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Adaptive

Ehlers Mother Of Adaptive Moving Averages [CC]The Mother Of Adaptive Moving Averages was created by John Ehlers (Rocket Science For Traders pgs 182-183) and this is definitely my favorite Ehlers moving average script. This works as a trend indicator and a typical moving average. When the mama is above the fama then the stock is in an uptrend and vice versa. Of course it is also good when the price is above the fama and mama lines. Buy when the indicator line is green and sell when it is red. Let me know if there are other indicator scripts you would like to see me publish or if you want something custom done!
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cheatcountry tarafından
14
Vertical Horizontal Moving Average [AneoPsy & alexgrover] Moving average adapting to the strength of the trend, this is made possible by using the square of the vertical-horizontal filter as a smoothing factor. Alerts are included with two different types of conditions available to the user. Settings Length : Period of the moving average Src : Input data for the indicator Alerts : Types of conditions to be used in the alerts, when set to "VHMA Direction Change" alerts are triggered once the VHMA is either rising or declining, else the alerts are based on the crosses between Src and the VHMA Usage The VHMA can be used as a fast or slow-moving average in a moving average crossover system, or as input for other indicators. VHMA of with length = 25 and sma with length = 200. VHMA with length = 25 used as input for the RSI with length = 14. Details The vertical-horizontal filter is a measure of the strength of the trend and lay in a (0,1) range, to calculate it you just need to divide the rolling range over with the rolling sum of the absolute price changes, squaring the result allow to get lower results with higher values of length . Squared vertical horizontal filter with length = 50, the value is low when the market is ranging and high when trending. To set the alerts go in the alert panel, click on create alert, and select VHMA in "condition", choose between the buy or sell alert. If Src = closing price or another indicator dependant on the closing price select in options "once per bar close", if the indicator using the opening or lagged closing prices values as input select "One per bar" instead. Thanks Thanks to AneoPsy for adding the color change, the idea to use two kinds of conditions for the alert, and for its feedback, you can follow him www.tradingview.com and finally thanks to you for reading and for your support, only one last script left for the month, then we'll start July with some pretty interesting indicators, I hope you'll like them ^^/
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alexgrover tarafından
14
[LunaOwl] 11 kinds of Adaptive MA Model作品: 11種自適應性平滑模型 It integrates eleven kinds of adaptive moving average method. At first, I just wanted to make a ATR. Later, the price series ±N*ATR mult, to form two series. Then use the concept of support/resistance breakthrough to design it, and then two adaptive series formation channels were formed. Take the average of the two series as the signal. When the price crosses the signal, it's judged to be long or short. 整合了十一種能夠自適應性的移動平均模型。起初只是想要做一個基本款ATR指標，後來將價格加減N個ATR倍數，形成兩條序列形成通道，再使用支撐阻力突破的概念去設計它，再形成兩條自適應性的序列形成通道，再取中間值當成信號。當價格與信號交叉，則判斷作多或者作空。 --------------------------* Parameter 設置參數 Resolution: The default is "the same as the variety". Is a named constant for resolution input type of input function. 商品分辨率：預設與品種相同。是input函數的時間周期輸入類型的命名常量。 Smoothing: The default is Recursive Moving Average(RMA). It can choose other methods, the table is as follows. 平滑類型：預設是「遞回平均」，可以選擇其它方法，列表如下。 列表 / The table of moving averages is as follows: //****中英對照表*****##______________________________________ 1. 遞回平均 || Recursive Moving Average 2. 簡單平均 || Simple Moving Average 3. 指數平均 || Exponential Moving Average 4. 加權平均 || Weighted Moving Average 5. 船體平均 || Hull Moving Average 6. 成交量加權 || Volume Weighted Moving Average 7. 對稱加權 || Symmetric Weighted Moving Average 8. 雙重指數 || Double Exponential Moving Average 9. 三重指數 || Triple Exponential Moving Average 10. 高斯分佈 || Arnaud Legoux Moving Average 11. 提爾森T3 || Tillson T3 Moving Average //##_________________________________________________________ Candle Mode: There are three versions, original, two-color and four-color. 燭台模式：預設模式只區分趨勢，可以改成原版蠟燭或四種顏色版本。 Length: The default is 14, usually no need to adjust. 平滑期數：預設值是14，基本上不用理它。 Occurrence: The default is 1. The range is 0~10. The larger the value, the more delayed. If zero will become too sensitive and noise. 滯後性：預設值是1。調整範圍是0~10，數值愈大信號愈延遲，如果值為0，會變得過於敏捷，那將會失去平滑的意義。 N multiple: The default is 0.618, can be set to 1. The range is 0.382~3.000. 倍數N：預設值是0.618，也可以設定1，最低是0.382，最大是3。 --------------------------* 1. Candle Mode can set the original candle, cancel candle trend color changes. However, the background will still be filled. 可以設定顯示原版的蠟燭線，背景與線並不會消失。 2. Four-color version of candles. It shows changes in trends and prices. 四色版本的蠟燭線，可以顯示趨勢與每日收盤價的變化。
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LunaOwl tarafından
17
