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คอฟมันส์ อะแดพทีฟ มูฟวิ่ง เอเวอเรจน์ (KAMA)

Double KAMA + VWMAThis study combines a fast and slow Kaufman Adaptive Moving Averages (KAMA) with a fast and slow Volume-Weighted Moving Average(VWMA). The KAMA is definitely one of our favorite moving averages because it takes into account volatility and filters out false signals during periods of insignificant or horizontal price movement. This results in more patient, less impulsive trading. At its most basic, the KAMA's value remains relatively close in value to the price when volatility is low then lags slightly behind it during highly volatile movements and larger trends. We've plotted two Kaufman's Adaptive Moving Averages: -The first KAMA is the slow KAMA, which we use as a trend filter. It is shown on the graph as the thicker solid line that alternates between green and red. When the trend filter KAMA is bullish, the line turns green. It then turns red when bearish. Users can adjust the lengths of the fast and slow EMA for the KAMA's calculation in the input option menu, but it is important to remember that the number of periods should remain high in comparison to the fast KAMA as this allows it to track long-term price movements and trends. -We then include a fast KAMA which has shorter EMA Lengths to focus in on movements within a smaller timeframe. NOTE: The fast KAMA is only plotted when the trend filter KAMA is generating bullish signals. It is shown as the alternating pink and teal line above the main green line. When the fast KAMA is increasing, its line and the area between it and the slow KAMA are filled teal. When the fast KAMA is falling, its line and the area between the fast and slow KAMA lines are colored pink. This helps with timing exits. Lastly, we've included a fast and slow VWMA to time long entries. These are only plotted when the Trend Filter KAMA is bearish. The fast VWMA is the teal solid line under the trend filter KAMA and the slow VWMA is the pink line. Optimal entries will occur when the fast VWMA crosses above the slow VWMA. When the slow VWMA is greater than the fast VWMA, the area between the two lines is filled red, while the same area is filled teal when the fast VWMA is greater than the slow. I've included entry signals (shown on the screenshot as the lime green background highlights), but this is the basic version of the indicator. If you're interested in taking a look at the full version with alerts and entry + exit signals, feel free to send us a message!
อินดิเคเตอร์ Pine Script™
โดย ProfitProgrammers
1
Moving Average CrossoverIt was planned as an addition to Moving Average Smoothness Benchmark and Profitable Moving Average Crossover , but can be used standalone. Supports 62 types of well-known moving averages and allows full-featured customization. Supported types of averages and filters: AEMA , Adaptive Exponential MA (by Vitali Apirine) AHMA , Ahrens MA (by Richard D. Ahrens) ALMA , Arnaud Legoux MA (by Arnaud Legoux and Dimitris Kouzis-Loukas) ALF , Adaptive Laguerre Filter (by John F. Ehlers) AMA , Adaptive MA (by Vitali Apirine) ARSI , Adaptive RSI BAMA , Bryant Adaptive MA (by Michael R. Bryant) BF2 , Butterworth Filter with 2 poles BF3 , Butterworth Filter with 3 poles DEMA , Double Exponential MA (by Patrick G. Mulloy) DWMA , Double Weighted (Linear) MA EDCF , Ehlers Distance Coefficient Filter (by John F. Ehlers) EDSMA , Ehlers Deviation-Scaled MA (by John F. Ehlers) EHMA , Exponential Hull MA EMA , Exponential MA EVWMA , Elastic Volume Weighted MA (by Christian P. Fries) FRAMA , Fractal Adaptive MA (by John F. Ehlers) GF1 , Gaussian Filter with 1 pole GF2 , Gaussian Filter with 2 poles GF3 , Gaussian Filter with 3 poles GF4 , Gaussian Filter with 4 poles HFSMA , Hampel Filter on Simple Moving Average HFEMA , Hampel Filter on