingAverageType
  
  The type of the moving average used in calculations.
Returns number[]
An array of Chaikin Volatility values, or null if calculations are not possible with given values.

calculateChandeForecastOscillator

calculateChandeForecastOscillator(dataValues, n): number[]
Calculates Chande Forecast Oscillator (CFO) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of CFO values, or null if calculations are not possible with given values.

calculateChandeMomentumOscillator

calculateChandeMomentumOscillator(dataValues, n): number[]
Calculates Chande Momentum Oscillator (CMO) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of CMO values, or null if calculations are not possible with given values.

calculateChoppinessIndex

calculateChoppinessIndex(closeValues, highValues, lowValues, n): number[]
Calculates Choppiness Index (CHOP) values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC data Close values.
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Period count.
Returns number[]
Array of Choppiness Index values, or null if calculation is not possible with given values.

calculateCommodityChannelIndex

calculateCommodityChannelIndex(closeValues, highValues, lowValues, n): number[]
Calculates Commodity Channel Index (CCI) values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC data Close values.
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Period count.
Returns number[]
Array of Commodity Channel Index values, or null if calculation is not possible with given values.

calculateCoppockCurve

calculateCoppockCurve(dataValues, periodCountLongROC, periodCountShortROC, periodCountWMA): number[]
Calculates Coppock Curve values using given time period counts.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- periodCountLongROC: number
  
  Period count for long Rate of Change.
- periodCountShortROC: number
  
  Period count for short Rate of Change.
- periodCountWMA: number
  
  Period count for Weighted Moving Average.
Returns number[]
An array of Coppock Curve values, or null if calculations are not possible with given values.

calculateCorrelationCoefficient

calculateCorrelationCoefficient(dataValues1, dataValues2, n): number[]
Calculates Correlation Coefficient between the two given datasets. If the datasets are of different length, the first values of the longer set are excluded from the calculations.
Parameters
- dataValues1: number[]
  
  First dataset values.
- dataValues2: number[]
  
  Second dataset values.
- n: number
  
  Time period count.
Returns number[]
An array of Correlation Coefficient values, or null if calculations are not possible with given values.

calculateDetrendedPriceOscillator

calculateDetrendedPriceOscillator(dataValues, n, movingAverageType): number[]
Calculates Detrended Price Oscillator (DPO) values using given moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  Moving average to use during calculations.
Returns number[]
An array of DPO values, or null if calculations are not possible with given values.

calculateDonchianChannels

calculateDonchianChannels(highValues, lowValues, n): number[][]
Calculates values for Donchian Channels using given period count (n).
Parameters
- highValues: number[]
  
  OHLC data High values.
- lowValues: number[]
  
  OHLC data Low values.
- n: number
  
  Period count.
Returns number[][]
An array containing three arrays. The first array has the upper band values, the second has the lower band values, and the third one the middle band values. Returns null if calculations are not possible with given parameters.

calculateEaseOfMovement

calculateEaseOfMovement(highValues, lowValues, volumes, n, scale, movingAverageType?): number[]
Calculates Ease of Movement (EOM) values based on given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- n: number
  
  Period count.
- scale: number
  
  Scale for the Volume values to keep them compatible with the other values.
- movingAverageType: MovingAverageType = MovingAverageType.SimpleMovingAverage
  
  Moving average to use during calculations.
Returns number[]
An array of EOM values, or null if calculations are not possible with given values.

calculateEhlerFisherTransform

calculateEhlerFisherTransform(highValues, lowValues, periodCount, rawSmoothingPeriods, fisherSmoothingPeriods, signalPeriodCount): number[][]
Calculates Ehler Fisher Transform (EFT) values based on given time period counts.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  The number of overall time periods (lookup periods).
- rawSmoothingPeriods: number
  
  The number of time periods used for raw smoothing before fisher transform.
- fisherSmoothingPeriods: number
  
  The number of time periods used for final smoothing with EMA.
- signalPeriodCount: number
  
  The number of time periods used to calculate the signal line.
Returns number[][]
An array containing two arrays: the first one has EFT-values and the second one Signal values. Returns null if calculations are not possible with given values.

calculateElderRayIndex

calculateElderRayIndex(sourceValues, highValues, lowValues, n, movingAverageType): number[][]
Calculates Elder-Ray Index (Elder-Ray Power Indicator) using given moving average type and number of time periods (n).
Parameters
- sourceValues: number[]
  
  Data values used as a basis for calculations, most commonly OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  The type of the used moving average.
Returns number[][]
An array containing two arrays: the first one has Bull Power values and the second one Bear Power values. Returns null if calculations are not possible with given values.

calculateElderThermometerCustom

calculateElderThermometerCustom(highValues, lowValues, n): number[][]
Calculates custom Elder Thermometer using given number of time periods.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Time period count.
Returns number[][]
An array containing two arrays: Thermometer Bull values and Thermometer Bear values.

calculateEldersForceIndex

calculateEldersForceIndex(dataValues, volumes, n): number[]
Calculates Elder's Force Index (EFI) using the given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
- n: number
  
  Period count.
Returns number[]
An array of EFI values, or null if calculations are not possible with given values.

calculateExponentialMovingAverage

calculateExponentialMovingAverage(values, n): number[]
Calculates Exponential Moving Average using given number of time periods (n).
Parameters
- values: number[]
  