Ehler's Reflex Indicator ( + MTF & Adaptive )Implementation of Ehler's Reflex Indicator from TASC Feb 2020. Optional MTF and fixed/adaptive length based on one of Ehler's cycle measurements. Optional settings for his recommended 2 bar averaging, can apply the averaging to either/and source ie (close + close ) / 2, the output of the smoothing filter portion of the calculation or the final indicator output. Green/Red : Reflex/Cycle Aqua/Purple : Trend
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rumpypumpydumpy tarafından
6
Adaptive Price Zone Strategy The adaptive price zone (APZ) is a volatility-based technical indicator that helps investors identify possible market turning points, which can be especially useful in a sideways-moving market. It was created by technical analyst Lee Leibfarth in the article “Identify the Turning Point: Trading With An Adaptive Price Zone,” which appeared in the September 2006 issue of the journal Technical Analysis of Stocks and Commodities. This indicator attempts to signal significant price movements by using a set of bands based on short-term, double-smoothed exponential moving averages that lag only slightly behind price changes. It can help short-term investors and day traders profit in volatile markets by signaling price reversal points, which can indicate potentially lucrative times to buy or sell. The APZ can be implemented as part of an automated trading system and can be applied to the charts of all tradeable assets. Green color is long. Red color is short. WARNING: - For purpose educate only - This script to change bars colors.
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HPotter tarafından
13
Adaptive Price Zone Indicator The adaptive price zone (APZ) is a volatility-based technical indicator that helps investors identify possible market turning points, which can be especially useful in a sideways-moving market. It was created by technical analyst Lee Leibfarth in the article “Identify the Turning Point: Trading With An Adaptive Price Zone,” which appeared in the September 2006 issue of the journal Technical Analysis of Stocks and Commodities. This indicator attempts to signal significant price movements by using a set of bands based on short-term, double-smoothed exponential moving averages that lag only slightly behind price changes. It can help short-term investors and day traders profit in volatile markets by signaling price reversal points, which can indicate potentially lucrative times to buy or sell. The APZ can be implemented as part of an automated trading system and can be applied to the charts of all tradeable assets.
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HPotter tarafından
2
Efficient Trend Step ChannelIntroduction The efficient trend-step indicator is a trend indicator that make use of the efficiency ratio in order to adapt to the market trend strength, this indicator originally aimed to remain static during ranging states while fitting the price only when large variations occur. The trend step indicator family unlike most moving averages has a boxy appearance and could therefore not be classified as smooth, this makes it an indicator relatively uninteresting to use as input for other non-trending indicators such as oscillators. Today a channel indicator making use of the efficient trend-step is proposed, the indicator has an upper and a lower extremity who can be used for breakout or support and resistance methodologies, however we will see that the indicator is sometimes able to return accurate support and resistance levels. The Indicator The indicator has the same settings has the efficient trend step indicator, length control the period of the efficiency ratio, fast control the period of the rolling standard deviation used for trending states, slow control the period of the rolling standard deviation used for ranging states, fast should be lower than slow , if both are equal then the indicator is equal to the classical trend step indicator and length does no longer affect the indicator output. Lower values of fast/slow will make the indicator more reactive to small variations thus changing direction more often. The color changes you can see on the indicator are changed depending on the prior direction took by the indicator output, if the indicator where higher than its precedent value, then the color will be blue until the indicator is lower than its precedent value. Those colors help you have an estimate of the current trend direction. Channel Calculation And Role The extremities made from the efficient trend step allow for more advanced trading rules, they can act as stop/target level and can also give a rough estimate of the current market volatility, with wider extremities indicating a more volatile market. The extremities are made directly from the dev element used by the efficient trend-step, the upper extremity is made by summing the efficient trend step with the value of dev when the efficient trend step change, the lower extremity is made the same way but the value is subtracted instead. Is it a weird choice ? It sure is strange to see such approach, the absolute rolling average error between the price and the efficient trend step could have been a logical measure but using dev instead is more efficient and also allow for a more adaptive approach which can benefit the support and resistance methodology, the last reason is because i didn't wanted to "denature" the trend-step signature of