STD-Adaptive T3 Channel w/ Ehlers Swiss Army Knife Mod. [Loxx]STD-Adaptive T3 Channel w/ Ehlers Swiss Army Knife Mod. is an adaptive T3 indicator using standard deviation adaptivity and Ehlers Swiss Army Knife indicator to adjust the alpha value of the T3 calculation. This helps identify trends and reduce noise. In addition. I've included a Keltner Channel to show reversal/exhaustion zones.
What is the Swiss Army Knife Indicator?
John Ehlers explains the calculation here: www.mesasoftware.com
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Keltnerchannel
FATL, SATL, RFTL, & RSTL Digital Signal Filter Smoother [Loxx]FATL, SATL, RFTL, & RSTL Digital Signal Filter (DSP) Smoother is is a baseline indicator with DSP processed source inputs
What are digital indicators: distinctions from standard tools, types of filters.
To date, dozens of technical analysis indicators have been developed: trend instruments, oscillators, etc. Most of them use the method of averaging historical data, which is considered crude. But there is another group of tools - digital indicators developed on the basis of mathematical methods of spectral analysis. Their formula allows the trader to filter price noise accurately and exclude occasional surges, making the forecast more effective in comparison with conventional indicators. In this review, you will learn about their distinctions, advantages, types of digital indicators and examples of strategies based on them.
Two non-standard strategies based on digital indicators
Basic technical analysis indicators built into most platforms are based on mathematical formulas. These formulas are a reflection of market behavior in past periods. In other words, these indicators are built based on patterns that were discovered as a result of statistical analysis, which allows one to predict further trend movement to some extent. But there is also a group of indicators called digital indicators. They are developed using mathematical analysis and are an algorithmic spectral system called ATCF (Adaptive Trend & Cycles Following). In this article, I will tell you more about the components of this system, describe the differences between digital and regular indicators, and give examples of 2 strategies with indicator templates.
ATCF - Market Spectrum Analysis Method
There is a theory according to which the market is chaotic and unpredictable, i.e. it cannot be accurately analyzed. After all, no one can tell how traders will react to certain news, or whether some large investor will want to play against the market like George Soros did with the Bank of England. But there is another theory: many general market trends are logical, and have a rationale, causes and effects. The economy is undulating, which means it can be described by mathematical methods.
Digital indicators are defined as a group of algorithms for assessing the market situation, which are based exclusively on mathematical methods. They differ from standard indicators by the form of analysis display. They display certain values: price, smoothed price, volumes. Many standard indicators are built on the basis of filtering the minute significant price fluctuations with the help of moving averages and their variations. But we can hardly call the MA a good filter, because digital indicators that use spectral filters make it possible to do a more accurate calculation.
Simply put, digital indicators are technical analysis tools in which spectral filters are used to filter out price noise instead of moving averages.
The display of traditional indicators is lines, areas, and channels. Digital indicators can be displayed both in the form of lines and in digital form (a set of numbers in columns, any data in a text field, etc.). The digital display of the data is more like an additional source of statistics; for trading, a standard visual linear chart view is used.
All digital models belong to the category of spectral analysis of the market situation. In conventional technical indicators, price indications are averaged over a fixed period of time, which gives a rather rough result. The use of spectral analysis allows us to increase trading efficiency due to the fact that digital indicators use a statistical data set of past periods, which is converted into a “frequency” of the market (period of fluctuations).
Fourier theory provides the following spectral ranging of the trend duration:
low frequency range (0-4) - a reflection of a long trend of 2 months or more
medium frequency range (5-40) - the trend lasts 10-60 days, thus it is referred to as a correction
high frequency range (41-130) - price noise that lasts for several days
The ATCF algorithm is built on the basis of spectral analysis and includes a set of indicators created using digital filters. Its consists of indicators and filters:
FATL: Built on the basis of a low-frequency digital trend filter
SATL: Built on the basis of a low-frequency digital trend filter of a different order
RFTL: High frequency trend line
RSTL: Low frequency trend line
Inclucded:
4 DSP filters
Bar coloring
Keltner channels with variety ranges and smoothing functions
Bollinger bands
40 Smoothing filters
33 souce types
Variable channels
LNL Pullback ArrowsBuying the dip has never been easier! LNL Pullback Arrows are here to pinpoint the best possible entries for the trend following setups. With the Pullback Arrows, trader can pick his own approach and risk level thanks to four different types of arrows. The goal of these arrows is to force the traders to scale in & out of trades which is in my opinion crucial when it comes to trend following strategies. These arrows were designed primarily for the daily & weekly time frame (swing trading).