  Data values to calculate from.
- n: number
  
  The number of values to use in averaging each round (period count).
Returns number[]
Array of Exponential Moving Average values, or null if averaging is not possible for the given values.

calculateFractalChaosBands

calculateFractalChaosBands(highValues, lowValues, periodCount): number[][]
Calculates Fractal Chaos Bands based on the given values and number of time periods.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  The number of bars/candles needed to form a fractal.
Returns number[][]
An array containing two arrays; the first one has the upper band values and the second lower band values. Returns null if calculations are not possible with given values.

calculateFractalChaosOscillator

calculateFractalChaosOscillator(highValues, lowValues, periodCount): number[]
Calculates Fractal Chaos Oscillator (FCO) using given number of time periods.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  The number of bars/candles needed to form a fractal.
Returns number[]
An array of FCO values, or null if calculations are not possible with given values.

calculateGopalakrishnanRangeIndex

calculateGopalakrishnanRangeIndex(highValues, lowValues, n): number[]
Calculates Gopalakrishnan Range Index (GAPO) values based on given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Period count.
Returns number[]
An array of GAPO values, or null if calculations are not possible with given values.

calculateHighLowBands

calculateHighLowBands(dataValues, n, percentage): number[][]
Calculates High Low Bands based on given data values and period count. Uses Triangular Moving Average to calculate the middle band.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- percentage: number
  
  Percentage of the TMA line to position the upper and lower bands.
Returns number[][]
An array containing three arrays. The first array has the middle band values, the second has the upper band values, and the third one the lower band values. Returns null if calculations are not possible with given parameters.

calculateHighMinusLow

calculateHighMinusLow(highValues, lowValues): number[]
Calculates High Minus Low values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
Returns number[]
An array of High Minus Low values, or null if calculations are not possible with given values.

calculateHistoricalVolatilityIndex

calculateHistoricalVolatilityIndex(dataValues, n, periodsPerYear, standardDeviations, useMovingAverage): number[]
Calculates Historical Volatility Index (HVI) using given number of time periods.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- periodsPerYear: number
  
  The number of time periods used for annualizing the indicator.
- standardDeviations: number
  
  The number of standard deviations used in calculations.
- useMovingAverage: boolean
  
  Whether Simple Moving average is used to smooth the standard deviations values during the calculations.
Returns number[]
An array of HVI values, or null if calculations are not possible with given values.

calculateHullMovingAverage

calculateHullMovingAverage(values, n): number[]
Calculates Hull Moving Average using given number of time periods (n).
Parameters
- values: number[]
  
  Data values to calculate from.
- n: number
  
  The number of values to use in averaging each round (period count).
Returns number[]
Array of Hull Moving Average values, or null if averaging is not possible for the given values.

calculateIchimokuCloud

calculateIchimokuCloud(highValues, lowValues, tenkanSenPeriodCount, kijunSenPeriodCount, senkouSpanBPeriodCount): number[][]
Calculates various values related to Ichimoku Cloud. Does not return Chikou Span (Lagging Span) values, since they are the same as OHLC-data Close values. Also, Close values are not needed in the calculations. The returned data does not contain X-values or moving data forward or back.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- tenkanSenPeriodCount: number
  
  Tenkan-Sen (Conversion Line) period count.
- kijunSenPeriodCount: number
  
  Kijun-Sen (Base Line) period count.
- senkouSpanBPeriodCount: number
  
  Senkou Span B (Leading Span B) period count.
Returns number[][]
An array of arrays containing: -Array of Tenkan-Sen (Conversion Line) values. -Array of Kijun-Sen (Base Line) values. -Array of Senkou Span A (Leading Span A) values. -Array of Senkou Span B (Leading Span B) values. Returns null if calculations are not possible with given values.

calculateIntradayMomentumIndex

calculateIntradayMomentumIndex(openValues, closeValues, n): number[]
Calculates Intraday Momentum Index (IMI) values using given number of time periods (n).
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- closeValues: number[]
  
  OHLC-data Close values.
- n: number
  
  Period count.
Returns number[]
An array of IMI values, or null if calculations are not possible with given values.

calculateKeltnerChannels

calculateKeltnerChannels(closeValues, highValues, lowValues, periodCountEMA, periodCountATR, multiplier): number[][]
Calculates values Keltner Channels. Uses Exponential Moving Average (EMA) of the typical price for the middle line and Average True Range (ATR) for the upper and lower bands.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCountEMA: number
  
  Period count for EMA.
- periodCountATR: number
  
  Period count for ATR.
- multiplier: number
  
  Multiplier for ATR.
Returns number[][]
An array containing three arrays: an array for EMA values, an array for upper channel values, and an array for lower channel values. Returns null if calculations are not possible with given values.

calculateKlingerVolumeOscillator

calculateKlingerVolumeOscillator(closeValues, highValues, lowValues, volumes, shortPeriodCount, longPeriodCount, signalPeriodCount, movingAverageType, movingAverageSignal): number[][]
Calculates Klinger Volume Oscillator (KVO) using given time period count and moving average types.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- shortPeriodCount: number
  
  Time period count for the shorter moving average.
- longPeriodCount: number
  
  Time period count for the longer moving average.
- signalPeriodCount: number
  
  Time period count for the Signal line.
- movingAverageType: MovingAverageType
  
  Moving average used to calculate short and long averages.
- movingAverageSignal: MovingAverageType
  
  Moving average used to calculate the Signal line.
Returns number[][]
An array containing three arrays. The first has the KVO values, the second the Signal values, and the third has the histogram values. Returns null if calculations are not possible with given values.