the indicator. The figure above represent the measurement used for making the extremities (in green). Since the previously described measure change only when the efficient trend step change, we can conclude that such measure is representative of a relatively large variation, since the efficient trend step aim to only change when a large variations appear. We can see that the upper extremity acted as an accurate resistance in this upper variation of AMD, Here as well, however like other bands indicators it is safer to take into account the current trend direction, a strong uptrend will have less difficulties crossing the upper extremity, therefore it might be better to rely on the support (lower extremity) on an up-trending market (indicator in blue), and on the resistance (upper extremity) on an down-trending market (indicator in orange). The figure above show support and resistances signals, a cross represent a false signal, while green arrows represent correct ones with their respective direction. Conclusion The presented indicator add more possibilities to the interpretation of the efficient trend step, the extremities can act as stop/target level, however this use has to be controlled, and the level should be in accordance to your risk/reward ratio. Showcasing another trend-step indicator was a real pleasure. Thanks for reading :)
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alexgrover tarafından
5
Minkowski Distance Factor Adaptive Period MACDHi, this script comes from the idea that Ricardo Santos' Minkovski Distance Function is transferred to the period as a factor. Minkowski distance is used as a percentage factor with the help of Relative Strength Index function. Minkowski Distance Function Script : And thus an adaptive MACD was created. This script can give much better results in more optimized larger periods. I leave the decision to determine the periods and weights. I used the weights of 9,12,26 and periods created with multiplied by factor. Regards.
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Noldo tarafından
3
Trend WaveHello Traders! You know, I can sill remember the first time I started tinkering with Pinescript. As I had no prior programming experience, I learned by experimenting with other open-source scripts on TradingViews Marketplace. Tearing apart and combining interesting scripts to see what the output would be. @ChrisMoody was a huge source of inspiration for learning, and I wanted to thank him, as well as @TheLark for the concept behind this script. The Trend Wave is based on @ChrisMoody's PPO-PercentileRank-Mkt-Tops-Bottoms , which also happens to be based on @TheLark's TheLark-Laguerre-PPO/ . Within my experimentation, I found that if I isolate the ppoT & ppoB variables and plot them calculated from extremely small decimals, you can get an extremely fast reacting, mirroring trend detector. Within the script, you have the ability to plot the background colors based on trend to make it easier to see where crossovers occured, as well as a Mirror Input to view the mirrored version of the script. -@DayTradingOil
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DrCatherineHalsey tarafından
20
Market Adaptive Stop-LossI realized that the zone changes in the stoploss remained slow, so I couldn't make enough use of the characteristics of technical indicators when opening positions. This pushed me to keep stop-loss under the influence of a dependent variable. This script helped me a lot (everget) : I've redesigned the stop-loss to be affected by intersections. Therefore, this script is also suitable for adaptive moving averages, fractional periods. Script features: 1.You can select calculation methods created by using various technical analysis methods from the scripts' settings: -Moving Average Convergence Divergence ( Macd ) -Stochastic Oscillator ( Stoch ) -Stochastic Relative Strength Index (StochRSI) -Stochastic Money Flow Index (StochMFI ) (More info : ) -Know Sure Thing ( KST ) -OBV ( On Balance Volume ) -SMA ( Simple Moving Average ) -EMA ( Exponential Moving Average ) -FISHERTRANSFORM ( Fisher Transform ) -AWESOMEOSCILLATOR( Awesome Oscillator ) -PSAR ( Parabolic Stop and Reverse - Parabolic SAR ) -HULLMA( Hull Moving Average ) -VWMA ( Volume Weighted Moving Average ) -RMA (Moving Average using in Relative Strength Index calculations.) -COG (Center of Gravity ) -ACC-DIST ( Accumulation / Distribution Index ) 2 - The region is determined according to the above calculation methods and if it is larger or smaller than the previous stop loss level. And if the price in the negative zone is lower than the stoploss, it is the exact signal and is shown with more highlighted colors. And, in the positive zone, where the price is greater than the stoploss, the trade zones are certain. Shown with more highlighted colors. If the zones are correct but stop-loss is not suitable for opening positions: In other words, if the stop-loss is above/under the highest-lowest levels in the positive zone or if the stop loss is located in the lower zone in the negative zone, these zones are shown to be darker and dimmed so that they do not cause false movements. *** SUMMARY : As a result, you can use this script with support and resistances,and trend lines to get good results. I hope it helps in your analyzes. Best regards.