Four Types of Pullback Arrows:
1. Aggro Arrows - Ideal for aggresive approach during parabolic trends. Sometimes trends are so strong that the price barely revisits the daily 8 EMA. This is where the aggro arrows can perfectly pinpoint the aggresive high risk entries. Ideal for halfsize or 1/4 size of the full position. Aiming for quick 1-2 day moves targeting the recent high/low. These arrows could be also named as scalping arrows for the swing traders. A quick In & Out.
2. HalfSize Arrows - Medium risk approach. First arrows to scale in. HalfSize arrows are the first sign that the pullback might be ending, yet there is still some space left for an even deeper pullback. That is the reason why they are called half-size. Ideally taken with half-sized position. When trading the HalfSize Arrows, It is better to have some "spare ammo in the gun" ready to use.
3. FullSize Arrows - Regular risk approach. These arrows represent a zone where the core of the posititon should be taken. The point of validity for the trend is not that far away, meaning the risk can be kept tight. Ideal for scailing the other halfs or quarters of the full position. Also great for more conservative traders or environments with higher volatility.
4. Rare Arrows - Offer the best risk to reward entries during the trend. Rare Arrows should be the "last kick" of the retracement, therefore stops can be positioned really tight. They either trigger the stop immidiately or they provide another juicy leg up or down in the direction of the trend. However, they really do appear rarely.
Simple EMA Cloud:
A simple cloud based on 21 and 55 exponential moving averages. This default length creates a pullback zone that is wide enough for the conservative traders but also give the opportunities to more aggresive traders. Alternatives such as 8 & 21, or 21 & 34 are forming the zone that is too aggresive and usually too thin. Of course, cloud can be fully adjusted or turned off completely. The only role of the cloud is to gauge the trend.
Tips & Tricks:
1.Importance of the Scailing
- As already stated, scailing is crucial to this since there is no way of knowing the exact level at which the price magically bounce every time. It is hard to tell where and which EMA will be respected. How can we know it will be 21 EMA every time? or 34 EMA or 10 EMA or 100 SMA or 50 DMA ... Single MA does not make a trend. This is the reason why scailing is so important. Scailing can make a difference.
2. Nothing is Perfect
- Same as any other study, nothing works 100% perfectly. Sometimes the setup will go right against you and sometimes the price will fade away sideways and breaks off the structure of the trend. This is not a magic certainty tool. This is just another probability tool.
3. Point of Validity & Other Studies
- Even though the pullback arrows can be a stand-alone strategy. It is important to use other indicators that visualize the actual trend. Whether its EMA Cloud or EMAs or DMI Bars or Keltner Channels, there should be something that validates the trend, something that tells the trend is over. (Pullback Arrows are not showing the actual stops!).
Hope it helps.
Adaptive ATR Keltner Channels [Loxx]Adaptive ATR Channels are adaptive Keltner channels. ATR is calculated using a rolling signal-to-noise ratio making this indicator flex more to changes in price volatility than the fixed Keltner Channels.
What is Average True Range (ATR)?
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.1
The true range is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
What are Keltner Channel (ATR)?
Keltner Channels are volatility-based bands that are placed on either side of an asset's price and can aid in determining the direction of a trend.
The Keltner channel uses the average-true range (ATR) or volatility, with breaks above or below the top and bottom barriers signaling a continuation.
Top Trend Backtest (Simple) [Loxx]Simple backtest for Top Trend found here:
What this backtest includes:
-Customization of inputs for Top Trend calculation
-Take profit 1 (TP1), and Stop-loss (SL), calculated using standard RMA-smoothed true range
-Activation of TP1 after entry candle closes
-Long and short signal cross entries
Happy trading!