calculateKurtosis

calculateKurtosis(dataValues, n, movingAverageType): number[]
Calculates Kurtosis values based on given moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  The type of the used moving average.
Returns number[]
An array of Kurtosis values, or null if calculations are not possible with given values.

calculateLinearRegression

calculateLinearRegression(dataValues, periodCount): number[][]
Calculates Linear Regression indicator values using given number of time periods.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- periodCount: number
  
  Time period count.
Returns number[][]
An array containing four data arrays: -Linear Regression Slope values. -Linear Regression Intercept values. -Linear Regression Forecast values. -Linear regression R Squared (R2) values. Returns null if calculations are not possible with given values.

calculateMACD

calculateMACD(dataValues, shortPeriod, longPeriod, signalPeriod): number[][]
Calculates MACD, Signal Line, and Histogram.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- shortPeriod: number
  
  Short period count.
- longPeriod: number
  
  Long period count.
- signalPeriod: number
  
  Signal period count.
Returns number[][]
An array containing three arrays, the first one has MACD values, the second Signal values, and the third Histogram values. Returns null if calculations are not possible with given values.

calculateMACDCustom

calculateMACDCustom(dataValues, shortPeriod, longPeriod, signalPeriod, movingAverageShort, movingAverageLong, movingAverageSignal): number[][]
Calculates MACD, Signal Line, and Histogram using given moving average types.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- shortPeriod: number
  
  Short period count.
- longPeriod: number
  
  Long period count.
- signalPeriod: number
  
  Signal period count.
- movingAverageShort: MovingAverageType
  
  Moving average type used to calculate the short moving average.
- movingAverageLong: MovingAverageType
  
  Moving average type used to calculate the long moving average.
- movingAverageSignal: MovingAverageType
  
  Moving average type used to calculate the signal line.
Returns number[][]
An array containing three arrays, the first one has MACD values, the second Signal values, and the third Histogram values. Returns null if calculations are not possible with given values.

calculateMarketFacilitationIndex

calculateMarketFacilitationIndex(highValues, lowValues, volumes): number[][]
Calculates Market Facilitation Index values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
Returns number[][]
An array containing two arrays: the first one has MFI values, and the second one has the bar colors as numbers. 1 = green (Green), 2 = blue (Fake), 3 = pink (Squat), 4 = brown (Fade) Returns null if calculations are not possible with given values.

calculateMassIndex

calculateMassIndex(highValues, lowValues, n): number[]
Calculates Mass Index values using given number of time periods (n).
Parameters
- highValues: number[]
  
  OHLC-data High values
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Period count.
Returns number[]
An array of Mass Index values, or null if calculations are not possible with given values.

calculateMedianPrice

calculateMedianPrice(highValues, lowValues): number[]
Calculates Median Prices based on given High and Low values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
Returns number[]
An array of Median Prices, or null if calculations are not possible with given values.

calculateMomentumOscillator

calculateMomentumOscillator(dataValues, n): number[]
Calculates Momentum Oscillator values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
Returns number[]
An array of Momentum Oscillator values, or null if calculations are not possible with given values.

calculateMoneyFlowIndex

calculateMoneyFlowIndex(closeValues, highValues, lowValues, volumes, n): number[]
Calculates Money Flow Index values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- n: number
  
  Period count.
Returns number[]
An array of Money Flow Index values, or null if calculations are not possible with given values.

calculateMovingAverageEnvelopes

calculateMovingAverageEnvelopes(dataValues, n, percentage, movingAverageType): number[][]
Calculates Moving Average Envelopes based on given values and moving average type.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count for the moving average.
- percentage: number
  
  Percentage of the moving average line to position the upper and lower bands.
- movingAverageType: MovingAverageType
  
  The moving average type used to calculate the envelopes.
Returns number[][]
An array containing three arrays. The first array has the middle band values, the second has the upper band values, and the third one the lower band values. Returns null if calculations are not possible with given parameters.

calculateNegativeVolumeIndex

calculateNegativeVolumeIndex(dataValues, volumes): number[]
Calculates Negative Volume Index (NVI) values based on given data and volume values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
Returns number[]
An array of NVI values, or null if calculations are not possible with given values.

calculateOnBalanceVolume

calculateOnBalanceVolume(dataValues, volumes, startOBV?): number[]
Calculates On-Balance Volume values based on given data and Volume values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
- startOBV: number = 0
  
  Optional starting value to which Volume values are added or subtracted from. If not given the first value will be the first Volume value.
Returns number[]
An array of On-Balance Volume values, or null if calculations are not possible with given values.

calculateParabolicSAR

calculateParabolicSAR(highValues, lowValues, accelerationFactor, maximumAccelerationFactor): number[]
Calculates Parabolic SAR values using given values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- accelerationFactor: number
  
  Acceleration Factor. Used as an initial values and as an incremental value.
- maximumAccelerationFactor: number
  
  Maximum value for Acceleration Factor.
Returns number[]
An array of Parabolic SAR values. Return null if calculations are not possible with given values.

calculatePercentagePriceOscillator

calculatePercentagePriceOscillator(dataValues, longPeriod, shortPeriod, signalPeriod): number[][]
Calculates Percentage Price Oscillator values using given number of time periods (n). Returns also Signal and Histogram values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- longPeriod: number
  