Exponential Moving Average HMA , Hull MA (by Alan Hull) HWMA , Henderson Weighted MA (by Robert Henderson) IDWMA , Inverse Distance Weighted MA IIRF , Infinite Impulse Response Filter (by John F. Ehlers) JAMA , Jurik Adaptive MA (by Mark Jurik) JMA , Jurik MA (by Mark Jurik, ) KAMA , Kaufman Adaptive MA (by Perry J. Kaufman) LF , Laguerre Filter (by John F. Ehlers) LMA , Leo MA (by ProRealCode' user Leo) LSMA , Least Squares MA (Moving Linear Regression) MAMA (by John F. Ehlers) FAMA , Following Adaptive MA (by John F. Ehlers) MD , McGinley Dynamic (by John R. McGinley) MHLMA , Middle-High-Low MA (by Vitali Apirine) MNMA , McNicholl MA (by Dennis McNicholl) NSMA , Moving Average 3.0 on SMA (by Manfred G. Dürschner) NEMA , Moving Average 3.0 on EMA (by Manfred G. Dürschner) NWMA , Moving Average 3.0 on WMA (by Manfred G. Dürschner) NVWMA , Moving Average 3.0 on VWMA (by Manfred G. Dürschner) PEMA , Pentuple Exponential MA (by Bruno Pio) PWMA , Parabolic Weighted MA QMA , Quick MA (by John McCormick) QEMA , Quadruple Exponential MA (by Bruno Pio) REMA , Regularized Exponential MA (by Chris Satchwell) RMA , Running MA (by J. Welles Wilder) RMF , Recursive Median Filter (by John F. Ehlers ) RMTA , Recursive Moving Trend Average (by Dennis Meyers) SHMMA , Sharp Modified MA (by Joe Sharp) SMA , Simple MA SSF2 , Super Smoother Filter with 2 poles (by John F. Ehlers) SSF3 , Super Smoother Filter with 3 poles (by John F. Ehlers) SWMA , Sine Weighted MA TEMA , Triple Exponential MA (by Patrick G. Mulloy) TMA , Triangular MA (generalized by John F. Ehlers) T3 , (by Tim Tillson) VIDYA , Variable Index Dynamic Average (by Tushar S. Chande) VWMA , Volume Weighted MA (by Buff P. Dormeier) WMA , Weighted (Linear) MA ZLEMA , Zero Lag Exponential MA (by John F. Ehlers and Ric Way)
อินดิเคเตอร์ Pine Script™
โดย everget
182
Bryant Adaptive Moving Average@ChartArt got my attention to this idea. This type of moving average was originally developed by Michael R. Bryant (Adaptrade Software newsletter, April 2014). Mr. Bryant suggested a new approach, so called Variable Efficiency Ratio (VER), to obtain adaptive behaviour for the moving average. This approach is based on Perry Kaufman' idea with Efficiency Ratio (ER) which was used by Mr. Kaufman to create KAMA. As result Mr. Bryant got a moving average with adaptive lookback period. This moving average has 3 parameters: Initial lookback Trend Parameter Maximum lookback The 2nd parameter, Trend Parameter can take any positive or negative value and determines whether the lookback length will increase or decrease with increasing ER. Changing Trend Parameter we can obtain KAMA' behaviour To learn more see www.adaptrade.com
อินดิเคเตอร์ Pine Script™
โดย everget
1
Profitable Moving Average CrossoverHi everyone! Introduction A popular use for moving averages is to develop simple trading systems based on moving average crossovers. A trading system using two moving averages would give a buy signal when the shorter (faster) moving average advances above the longer (slower) moving average. A sell signal would be given when the shorter moving average crosses below the longer moving average. The speed of the systems and the number of signals generated will depend on the length of the moving averages. There are many types of averages that are based on different techniques. Each type has its drawbacks and merits. And if we decide to choose a certain type of average for the trading system, then how do we know that our choice is optimal? What is this tool? This tool will help you to choose this type to create the most profitable trading system based on crossovers for the specified periods. It backtests pairs of each type throughout the whole instrument's history and shows Net Profit curves as a result. So, the type of the most profitable crossover system will be at the