Top Trend [Loxx]Top Trend is a trend following indicator that signals breakouts and plots dynamic support and resistance levels.
Included:
-Calculation of Top Trend using either Bollinger Bands and Keltner Channels
This is an exact clone of the "TopTrend" for MT4 indicator
Keltner Channel Width Oscillator (KingThies)Definition
The Keltner Channel Width oscillator is a technical analysis indicator derived originally from the same relationship the Bollinger Band Width indicator takes on Bollinger Bands.
Similar to the Bollinger Bands, Kelts measure volatility in relation to price, and factor in various range calculations to create three bands around the price of a given stock or digital asset. The Middle Line is typically a 20 Day Exponential Moving Average while the upper and lower bands highlight price at different range variations around its basis. Keltner Channel Width serve as a way to quantitatively measure the width between the Upper and Lower Bands and identify opportunities for entires and exits, based on the relative range price is experiencing that day.
Calculation
Kelt Channel Width = (Upper Band - Lower Band) / Middle Band
More on Keltner Channels
Keltner channel was first described by a Chicago grain trader called Chester W. Keltner in his 1960 book How to Make Money in Commodities. Though Keltner claimed no ownership of the original idea and simply called it the ten-day moving average trading rule, his name was applied by those who heard of this concept through his books.
Similarly to the Bollinger Bands, Keltner channel is a technical analysis tool based on three parallel lines. In fact, the Keltner indicator consists of a central moving average in addition to channel lines spread above and below it. The central line represents a 10-day simple moving average of what Chester W. Keltner called typical price. The typical price is defined as the average of the high, low and close. The distance between the central line and the upper, or lower line, is equivalent to the simple moving average of the preceding 10 days' trading ranges.
One way to interpret the Keltner Channel would be to consider the price breakouts outside of the channel. A trader would track price movement and consider any close above the upper line as a strong buy signal. Equivalently, any close below the lower line would be considered a strong sell signal. The trader would follow the trend emphasized by the indicator while complementing his analysis with the use of other indicators as well. However, the breakout method only works well when the market moves from a range-bound setting to an established trend. In a trend-less configuration, the Keltner Channel is better used as an overbought/oversold indicator. Thus, as the price breaks out below the lower band, a trader waits for the next close inside the Keltner Channel and considers this price behavior as an oversold situation indicating a potential buy signal. Similarly, as the price breaks out above the upper band, the trader waits for the next close inside the Keltner Channel and considers this price action as an overbought situation indicating a potential sell signal. By waiting for the price to close within the Channel, the trader avoids getting caught in a real upside or downside breakout.
Bollinger Bands + Keltner Channel Refurbished█ Goals
This is an indicator that brings together Bollinger Bands and Keltner's Channels in one thing.
Both are very similar, so I decided to make a merge of the best features I found out there.
Here there is the possibility of choosing one of these two as needed.
In addition, I added the following resources:
1. Pre-Defined intermediate bands with Fibonacci values;
2. Detachment of the bands in which the price was present;
3. Choice of Moving Average:
"Simple", "Exponential", "Regularized Exponential", "Hull", "Arnaud Legoux", "Weighted Moving Average", "Least Squares Moving Average (Linear Regression)", "Volume Weighted Moving Average", "Smoothed Moving Average", "Median", "VWAP");
4. Statistics: bars count within the bands.
█ Concepts
Keltner Channels vs. Bollinger Bands
"These two indicators are quite similar.
Keltner Channels use ATR to calculate the upper and lower bands while Bollinger Bands use standard deviation instead.
The interpretation of the indicators is similar, although since the calculations are different the two indicators may provide slightly different information or trade signals."
(Investopedia)
Bollinger Bands (BB)
"Bollinger Bands (BB) are a widely popular technical analysis instrument created by John Bollinger in the early 1980’s.
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
Typically the Upper and Lower Bands are set to two standard deviations away from the SMA (The Middle Line); however the number of standard deviations can also be adjusted by the trader."
(TradingView)
Keltner Channels (KC)
"The Keltner Channels (KC) indicator is a banded indicator similar to Bollinger Bands and Moving Average Envelopes.