  Long period count.
- shortPeriod: number
  
  Short period count.
- signalPeriod: number
  
  Signal period count.
Returns number[][]
An array containing three arrays, the first one has PPO values, the second Signal values, and the third Histogram values. Returns null if calculations are not possible with given values.

calculatePerformanceIndex

calculatePerformanceIndex(dataValues): number[]
Calculates Performance Index values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
Returns number[]
An array of Performance Index values, or null if calculations are not possible with given values.

calculatePositiveVolumeIndex

calculatePositiveVolumeIndex(dataValues, volumes): number[]
Calculates Positive Volume Index (PVI) values based on given data and volume values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
Returns number[]
An array of PVI values, or null if calculations are not possible with given values.

calculatePrettyGoodOscillator

calculatePrettyGoodOscillator(sourceValues, closeValues, highValues, lowValues, periodCountMA, periodCountATR, movingAverageMA, movingAverageATR): number[]
Calculates Pretty Good Oscillator (PGO) values using given number of time periods and moving average types.
Parameters
- sourceValues: number[]
  
  Data values used as a basis for calculations, most commonly OHLC-data Close values.
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCountMA: number
  
  The number of time periods used to calculate the moving averages.
- periodCountATR: number
  
  The number of time periods used to calculate the Average True Range.
- movingAverageMA: MovingAverageType
  
  The type of the OHLC-data based moving average.
- movingAverageATR: MovingAverageType
  
  The type of the Average True Range based moving average.
Returns number[]
An array of PGO values, or null if calculations are not possible with given values.

calculatePriceVolumeTrend

calculatePriceVolumeTrend(dataValues, volumes): number[]
Calculates Price Volume Trend (PVT) using given price and volume values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
Returns number[]
An array of PVT values, or null if calculations are not possible with given values.

calculatePrimeNumberBands

calculatePrimeNumberBands(dataValues): number[][]
Calculates Prime Number Bands based on given values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
Returns number[][]
An array containing two arrays. The first one has upper bands values and the second lower band values. Returns null if calculations are not possible with given values.

calculatePrimeNumberOscillator

calculatePrimeNumberOscillator(dataValues): number[]
Calculates Prime Number Oscillator (PNO) values based on given data values.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
Returns number[]
An array of PNO values, or null if calculations are not possible with given values.

calculateQStick

calculateQStick(openValues, closeValues, n, movingAverageType): number[]
Calculates QStick values using given moving average and number of time periods (n).
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- closeValues: number[]
  
  OHLC-data Close values.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  Moving average to use during calculations.
Returns number[]
An array of QStick values, or null if calculations are not possible with given values.

calculateRainbowOscillator

calculateRainbowOscillator(dataValues, periodCount, lookbackPeriods, smoothingLevels, movingAverageType): number[][]
Calculates Rainbow Oscillator values using given parameters and moving average type.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- periodCount: number
  
  The number of time periods used for calculating the series of moving averages.
- lookbackPeriods: number
  
  The number of time periods checked when finding out the highest and lowest prices.
- smoothingLevels: number
  
  The number of times the oscillator is smoothed with a moving average.
- movingAverageType: MovingAverageType
  
  Moving average type used for calculating the series of averages.
Returns number[][]
An array containing three arrays: the first array has Rainbow Oscillator values, the second array has values for the upper band, and the third array has values for the lower band. Returns null if calculations are not possible with given values.

calculateRandomWalkIndex

calculateRandomWalkIndex(closeValues, highValues, lowValues, n): number[][]
Calculates Random Walk Index (RWI) values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Time period count.
Returns number[][]
An array containing two arrays: the first one has RWI High values and the second one RWI Low values. Returns null if calculations are not possible with given values.

calculateRangeActionVerificationIndex

calculateRangeActionVerificationIndex(dataValues, periodCountShort, periodCountLong, movingAverageShort, movingAverageLong): number[]
Calculates Range Action Verification Index (RAVI) using given moving average types and time period counts.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- periodCountShort: number
  
  Period count for the shorter moving average.
- periodCountLong: number
  
  Period count for the longer moving average.
- movingAverageShort: MovingAverageType
  
  The type of the shorter moving average.
- movingAverageLong: MovingAverageType
  
  The type of the longer moving average.
Returns number[]
An array of RAVI values, or null if calculations are not possible with given values.

calculateRateOfChange

calculateRateOfChange(dataValues, n): number[]
Calculates Rate of Change (ROC) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
Array of Rate of Change values, or null if calculation is not possible with given values.

calculateRelativeStrengthIndex

calculateRelativeStrengthIndex(dataValues, n): number[]
Calculates Relative Strength Index (RSI) using given number of time periods, N.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Number of values over which the smoothing calculation is applied.
Returns number[]
Array of Relative Strength Index values, or null if calculations are not possible.

calculateSQNTrend

calculateSQNTrend(dataValues, n, movingAverageType): number[]
Calculates SQN Trend (System Quality Number) using given values, moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- movingAverageType: MovingAverageType
  
  Moving average type used during calculations.
Returns number[]
An array of SQN Trend values, or null if calculations are not possible with given values.

calculateSchaffTrendCycle

calculateSchaffTrendCycle(dataValues, macdShortPeriods, macdLongPeriods, firstStochPeriods, firstStochKPeriods, firstStochDPeriods, secondStochPeriods, secondStochKPeriods, secondStochDPeriods, macdShortMA, macdLongMA, firstStochKMA, firstStochDMA, secondStochKMA, secondStochDMA): number[]
Calculates Schaff Trend Cycle (STC) values using given time period counts and moving averages.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- macdShortPeriods: number
  