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Noldo tarafından
10
Adaptive Pivot (HLC3)SUMMARY: Standard Pivot (HLC3) with ATR leeway added to make it adaptive to market volatility. DESCRIPTION: Adaptive Pivot is an indicator utilizing the simplicity of HLC3 Pivots as a turning point (and sometimes a trend indicator) while addressing it's fixed and inflexible nature. Because the indicator is just a single line in the chart, the price may go near it but never touch it. Or it can go pass through it and never retest it again. In an attempt to lessen these from occurring, we can combine pivots with average true range (ATR). This is the specific formula I applied in this indicator: >Upper Pivot = HLC3 + ATR >Lower Pivot = HLC3 - ATR This creates a kind of a range or cloud around the Pivot, making it possibly a more accurate indicator for market turning points. ADJUSTABLE PARAMETERS: The usual ATR parameters are included in this indicator: >ATR_Length = input(14, title="ATR Length", minval=1) >ATR_Smoothing = input(title="ATR Smoothing", defval="RMA", options="RMA", "SMA", "EMA", "WMA") Added to the usual ones is this: >ATR_Multiplier = input(1, title="ATR Multiplier", minval=0.1) which modifies the extent of the ATR (similar to Chandelier Exit) as it is added/subtracted from the pivot values. Pivot’s timeframe is also adjustable: >Pivot_Timeframe = input("3M", title='Pivot Resolution') Note: I did not lock the type to input.resolution to allow for more possible timeframes. OTHER PARAMETERS Indicator color will change to green when the open is above the HLC3 Pivot and change to red when the reverse is true.
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reimadara tarafından
1
Price-Line Channel - A Friendly Support And Resistance IndicatorIntroduction Lines are the most widely used figures in technical analysis, this is due to the linear trends that some securities posses (daily log SP500 for example), support and resistances are also responsible for the uses of lines, basically linear support and resistances are made with the assumption that the line connecting two local maximas or minimas will help the user detect a new local maxima or minima when the price will cross the line. Technical indicators attempting to output lines have always been a concern in technical analysis, the mostly know certainly being the linear regression, however any linear models would fit in this category. In general those indicators always reevaluate their outputs values (repainting), others non repainting indicators returning lines are sometimes to impractical to set-up. This is what has encouraged me to make a simpler indicator based on the framework used in the recursive bands indicator that i published. The proposed indicator aim to be extremely flexible and easy to use while returning linear support and resistances, an option that allow readjustment is also introduced, thus allowing for a "smarter" indicator. The Indicator The indicator return two extremities, the upper one aim to detect resistance points while the lower one aim to detect support points. The length setting control the steepness of the line, with higher values of length involving a lower slope, this make the indicator less reactive and interact with the price less often. The name "price-line" comes from the fact that the channel is dependent on its own interaction with the price, therefore a breakout methodology can also be used, where price is up-trending when crossing with the upper extremity and down trending when crossing with the lower one. Readjusted Option The line steepness can be readjusted based on the market volatility, it make more sense for the line to be more steep when the market is more volatile, thus making it converge faster toward the price, this of course is done at the cost of some linearity. This is achieved by checking the "readjustment" option. The effects can be shown on BTCUSD, below the indicator without the readjusted option : when the "readjustment" option is checked we have the following results : The volatile down movement on BTCUSd make the upper extremity converge faster toward the price, this option can be great for volatile markets. Conclusion The recursive bands indicator prove to be an excellent framework that allow for the creation of lots of indicators, the proposed indicator is extremely efficient and provide an easy solution for returning linear support and resistances without much drawbacks, the readjusted option allow the indicator to adapt to the market volatility at the cost of linearity. The performance of the indicator is relative to the motion of the price, however the indicator show signs of returning accurate support and resistances points. I hope the indicator find its use in the community. Thanks for reading ! Note Respect the house rules, always request permission before publishing open source code. This is an original work, requesting permission is the least you can do.