They consist of an Upper Envelope above a Middle Line as well as a Lower Envelope below the Middle Line.
The Middle Line is a moving average of price over a user-defined time period.
Either a simple moving average or an exponential moving average are typically used. The Upper and Lower Envelopes (user defined) are set a range away from the Middle Line.
This can be a multiple of the daily high/low range, or more commonly a multiple of the Average True Range."
(TradingView)
█ Examples
Bollinger Bands with 200 REMA:
Keltner Channel with 200 REMA:
Bollinger Bands with 55 ALMA:
Keltner Channel with 55 ALMA:
Bollinger Bands with 55 Least Squares Moving Average:
█ Thanks
- TradingView (BB, KC, ATR, MA's)
- everget (Regularized Exponential Moving Average)
- TimeFliesBuy ("Triple Bollinger Bands")
- Rashad ("Fibonacci Bollinger Bands")
- Dicargo_Beam ("Is the Bollinger Bands assumption wrong?")
LNL Keltner ExhaustionLNL Keltner Exhaustion resolves the constant issue of Bands vs. EMAs
With the keltner exhaustion wedges, you can easily see the keltner channel extremes witout using the actual bands. That way, you will know whether the price is outside of the keltner channels + you can use other indicators (such as EMAs) on chart without the bands so the chart does not look messy & hard to read.
Two Types of Wedges:
1. Green/Red Wedge - Price action is extended outside the regular band. More of a "profit taking" zone rather than "entry taking" (default set to 3.0 ATR factor).
2. Purple Wedge - Price action is extended outside of the extreme band. Chances are price will revert to mean soon (default set to 4.0 ATR factor).
Works great as a target tool with the squeeze setup or as an overall extension gauge.
Hope it helps.
SSL + Wavetrend (7 indicators) by TradeSmartHello everyone! This script is implementing a strategy that uses 7 indicators: SSL, Wavetrend, SSL Hybrid, Keltner Channel, EMA, Candle Height and ATR. This is the 2nd best strategy that we have tested so far (based on the 100 backtests).
STRATEGY ENTRY RULES
Long entry: go long if SSL Hybrid is blue (between last candle and entry candle) and SSL Channel crosses up (green SSL line is on the top) and Wave Trend prints green dot (candle color turns yellow) and entry Candle Height is not higher than 0.6 and entry candle is inside the Keltner Channel and price target does not hit the 200 EMA.
Short entry: go short if SSL Hybrid is pink (between last candle and entry candle) and SSL Channel crosses down (red SSL line is on the top) and Wave Trend prints red dot (candle color turns blue) and entry Candle Height is not higher than 0.6 and entry candle is inside the Keltner Channel and price target does not hit the 200 EMA.
EXIT STRATEGY
The strategy will exit based on a set ATR value. Take profit and stop loss levels can be changed with risk/reward settings.
CHANGEABLE SETTINGS
Wave Trend: Channel Length, Average Length, Wave Trend Limit High, Wave Trend Limit Low
SSL: Period
SSL Hybrid: SSL1 / Baseline Type, SSL1 / Baseline Length, Base Channel Multiplier
Target Price Limit: can set 6 different limiters for long and short entries
Candle Height Limit: Limit based on, Candle Limit High, Candle Limit Low
Keltner Channel: Limit range long, Limit range short, Length, Multiplier, Source, Use Exponential MA, Bands Style, ATR Length
Exit strategy: ATR Length, ATR Smoothing, Stop Loss Multiplier (risk), Exit Price Multiplier (reward)
Setups: Capital Percentage, Risk Percentage, Allow Long Entries, Allow Short Entries
Date Range: Limit Between Dates, Start Date, End Date
Trading Time: Valid Trading Days
FIRST RELEASE SETTINGS FOR ALGOUSDT 30 M (3/19/2022)
Wave Trend: Channel Length = 11, Average Length = 19, Wave Trend Limit High = 27, Wave Trend Limit Low = -48
SSL: Period = 10
SSL Hybrid: SSL1 / Baseline Type = EMA, SSL1 / Baseline Length = 36, Base Channel Multiplier = 0.21
Target Price Limit: can set 6 different limiters for long and short entries: all false
Candle Height Limit: Limit based on: Candle Body (open/close), Candle Limit High = disabled, Candle Limit Low = enabled, 0.32
Keltner Channel: Limit range long = enabled, Full range, Limit range short = enabled, Full range, Length = 3, Multiplier = 1, Source = close, Use Exponential MA = enabled, Bands Style = Average True Range, ATR Length = 11
Exit strategy: ATR Length = 14, ATR Smoothing = EMA, Stop Loss Multiplier (risk) = 1.9, Exit Price Multiplier (reward) = 2
Setups: Capital Percentage = disabled, Risk Percentage = enabled, 1, Allow Long Entries = enabled, Allow Short Entries = enabled
Date Range: Limit Between Dates = disabled, Start Date, End Date
Trading Time: Valid Trading Days = 1234567
Hope you like this strategy, feel free to check all of our scripts. Thank you for your support!