  The short period count for MACD calculations.
- macdLongPeriods: number
  
  The long period count for MACD calculations.
- firstStochPeriods: number
  
  The time period count used to calculate the first Stochastic, that is the lookback periods when finding the highest and lowest values.
- firstStochKPeriods: number
  
  The time period count used to smooth the first Stochastic (%K).
- firstStochDPeriods: number
  
  The time period count used to calculate the first %D values.
- secondStochPeriods: number
  
  The time period count used to calculate the second Stochastic, that is the lookback periods when finding the highest and lowest values.
- secondStochKPeriods: number
  
  The time period count used to smooth the second Stochastic (%K).
- secondStochDPeriods: number
  
  The time period count used to calculate the second %D values, in other words the final STC values.
- macdShortMA: MovingAverageType
  
  Moving average type to calculate the short moving average during MACD calculations.
- macdLongMA: MovingAverageType
  
  Moving average type to calculate the long moving average during MACD calculations.
- firstStochKMA: MovingAverageType
  
  Moving average type to calculate the first Stochastic %K values.
- firstStochDMA: MovingAverageType
  
  Moving average type to calculate the first Stochastic %D values.
- secondStochKMA: MovingAverageType
  
  Moving average type to calculate the second Stochastic %K values.
- secondStochDMA: MovingAverageType
  
  Moving average type to calculate the second Stochastic %D values.
Returns number[]
An array of STC values, or null if calculations are not possible with given values.

calculateSchaffTrendCycleSignal

calculateSchaffTrendCycleSignal(dataValues, macdShortPeriods, macdLongPeriods, macdSignalPeriods, firstStochPeriods, firstStochKPeriods, firstStochDPeriods, secondStochPeriods, secondStochKPeriods, secondStochDPeriods, macdShortMA, macdLongMA, macdSignalMA, firstStochKMA, firstStochDMA, secondStochKMA, secondStochDMA): number[]
Calculates Schaff Trend Cycle (STC) values using given time period counts and moving averages. This version uses MACD's Signal line as basis for Stochastic calculations.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- macdShortPeriods: number
  
  The short period count for MACD calculations.
- macdLongPeriods: number
  
  The long period count for MACD calculations.
- macdSignalPeriods: number
  
  The signal period count for MACD calculations.
- firstStochPeriods: number
  
  The time period count used to calculate the first Stochastic, that is the lookback periods when finding the highest and lowest values.
- firstStochKPeriods: number
  
  The time period count used to smooth the first Stochastic (%K).
- firstStochDPeriods: number
  
  The time period count used to calculate the first %D values.
- secondStochPeriods: number
  
  The time period count used to calculate the second Stochastic, that is the lookback periods when finding the highest and lowest values.
- secondStochKPeriods: number
  
  The time period count used to smooth the second Stochastic (%K).
- secondStochDPeriods: number
  
  The time period count used to calculate the second %D values, in other words the final STC values.
- macdShortMA: MovingAverageType
  
  Moving average type to calculate the short moving average during MACD calculations.
- macdLongMA: MovingAverageType
  
  Moving average type to calculate the long moving average during MACD calculations.
- macdSignalMA: MovingAverageType
  
  Moving average type to calculate the signal line during MACD calculations.
- firstStochKMA: MovingAverageType
  
  Moving average type to calculate the first Stochastic %K values.
- firstStochDMA: MovingAverageType
  
  Moving average type to calculate the first Stochastic %D values.
- secondStochKMA: MovingAverageType
  
  Moving average type to calculate the second Stochastic %K values.
- secondStochDMA: MovingAverageType
  
  Moving average type to calculate the second Stochastic %D values.
Returns number[]
An array of STC values, or null if calculations are not possible with given values.

calculateSimpleMovingAverage

calculateSimpleMovingAverage(dataValues, n): number[]
Calculates Simple Moving Average using given averaging frame length (window length, or period count N).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  The number of values to use in averaging each round (period count).
Returns number[]
Array of Simple Moving Average values, or null if averaging is not possible for the given values.

calculateSkewness

calculateSkewness(dataValues, n, movingAverageType): number[]
Calculates Skewness values based on given moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- movingAverageType: MovingAverageType
  
  The type of the used moving average.
Returns number[]
An array of Skewness values, or null if calculations are not possible with given values.

calculateStandardDeviation

calculateStandardDeviation(dataValues, n, movingAverageType?): number[]
Calculates Standard Deviation values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- movingAverageType: MovingAverageType = MovingAverageType.None
  
  Optional moving average type, default is no averaging.
Returns number[]
An array of Standard Deviation values, or null if calculations are not possible with given values.

calculateStandardError

calculateStandardError(dataValues, n, movingAverageType): number[]
Calculates Standard Error values using given moving average and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  Moving average to use during calculations.
Returns number[]
An array of Standard Error values, or null if calculations are not possible with given values.

calculateStandardErrorBands

calculateStandardErrorBands(dataValues, n, multiplier, movingAverageType): number[][]
Calculates Standard Error Bands values using given moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- multiplier: number
  
  Multiplier for the standard error used when calculating upper and lower bands.
- movingAverageType: MovingAverageType
  