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alexgrover tarafından
21
EQma - Adaptive Smoothing Based On Optimal Markets DetectionIntroduction "You don’t put sunscreen when there is no sun, you don’t use an umbrella when there is no rain, you don’t use a kite when there is no wind, so why would you use a trend following strategy when there is no trend ?" This is how i start my 4th paper "A New Technical Indicator For Optimal Markets Detection" where i present two new technical indicators. We talked about the first one, running equity, which aim to detect the best moment to enter trades, based on this new metric i made an adaptive moving average. You can see the full paper here figshare.com The Indicator The moving average is based on exponential averaging and use a smoothing variable alpha based on the running equity metric, in order to calculate alpha the running equity is divided by the optimal equity which show the best returns possible for the conditions used. Basically the indicator work as follow : When the running equity is close to the optimal equity it means that the price need no/little filtering since it does not contain information that need to be filtered, therefore alpha is high, however when the running equity is far from the optimal equity this mean that the price posses malign information that need to be removed. This is why the indicator will be closer to the price when length is high : See the full paper for an explanation on how this work. I added various options for the indicator, one will reduce the lag by squaring alpha, thus giving for length = 14 : The efficient option will make use of recursion to provide a more efficient indicator : In green the efficient version, note how this option can allow a better fit with the price. Conclusion This is an indicator but at its core its rather a framework, if you have read the paper you'll see that the conditions are just 1 and -1 that changes with time, basically its like making a strategy with : Condition = if buy then 1 else if sell then -1 else Precedent value of condition. So those two indicators allow to give useful and usable information about your strategy. I hope it can be of use for anyone here, if so don't hesitate to send me what you made using the proposed indicator (and with all my indicators in general). If you are writing a paper and you think this indicator could fit in your work then let me know so i can be aware of it :) Thanks for reading ! Acknowledgement My papers are quite ridiculous but they still manage to get some views, some researchers don't even reach those number in so little time which is quite unfortunate but also really motivating for me, so thanks to those who take time to read them and give me some feedback :)
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alexgrover tarafından
14
Kaufman Adaptive Least Squares Moving AverageIntroduction It is possible to use a wide variety of filters for the estimation of a least squares moving average, one of the them being the Kaufman adaptive moving average (KAMA) which adapt to the market trend strength, by using KAMA in an lsma we therefore allow for an adaptive low lag filter which might provide a smarter way to remove noise while preserving reactivity. The Indicator The lsma aim to minimize the sum of the squared residuals, paired with KAMA we obtain a great adaptive solution for smoothing while conserving reactivity. Length control the period of the efficiency ratio used in KAMA, higher values of length allow for overall smoother results. The pre-filtering option allow for even smoother results by using KAMA as input instead of the raw price. The proposed indicator without pre-filtering in green, a simple moving average in orange, and a lsma with all of them length = 200. The proposed filter allow for fast and precise crosses with the moving average while eliminating major whipsaws. Same setup with the pre-filtering option, the result are overall smoother. Conclusion The provided code allow for the implementation of any filter instead of KAMA, try using your own filters. Thanks for reading :)
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alexgrover tarafından
16
Kaufman Adaptive Correlation OscillatorIntroduction The correlation oscillator is a technical indicator that measure the linear relationship between the market closing price and a simple increasing line, the indicator is in a (-1,1) range and rise when price is up-trending and fall when price is down-trending. Another characteristic of the indicator is its inherent smoothing which provide a noise free (to some extent) oscillator. Such indicator use simple moving averages as well as estimates of the standard deviation for its calculation, but we can easily make it adaptive, this is why i propose this new technical indicator that create an adaptive correlation oscillator based on the Kaufman adaptive moving average. The Indicator The length parameter control the period window of the moving average, larger periods return smoother results while having a low kurtosis, which mean that values will remain around 1 or -1 a longer period of time. Pre-filtering apply a Kaufman adaptive moving average to the input, which allow for a smoother output. No pre-filtering in orange, pre-filtering in yellow, period = 100 for both oscillators. If you are not aware of the Kaufman adaptive moving average, such moving average return more reactive results when price is trending and smoother results when price is ranging, this also apply for the proposed indicator. Conclusion Classical correlation coefficients could use this approach, therefore the linear relationships between any variables could be measured. The fact that the indicator is adaptive add a certain potential, however such combination make the indicator have the drawback of kama + the correlation oscillator, which might appear at certain points. Thanks for reading !