multicolor Bollinger Bands (BB <-> KC)Concept:
After every low volatile phase comes a high volatile phase and after every high volatile phase comes a low volatile phase.
If the Bollinger bands are smaller then the Keltner channel (colored red), the price action is low in volatility… meaning a breakout (colored green) will happen soon.
If Bollinger band is bigger than the Keltner channel = green
If Bollinger band is smaller than the Keltner channel = red
Displaying the Keltner Channel is optional
If multicolor BB is disabled, BB color = blue (default color)
Customise colors to your liking under settings -> style
-----------------------------------
To get alerts for all coins
1. visit » tradingview.com/crypto-screener
2. set the filter to »
Bollinger Upper Band (20) below Keltner Channels Upper Band (20)
Bollinger Lower Band (20) above Keltner Channels Lower Bands (20)
3. add your own custom filters, like: exchange, marketcap, etc…
4. choose the timeframe you want
5. enable alerts
+ Magic Carpet BandsFun name for an indicator, eh? Well, it is true, I think; they look like magic carpets. They're actually pretty simple actually. They're Keltner Channels smoothed with a moving average. If you go down to the lookback period for the bands and set it to 1, you'll recognize them immediately.
Digging a bit deeper you see there are four magic carpets on the chart. The inner ones are set to a multiplier of 2, and the outer to a multiplier of 4. Each "carpet" is composed of two smoothed upper or lower Keltner Channels bounds, both with an optional offset, one of which is set to 13, and the other to 0 by default; and an optional color fill between these. There is also a color fill between the outer and inner carpets which gives them an interesting 3-dimensional aspect at times. They can look a bit like tunnels by default.
My thinking around the idea of using an offset with the bands is that if we assume these things to provide a dynamic support and resistance, and previous support and resistance maintains status as support and resistance until proven otherwise, then by putting an offset to past data we are creating a more obvious visual indication of that support or resistance in the present. The default offset is set to 13 bars back, so if price found resistance at some point around 13 bars ago, and price is currently revisiting it we assume it is still resistance, and that offset band is there to give us a strong visual aid. Obviously it's not foolproof, but nothing is.
Beyond that most interesting part of the indicator you have a nice selection of moving averages which the bands are calculated off of. By default it's set to my UMA. The bands themselves also have a selection of moving averages for how the keltner channels are smoothed. And a note: because the UMA and RDMA are averages of different length MAs, they can not be adjusted other than via the multiplier that sets the distance from the moving average.
The indicator is multi-timeframe, and the moving average can be colored based on a higher timeframe as well.
I popped in the divergence indicator here too. You can choose from RSI and OBV, and the divergences will be plotted on the chart. Working on finding a way to be able to have the bands/MA set to a higher timeframe while plotting the divergences on the chart timeframe, but don't have an answer to that yet.
Alerts for moving average crosses, band touches, and divergences.
I like this one a lot. Enjoy!
Pictures below.
s3.tradingview.com
One interesting thing about this indicator is that band twists often occur at areas of support or resistance. Simply drawing horizontal lines from previous twisted points can provide places from which you may look for strength or weakness to enter into a trade, or which you might use as targets for taking profits. The vertical lines are just showing the point on the chart when the cross occurred.
s3.tradingview.com
Above is a Jurik MA with a bunch of adjustments made to the bands, and the moving average itself. Everything is super adjustable, so you can play around and have fun with them quite a bit.
s3.tradingview.com
Just a different MA and bands.
s3.tradingview.com
Keltner Channel With User Selectable Moving AvgKeltner Channel with user options to calculate the moving average basis and envelopes from a variety of different moving averages.