  The type of the used moving average.
Returns number[][]
An array containing three arrays. The first array has the middle band values, the second has the upper band values, and the third one the lower band values. Returns null if calculations are not possible with given parameters.

calculateStochasticMomentumIndex

calculateStochasticMomentumIndex(closeValues, highValues, lowValues, periodCount, firstSmoothPeriods, doubleSmoothPeriods, movingAveragePeriods, oscillatorMovingAverage, maMovingAverage): number[][]
Calculates Stochastic Momentum Index (SMI) values using given moving average types and time period counts.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  The number of time periods to calculate the stochastic (%K) line. This is the lookback period for High/Low range.
- firstSmoothPeriods: number
  
  The number of time periods used for the first smoothing of the stochastic (%K) values.
- doubleSmoothPeriods: number
  
  The number of time periods used for the second (double) smoothing of the stochastic (%K) values.
- movingAveragePeriods: number
  
  The number of time periods used to calculate the moving average (%D) line.
- oscillatorMovingAverage: MovingAverageType
  
  The moving average used to smooth the oscillator (%K) line.
- maMovingAverage: MovingAverageType
  
  The moving average used to calculate the moving average (%D) line.
Returns number[][]
An array of two arrays: the first one has SMI values (%K) while the second one has moving average values (%D). Returns null if calculations are not possible with given values.

calculateStochasticOscillator

calculateStochasticOscillator(closeValues, highValues, lowValues, n, movingAveragePeriods): number[][]
Calculates Stochastic Oscillator values using given number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  The number of time periods used to calculate the oscillator.
- movingAveragePeriods: number
  
  The number of time periods used to calculate the moving average.
Returns number[][]
An array containing two arrays, the first one has Stochastic Oscillator values and the second one moving average values. Returns null if calculation is not possible with given values.

calculateStochasticOscillatorSmoothed

calculateStochasticOscillatorSmoothed(closeValues, highValues, lowValues, oscillatorPeriods, oscillatorSmoothingPeriods, movingAveragePeriods, oscillatorMovingAverage, maMovingAverage): number[][]
Calculates Smoothed Stochastic Oscillator values using given moving average types and time period counts.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- oscillatorPeriods: number
  
  The number of time periods used to calculate the stochastic (%K) values.
- oscillatorSmoothingPeriods: number
  
  The number of time periods used to smooth the stochastic (%K) values.
- movingAveragePeriods: number
  
  The number of time periods used to calculate the moving average (%D) values.
- oscillatorMovingAverage: MovingAverageType
  
  The moving average type used to smooth the stochastic (%K) values.
- maMovingAverage: MovingAverageType
  
  The moving average type used to calculate the moving average (%D) values.
Returns number[][]
An array containing two arrays: the first one has stochastic (%K) values while the second one has the moving average (%D) values. Returns null if calculations are not possible with given values.

calculateStollerAverageChannels

calculateStollerAverageChannels(sourceValues, closeValues, highValues, lowValues, periodCountMA, periodCountATR, multiplier, movingAverageType): number[][]
Calculates Stoller Average Range Channels (STARC) using given moving average type and number of time periods.
Parameters
- sourceValues: number[]
  
  Data values used as a basis for calculations, most commonly OHLC-data Close values.
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCountMA: number
  
  Period count for the moving average.
- periodCountATR: number
  
  Period count for the Average True Range.
- multiplier: number
  
  Multiplier for the Average True Range.
- movingAverageType: MovingAverageType
  
  The type of the used moving average.
Returns number[][]
An array containing three arrays: an array for moving average values, an array for upper channel values, and an array for lower channel values. Returns null if calculations are not possible with given values.

calculateSuperTrend

calculateSuperTrend(closeValues, highValues, lowValues, periodCount, multiplier): number[]
Calculates Supertrend values using given number of time periods.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- periodCount: number
  
  Period count.
- multiplier: number
  
  Multiplier for ATR.
Returns number[]
An array of Supertrend values, or null if calculations are not possible with values.

calculateSwingIndex

calculateSwingIndex(openValues, highValues, lowValues, closeValues, limitMoveValue): number[]
Calculates Swing Index (SI) values using given data and maximum price change (limit move) values.
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- closeValues: number[]
  
  OHLC-data Close values.
- limitMoveValue: number
  
  Maximum price change in one direction.
Returns number[]
An array of Swing Index values, or null if calculations are not possible with given values.

calculateTimeSeriesMovingAverage

calculateTimeSeriesMovingAverage(dataValues, n): number[]
Calculates Time Series Moving Average (TSMA) values using given number of time periods (n). Uses least squares regression fitting.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of TSMA values, or null if calculations are not possible with given values.

calculateTradeVolumeIndex

calculateTradeVolumeIndex(dataValues, volumes, minimumTickValue): number[]
Calculates Trade Volume Index (TVI) values using given minimum tick value.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
- minimumTickValue: number
  
  Minimum tick value to be used in the calculations.
Returns number[]
An array of TVI values, or null if calculations are not possible with given values.

calculateTriangularMovingAverage

calculateTriangularMovingAverage(dataValues, n): number[]
Calculates Triangular Moving Average (TMA) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of TMA values, or null if calculations are not possible with given values.

calculateTripleExponentialAverage

calculateTripleExponentialAverage(dataValues, n): number[][]
Calculates Triple Exponential Average (TRIX) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[][]
An array containing two arrays, the first one has Triple Exponential Average values and the second one 9-day Exponential Moving Average values. Returns null if calculations are not possible with given values.