top of list of labels on the chart. (Click on the price scale, point to "Labels" and switch off "No Overlapping Labels" option). Settings The main settings are periods for each type pair of fast and slow moving averages. Additionally, it allows to customize some multi-parametric moving averages such as JMA, ALMA, McGinley Dynamic, Adaptive Laguerre Filter etc. 1st Period (default: 14 ) 2nd Period (default: 50 ) 1st ALF Median Length (default: 5 ) 2nd ALF Median Length (default: 5 ) 1st ALMA Offset (default: 0.85 ) 1st ALMA Sigma (default: 6 ) 2nd ALMA Offset (default: 0.85 ) 2nd ALMA Sigma (default: 6 ) 1st HF Scaling Factor (default: 3 ) 2nd HF Scaling Factor (default: 3 ) 1st JMA Phase (default: 50 ) 2nd JMA Phase (default: 50 ) 1st MD Constant (default: 0.6 ) 2nd MD Constant (default: 0.6 ) 1st MHLMA Range (default: 10 ) 2nd MHLMA Range (default: 10 ) 1st PWMA Power (default: 2 ) 2nd PWMA Power (default: 2 ) 1st REMA Lambda (default: 0.5 ) 2nd REMA Lambda (default: 0.5 ) 1st RMF Median Length (default: 5 ) 2nd RMF Median Length (default: 5 ) 1st T3 Alpha (default: 0.7 ) 2nd T3 Alpha (default: 0.7 ) MAMA & FAMA Fast Limit (default: 0.5 ) MAMA & FAMA Slow Limit (default: 0.05 ) Supported types of averages and filters (use short titles to match averages on the chart) AHMA , Ahrens MA (by Richard D. Ahrens) ALMA , Arnaud Legoux MA (by Arnaud Legoux and Dimitris Kouzis-Loukas) ALF , Adaptive Laguerre Filter (by John F. Ehlers) ARSI , Adaptive RSI BF2 , Butterworth Filter with 2 poles BF3 , Butterworth Filter with 3 poles DEMA , Double Exponential MA (by Patrick G. Mulloy) DWMA , Double Weighted (Linear) MA EDCF , Ehlers Distance Coefficient Filter (by John F. Ehlers) EHMA , Exponential Hull MA EMA , Exponential MA EVWMA , Elastic Volume Weighted MA (by Christian P. Fries) FRAMA , Fractal Adaptive MA (by John F. Ehlers) GF1 , Gaussian Filter with 1 pole GF2 , Gaussian Filter with 2 poles GF3 , Gaussian Filter with 3 poles GF4 , Gaussian Filter with 4 poles HFSMA , Hampel Filter on Simple Moving Average HFEMA , Hampel Filter on Exponential Moving Average HMA , Hull MA (by Alan Hull) HWMA , Henderson Weighted MA (by Robert Henderson) IDWMA , Inverse Distance Weighted MA IIRF , Infinite Impulse Response Filter (by John F. Ehlers) JMA , Jurik MA (by Mark Jurik, ) LF , Laguerre Filter (by John F. Ehlers) LMA , Leo MA (by ProRealCode' user Leo) LSMA , Least Squares MA (Moving Linear Regression) MAMA & FAMA , (by John F. Ehlers, special case that used as a benchmark) MD , McGinley Dynamic (by John R. McGinley) MHLMA , Middle-High-Low MA (by Vitali Apirine) PWMA , Parabolic Weighted MA REMA , Regularized Exponential MA (by Chris Satchwell) RMA , Running MA (by J. Welles Wilder) RMF , Recursive Median Filter (by John F. Ehlers) RMTA , Recursive Moving Trend Average (by Dennis Meyers) SHMMA , Sharp Modified MA (by Joe Sharp) SMA , Simple MA SSF2 , Super Smoother Filter with 2 poles (by John F. Ehlers) SSF3 , Super Smoother Filter with 3 poles (by John F. Ehlers) SWMA , Sine Weighted MA TEMA , Triple Exponential MA (by Patrick G. Mulloy) TMA , Triangular MA (generalized by John F. Ehlers) T3 , (by Tim Tillson) VIDYA , Variable Index Dynamic Average (by Tushar S. Chande) VWMA , Volume Weighted MA (by Buff P. Dormeier) WMA , Weighted (Linear) MA ZLEMA , Zero Lag Exponential MA (by John F. Ehlers and Ric Way) NOTE : The results may vary on different tickers and timeframes. If you see the preview result it doesn't mean that these crossovers will be profitable on other instruments and timeframes. This is a normal situation because time series and their characteristics differ. I know that because I tested this tool before publishing. NOTE 2 : You can use this tool by yourself and experiment with it, or you can order a study and I will share the spreadsheet that contains results with you. Good luck!