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alexgrover tarafından
16
Powered Kaufman Adaptive Moving AverageIntroduction The ability the Kaufman adaptive moving average (KAMA) has to be flat during ranging markets and close to the price during trending markets is what make this moving average one of the most useful in technical analysis. KAMA is calculated by using exponential averaging using the efficiency ratio (ER) as smoothing variable where 1 > ER > 0 . An increasing efficiency ratio indicate a trending market. Based on one of my latest indicator (see Kaufman Adaptive Bands) i propose this modified KAMA that allow to emphasis the abilities of KAMA by powering the efficiency ratio. I also added a new option that allow for even more adaptivity. The Indicator The indicator is a simple KAMA of period length that use a powered ER with exponent factor . When factor = 1 the indicator is a simple KAMA, however when factor > 1 there can be more emphasis on the flattening effect of KAMA. You can also restrain this effect by using 1 > factor > 0 Note that when the exponent is lower than 1 and greater than 0 you are basically applying a nth square root to the value, for example pow(2,0.5) = sqrt(2) because 1/0.5 = 2, in our case : pow(ER,factor > 1) < ER and pow(ER,1 > factor > 0) > ER Self Powered P-KAMA When the self powered option is checked you are basically powering ER with the reciprocal of ER as exponent, however factor does no longer change anything. This can give interesting results since the exponent depend on the market trend strength. In orange the self powered KAMA of period length = 50 and in blue a basic powered KAMA with a factor of 3 and a period of length = 50. Conclusion Applying basic math to indicators is always fun and easy to do, if you have adaptive moving averages using exponential averaging try powering your smoothing variable in order to see interesting results. I hope you like this indicator. Thanks for reading !
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alexgrover tarafından
31
Kaufman Adaptive BandsIntroduction Bands are quite efficient in technical analysis, they can provide support and resistance levels, provide breakouts points, trailing stop loss/take profits positions and can show the current market volatility to the user. Most of the time bands are made from a central tendency estimator like a moving average plus/minus a volatility indicator. Therefore bands can be made out of pretty much everything thus allowing for any kind of flavors. So i propose a band indicator made from a Kaufman adaptive moving average using an estimate of the standard deviation. Construction The Kaufman moving average is an exponential averager using the efficiency ratio as smoothing variable, length control the period of kama and in order to provide more smoothness a power parameter has been introduced, higher values of power will return smoother results. The volatility indicator is made from a biased estimation of the standard deviation by using the square root of the mean of the square minus the square of the mean method, except that we use kama instead of a mean. The bands are made by adding/subtracting this volatility indicator with kama. How To Use The ability of the indicator to adapt to the current market state is what makes him a great tool for avoiding major exposition during ranging market, therefore the indicator will have a greater motion during trending market, or more simply the bands will move during trending markets while staying "flat" during ranging ones. Therefore the indicator might be more suited to breakouts, even if some cases will return what where turning points, this is particularly true during ranging markets. Of course the efficiency ratio is not an "unbiased" trend metric indicator, it can consider high volatility markets as trending markets. Its one of his downsides. High values of power will create smoother bands. When using a low power parameter use an higher mult. In general using a low power value will make the bands move more freely as well as making them closer to each others. Conclusion At least the indicator is really nice to the eyes when using high power values, its ability to adapt to the market is a great addition to other more classical bands indicators, i also introduced a volatility estimator based on kama, some might have used the following estimation : kama(abs(price - kama)) which would have created a slower result. A trailing stop might be made from it if i see request about such addition. If you are curious here are some more images of the indicator performing on different markets. Thanks for reading !
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alexgrover tarafından
17