calculateTrueStrengthIndex

calculateTrueStrengthIndex(dataValues, priceChangePeriods, firstSmoothPeriods, doubleSmoothPeriods, signalPeriods, firstSmoothMovingAverage, doubleSmoothMovingAverage, signalMovingAverage): number[][]
Calculates True Strength Index (TSI) values using given time period counts and moving average types.
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- priceChangePeriods: number
  
  Time periods used to calculate the price change (value - value n periods ago).
- firstSmoothPeriods: number
  
  Time periods used to calculate the first smoothing.
- doubleSmoothPeriods: number
  
  Time periods used to calculate the second (double) smoothing.
- signalPeriods: number
  
  Time periods used to calculate the signal values.
- firstSmoothMovingAverage: MovingAverageType
  
  Moving average type used for the first smoothing.
- doubleSmoothMovingAverage: MovingAverageType
  
  Moving average type used for the second (double) smoothing.
- signalMovingAverage: MovingAverageType
  
  Moving average type used to calculate the signal values.
Returns number[][]
An array containing two arrays: the first one has TSI values while the second one has the signal values. Returns null if calculations are not possible with given values.

calculateTwiggsMoneyFlow

calculateTwiggsMoneyFlow(closeValues, highValues, lowValues, volumes, n): number[]
Calculates Twiggs Money Flow values using given OHLC- and Volume values and number of time periods (n).
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- n: number
  
  Period count.
Returns number[]
An array of Twiggs Money Flow values, or null if calculations are not possible with given values.

calculateTypicalPrice

calculateTypicalPrice(highValues, lowValues, closeValues): number[]
Calculates Typical Prices based on given High, Low and Close values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- closeValues: number[]
  
  OHLC-data Close values.
Returns number[]
An array of Typical Prices, or null if calculations are not possible with given values.

calculateUltimateOscillator

calculateUltimateOscillator(closeValues, highValues, lowValues, shortPeriods, midPeriods, longPeriods): number[]
Calculates Ultimate Oscillator (UO) values using given time period counts.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- shortPeriods: number
  
  Period count for the shortest average.
- midPeriods: number
  
  Period count for the middle average.
- longPeriods: number
  
  Period count for the longest average.
Returns number[]
An array of Ultimate Oscillator values, or null if calculations are not possible with given values.

calculateUltimateOscillatorSmoothed

calculateUltimateOscillatorSmoothed(closeValues, highValues, lowValues, shortPeriods, midPeriods, longPeriods, movingAverageType): number[]
Calculates Ultimate Oscillator Smoothed (UO ST) values using given time period counts and moving average.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- shortPeriods: number
  
  Period count for the shortest average.
- midPeriods: number
  
  Period count for the middle average.
- longPeriods: number
  
  Period count for the longest average.
- movingAverageType: MovingAverageType
  
  Moving average to be used in smoothing
Returns number[]
An array of Ultimate Oscillator ST values, or null if calculations are not possible with given values.

calculateVIDYA

calculateVIDYA(dataValues, n, periodCountStDevShort, periodCountStDevLong): number[]
Calculates Variable Index Dynamic Average (VIDYA) values using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- periodCountStDevShort: number
  
  Short standard deviation period count used in VIDYA calculations.
- periodCountStDevLong: number
  
  Long standard deviation period count used in VIDYA calculations.
Returns number[]
An array of VIDYA values, or null if calculations are not possible with given values.

calculateVariableMovingAverage

calculateVariableMovingAverage(dataValues, n): number[]
Calculates Variable Moving Average (VMA) values using the given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of VMA values, or null if calculations are not possible with given values.

calculateVerticalHorizontalFilter

calculateVerticalHorizontalFilter(dataValues, n): number[]
Calculates Vertical Horizontal Filter (VHF) using given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of VHF values, or null if calculations are not possible with given values.

calculateVolumeOscillator

calculateVolumeOscillator(volumes, shortPeriodCount, longPeriodCount, signalPeriodCount, calculateAsPercentage, movingAverageType, movingAverageSignal): number[][]
Calculates Volume Oscillator (VO) using the given time period counts and moving average types.
Parameters
- volumes: number[]
  
  Volume values to calculate from.
- shortPeriodCount: number
  
  Short-term period count.
- longPeriodCount: number
  
  Long-term period count.
- signalPeriodCount: number
  
  Period count for signal line.
- calculateAsPercentage: boolean
  
  When enabled, the difference between the short and long moving averages is calculated as a percentage and not as an actual volume difference.
- movingAverageType: MovingAverageType
  
  Moving average type for the short and long averages.
- movingAverageSignal: MovingAverageType
  
  Moving average type for the signal line.
Returns number[][]
An array containing three arrays. The first has the VO values, the second the Signal values, and the third has the histogram values. Returns null if calculations are not possible with given values.

calculateVolumeRateOfChange

calculateVolumeRateOfChange(volumes, n): number[]
Calculates Volume Rate of Change (VROC) values using given number of time periods (n).
Parameters
- volumes: number[]
  
  Volumes values to calculate from.
- n: number
  
  Period count.
Returns number[]
An array of VROC values, or null if calculations are not possible with given values.

calculateVolumeWeightedMovingAverage

calculateVolumeWeightedMovingAverage(dataValues, volumes, n): number[]
Calculates Volume Weighted Moving Average (VWMA) values using the given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- volumes: number[]
  