อินดิเคเตอร์ Pine Script™
โดย everget
23
Zerolag KAMA MACDExperimental Zero Lag Adjusted KAMA based MACD. Uses Kaufman's Adaptive Moving Average (KAMA) instead of the standard EMAs to calculate the MACD with an optional application of the zero lag adjustment. Significant differences in momentum changes (zero line crossovers), often earlier signal line crossovers and differences in divergences. Chart displays : Top : Zero lag adjusted KAMA based MACD Middle : Unadjusted KAMA based MACD Bottom : Standard MACD
อินดิเคเตอร์ Pine Script™
โดย rumpypumpydumpy
2
Market Status Moving AverageGet a quick easy view of the current market status. Examples used above are lengths 6 and 15, but you can tweak to your liking. Want to stop sweating the small stuff and see the bigger picture? Try increasing the length to 50, 100 etc Green = Bullish Orange = Consolidation / Flat Red = Bearish -------------------------------------------------------------------- -------------------------------------------------------------------- Check out some of our other recent releases below :
อินดิเคเตอร์ Pine Script™
โดย CryptoProTools
3
MA Study: Different Types and More [NeoButane]A study of moving averages that utilizes different tricks I've learned to optimize them. Included is Bollinger Bands, Guppy (GMMA) and Super Guppy. The method used to make it MtF should be more precise and smoother than regular MtF methods that use the security function. For intraday timeframes, each number represents each hour, with 24 equal to 1 day. For daily, 3 is 3 day, for weekly, 4 is the 4 weekly, etc. If you're on a higher timeframe than the one selected, the length will not change. Log-space is used to make calculations work on many cryptos. The rules for color changing Guppy is changed to make it not as choppy on MAs other than EMA. Note that length does not affect SWMA and VWAP and source does not affect VWAP. A short summary of each moving average can be found here: medium.com List of included MAs: ALMA: Arnaud Legoux Double EMA EMA: Exponential Hull MA KAMA: Kaufman Adaptive Linear Regression Curve LSMA: Least Squares SMA: Simple SMMA/RMA: Smoothed/Running SWMA: Symm. Weighted TMA: Triangular Triple EMA VWMA: Volume Weighted WMA: Weighted ZLEMA: Zero Lag VWAP: Vol Weighted Average Welles Wilder MA
อินดิเคเตอร์ Pine Script™
โดย NeoButane
11
KAMA: Kaufman Adaptive Moving Average x2/LogCalculation begins at the beginning of the bar, eliminating incorrect moving average weighting at the very beginning of the ticker you're watching. This is important for new stocks, futures, altcoins, etc. The inputs for the fast/slow alphas are now normal integers, with the calculation (2 / (y + 1)) for alpha added after input. Comes with two moving averages and a setting for geometric mean/log. Source is adjustable but using the close works best, especially with how this particular MA is calculated in the first place. Besides that, this is mostly the same as other KAMAs on TradingView, but I'd like to say I put a bit more care into this one. It is important to know that the acceptable length for KAMA is within the boundaries of the alpha lengths. For example, the default lengths are 2 and 30 for alpha, so the acceptable length for KAMA is within 2-30. stockcharts.com www.technicalindicators.net
อินดิเคเตอร์ Pine Script™
โดย NeoButane
2
FCI: EMA Cross KAMA+EnvHey there gentleman, I worked pretty hard to compile and manipulate several different scripts to get us a functioning coded version of our strategy. I even managed to get it to where you can edit the 4 the variables in the settings pop-up. It functions properly across multiple candle periods. The candles turn green when the position is long and red when the position is short. Spend some time with it and get comfortable with it. We need to master it for each pair that we want to trade. Best, Adam
กลยุทธ์ Pine Script™
โดย CryptoPalace
5