PINE LIBRARY
업데이트됨 Library_Smoothers

Library "Library_Smoothers"
CorrectedMA(Src, Len)
CorrectedMA The strengths of the corrected Average (CA) is that the current value of the time series must exceed a the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals when the trend is in a weak phase.
Parameters:
Src
Len
Returns: The Corrected source.
EHMA(src, len)
EMA Exponential Moving Average.
Parameters:
src: Source to act upon
len
Returns: EMA of source
FRAMA(src, len, FC, SC)
FRAMA Fractal Adaptive Moving Average
Parameters:
src: Source to act upon
len: Length of moving average
FC: Fast moving average
SC: Slow moving average
Returns: FRAMA of source
Jurik(src, length, phase, power)
Jurik A low lag filter
Parameters:
src: Source
length: Length for smoothing
phase: Phase range is ±100
power: Mathematical power to use. Doesn't need to be whole numbers
Returns: Jurik of source
SMMA(src, len)
SMMA Smoothed moving average. Think of the SMMA as a hybrid of its better-known siblings — the simple moving average (SMA) and the exponential moving average (EMA).
Parameters:
src: Source
len
Returns: SMMA of source
SuperSmoother(src, len)
SuperSmoother
Parameters:
src: Source to smooth
len
Returns: SuperSmoother of the source
TMA(src, len)
TMA Triangular Moving Average
Parameters:
src: Source
len
Returns: TMA of source
TSF(src, len)
TSF Time Series Forecast. Uses linear regression.
Parameters:
src: Source
len
Returns: TSF of source
VIDYA(src, len)
VIDYA Chande's Variable Index Dynamic Average. See fxcorporate.com/help/MS/NOTFIFO/i_Vidya.html
Parameters:
src: Source
len
Returns: VIDYA of source
VAWMA(src, len, startingWeight, volumeDefault)
VAWMA = VWMA and WMA combined. Simply put, this attempts to determine the average price per share over time weighted heavier for recent values. Uses a triangular algorithm to taper off values in the past (same as WMA does).
Parameters:
src: Source
len: Length
startingWeight
volumeDefault: The default value to use when a chart has no volume.
Returns: The VAWMA of the source.
WWMA(src, len)
WWMA Welles Wilder Moving Average
Parameters:
src: Source
len
Returns: The WWMA of the source
ZLEMA(src, len)
ZLEMA Zero Lag Expotential Moving Average
Parameters:
src: Source
len
Returns: The ZLEMA of the source
SmootherType(mode, src, len, fastMA, slowMA, offset, phase, power, startingWeight, volumeDefault, Corrected)
Performs the specified moving average
Parameters:
mode: Name of moving average
src: the source to apply the MA type
len
fastMA: FRAMA fast moving average
slowMA: FRAMA slow moving average
offset: Linear regression offset
phase: Jurik phase
power: Jurik power
startingWeight: VAWMA starting weight
volumeDefault: VAWMA default volume
Corrected
Returns: The MA smoothed source
CorrectedMA(Src, Len)
CorrectedMA The strengths of the corrected Average (CA) is that the current value of the time series must exceed a the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals when the trend is in a weak phase.
Parameters:
Src
Len
Returns: The Corrected source.
EHMA(src, len)
EMA Exponential Moving Average.
Parameters:
src: Source to act upon
len
Returns: EMA of source
FRAMA(src, len, FC, SC)
FRAMA Fractal Adaptive Moving Average
Parameters:
src: Source to act upon
len: Length of moving average
FC: Fast moving average
SC: Slow moving average
Returns: FRAMA of source
Jurik(src, length, phase, power)
Jurik A low lag filter
Parameters:
src: Source
length: Length for smoothing
phase: Phase range is ±100
power: Mathematical power to use. Doesn't need to be whole numbers
Returns: Jurik of source
SMMA(src, len)
SMMA Smoothed moving average. Think of the SMMA as a hybrid of its better-known siblings — the simple moving average (SMA) and the exponential moving average (EMA).
Parameters:
src: Source
len
Returns: SMMA of source
SuperSmoother(src, len)
SuperSmoother
Parameters:
src: Source to smooth
len
Returns: SuperSmoother of the source
TMA(src, len)
TMA Triangular Moving Average
Parameters:
src: Source
len
Returns: TMA of source
TSF(src, len)
TSF Time Series Forecast. Uses linear regression.
Parameters:
src: Source
len
Returns: TSF of source
VIDYA(src, len)
VIDYA Chande's Variable Index Dynamic Average. See fxcorporate.com/help/MS/NOTFIFO/i_Vidya.html
Parameters:
src: Source
len
Returns: VIDYA of source
VAWMA(src, len, startingWeight, volumeDefault)
VAWMA = VWMA and WMA combined. Simply put, this attempts to determine the average price per share over time weighted heavier for recent values. Uses a triangular algorithm to taper off values in the past (same as WMA does).
Parameters:
src: Source
len: Length
startingWeight
volumeDefault: The default value to use when a chart has no volume.
Returns: The VAWMA of the source.
WWMA(src, len)
WWMA Welles Wilder Moving Average
Parameters:
src: Source
len
Returns: The WWMA of the source
ZLEMA(src, len)
ZLEMA Zero Lag Expotential Moving Average
Parameters:
src: Source
len
Returns: The ZLEMA of the source
SmootherType(mode, src, len, fastMA, slowMA, offset, phase, power, startingWeight, volumeDefault, Corrected)
Performs the specified moving average
Parameters:
mode: Name of moving average
src: the source to apply the MA type
len
fastMA: FRAMA fast moving average
slowMA: FRAMA slow moving average
offset: Linear regression offset
phase: Jurik phase
power: Jurik power
startingWeight: VAWMA starting weight
volumeDefault: VAWMA default volume
Corrected
Returns: The MA smoothed source
릴리즈 노트
v2Code 9
릴리즈 노트
v3, 10릴리즈 노트
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파인 라이브러리
진정한 트레이딩뷰 정신에 따라 작성자는 이 파인 코드를 오픈 소스 라이브러리로 공개하여 커뮤니티의 다른 파인 프로그래머들이 재사용할 수 있도록 했습니다. 작성자에게 건배! 이 라이브러리는 개인적으로 또는 다른 오픈 소스 출판물에서 사용할 수 있지만, 출판물에서 이 코드를 재사용하는 것은 하우스 룰의 적용을 받습니다.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.