  Volume values.
- n: number
  
  Time period count.
Returns number[]
An array of VWMA values, or null if calculations are not possible with given values.

calculateWeightedClose

calculateWeightedClose(highValues, lowValues, closeValues): number[]
Calculates Weighted Close values based on given High, Low and Close values.
Parameters
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- closeValues: number[]
  
  OHLC-data Close values.
Returns number[]
An array of Weighted Close values, or null if calculations are not possible with given values.

calculateWeightedMovingAverage

calculateWeightedMovingAverage(values, n): number[]
Calculates Weighted Moving Average using given number of time periods (n).
Parameters
- values: number[]
  
  Data values to calculate from.
- n: number
  
  The number of values to use in averaging each round (period count).
Returns number[]
Array of Weighted Moving Average values, or null if averaging is not possible for the given values.

calculateWellesWilderSmoothing

calculateWellesWilderSmoothing(dataValues, n): number[]
Calculates Welles Wilder Smoothing (WWS) for the data values using the given number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
Returns number[]
An array of WWS values, or null if calculations are not possible with given values.

calculateWilliamsAccumulationDistribution

calculateWilliamsAccumulationDistribution(closeValues, highValues, lowValues, volumes, useVolume): number[]
Calculates Williams Accumulation Distribution (WAD) values.
Parameters
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values. Can be null if useVolume is set false (Volume values not incorporated into calculations).
- useVolume: boolean
  
  Sets whether to take Volume into account during calculations.
Returns number[]
An array of WAD values, or null if calculations are not possible with given values.

calculateWilliamsPercentRange

calculateWilliamsPercentRange(sourceValues, highValues, lowValues, n): number[]
Calculates Williams Percent Range values using given number of time periods (n).
Parameters
- sourceValues: number[]
  
  Data values used as a basis for calculations, most commonly OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- n: number
  
  Time period count.
Returns number[]
An array of Williams Percent Range values, or null if calculations are not possible with given values.

calculateWilliamsVariableAccumulationDistribution

calculateWilliamsVariableAccumulationDistribution(openValues, closeValues, highValues, lowValues, volumes, n, movingAverageType): number[]
Calculates Williams Variable Accumulation Distribution (WVAD) values using given moving average and number of time periods (n).
Parameters
- openValues: number[]
  
  OHLC-data Open values.
- closeValues: number[]
  
  OHLC-data Close values.
- highValues: number[]
  
  OHLC-data High values.
- lowValues: number[]
  
  OHLC-data Low values.
- volumes: number[]
  
  Volume values.
- n: number
  
  Period count.
- movingAverageType: MovingAverageType
  
  Moving average to use during calculations.
Returns number[]
An array of WVAD values, or null if calculations are not possible with given values.

calculateZValue

calculateZValue(dataValues, n, movingAverageType): number[]
Calculates Z-Value values based on given moving average type and number of time periods (n).
Parameters
- dataValues: number[]
  
  Data values to calculate from.
- n: number
  
  Time period count.
- movingAverageType: MovingAverageType
  
  Moving average to use during calculations.
Returns number[]
An array of Z-Values, or null if calculations are not possible with given values.

isPrime

isPrime(value): boolean
Tests if given value is a prime number.
Parameters
- value: number
  
  Value to test.
Returns boolean
True if value is a prime number.

linearRegression

linearRegression(xInFactorization, yInFactorization, xValuesToFit): number[]
Calculate linear line fit for given points.
Parameters
- xInFactorization: number[]
  
  X-values that are used to calculate the factors. This is the point set where the regression line is fitted to.
- yInFactorization: number[]
  
  Y-values that are used to calculate the factors. Length must be equal to xInFactorization length.
- xValuesToFit: number[]
  
  X-values whose Y values are to be solved, using the factors.
Returns number[]
Array containing fitted Y-values. Returns null if unable to calculate with given values.

Class TechnicalAnalysisMethods

Hierarchy

Index

Constructors

Methods

Constructors

constructor

Parameters

priceChart: TradingChart

Returns TechnicalAnalysisMethods

Methods

calculateAccumulationDistribution

Parameters

closeValues: number[]

highValues: number[]

lowValues: number[]

volumes: number[]

Returns number[]

calculateAccumulativeSwingIndex

Parameters

openValues: number[]

highValues: number[]

lowValues: number[]

closeValues: number[]

limitMoveValue: number

Returns number[]

calculateAroon

Parameters

highValues: number[]

lowValues: number[]

n: number

Returns number[][]

calculateAroonOscillator

Parameters

highValues: number[]

lowValues: number[]

n: number

Returns number[]

calculateAverageDailyRange

Parameters

highValues: number[]

lowValues: number[]

n: number

Returns number[]

calculateAverageDirectionalIndex

Parameters

closeValues: number[]

highValues: number[]

lowValues: number[]

n: number

Returns number[][]

calculateAverageTrueRange

Parameters

closeValues: number[]

highValues: number[]

lowValues: number[]

n: number

Returns number[]

calculateAwesomeOscillator

Parameters

highValues: number[]

lowValues: number[]

shortPeriodCount: number

longPeriodCount: number

Returns number[]

calculateBalanceOfPower

Parameters

openValues: number[]

highValues: number[]

lowValues: number[]

closeValues: number[]

n: number

movingAverageType: MovingAverageType

Returns number[]

calculateBollingerBand

Parameters

sourceValues: number[]

closeValues: number[]

highValues: number[]

lowValues: number[]