The user selects their choice of moving average, and the envelopes automatically adjust. The user may select a MA that reacts faster to volatility or slower/smoother.
Added additional options to color the envelopes or basis based on the current trend and alternate candle colors for envelope touches. The script has a rainbow gradient by default based on RSI.
Options (generally from slower/smoother to faster/more responsive to volatility):
SMMA,
SMA,
Donchian, (Note: Selecting Donchian will just convert this indicator to a regular Donchian Channel)
Tillson T3,
EMA,
VWMA,
WMA,
EHMA,
ALMA,
LSMA,
HMA,
TEMA
Value Added:
Allows Keltner Channel to be calculated from a variety of moving averages other than EMA/SMA, including ones that are well liked by traders such as Tillson T3, ALMA, Hull MA, and TEMA.
Glossary:
The Hull Moving Average ( HMA ), developed by Alan Hull, is an extremely fast and smooth moving average . In fact, the HMA almost eliminates lag altogether and manages to improve smoothing at the same time.
The Exponential Hull Moving Average is similar to the standard Hull MA, but with superior smoothing. The standard Hull Moving Average is derived from the weighted moving average ( WMA ). As other moving average built from weighted moving averages it has a tendency to exaggerate price movement.
Weighted Moving Average: A Weighted Moving Average ( WMA ) is similar to the simple moving average ( SMA ), except the WMA adds significance to more recent data points.
Arnaud Legoux Moving Average: ALMA removes small price fluctuations and enhances the trend by applying a moving average twice, once from left to right, and once from right to left. At the end of this process the phase shift (price lag) commonly associated with moving averages is significantly reduced. Zero-phase digital filtering reduces noise in the signal. Conventional filtering reduces noise in the signal, but adds a delay.
Least Squares: Based on sum of least squares method to find a straight line that best fits data for the selected period. The end point of the line is plotted and the process is repeated on each succeeding period.
Triple EMA (TEMA) : The triple exponential moving average (TEMA) was designed to smooth price fluctuations, thereby making it easier to identify trends without the lag associated with traditional moving averages (MA). It does this by taking multiple exponential moving averages (EMA) of the original EMA and subtracting out some of the lag.
Running (SMoothed) Moving Average: A Modified Moving Average (MMA) (otherwise known as the Running Moving Average (RMA), or SMoothed Moving Average (SMMA)) is an indicator that shows the average value of a security's price over a period of time. It works very similar to the Exponential Moving Average, they are equivalent but for different periods (e.g., the MMA value for a 14-day period will be the same as EMA-value for a 27-days period).
Volume-Weighted Moving Average: The Volume-weighted Moving Average (VWMA) emphasizes volume by weighing prices based on the amount of trading activity in a given period of time. Users can set the length, the source and an offset. Prices with heavy trading activity get more weight than prices with light trading activity.
Tillson T3: The Tillson moving average a.k.a. the Tillson T3 indicator is one of the smoothest moving averages and is both composite and adaptive.
+ Ultimate MAWhat is the "Ultimate MA" exactly, you ask? Simple. It actually takes as its influence the Rex Dog Moving Average (which I have included as an MA in some of my other indicators), an invention by xkavalis that is simply an average of different length moving averages.
It's available for free on his account, so take a look at it.
I've recently become drawn to using fibonacci sequence numbers as lookbacks for moving averages, and they work really well (I'm honestly beginning to think the number doesn't matter).
You can see where this is going. The Ultimate MA is an average of several (eight) moving averages of varying lengths (5 - 144) all of fibonacci numbers. Sounds pretty basic, right? That's not actually the case, however.
If you were to take all these numbers, add them up, then average them by eight you'd get ~46. Now, stick a 46 period moving average on the chart and compare it to this one and see what you get. They track price very differently. Still, this all sort of sounds like I'm copying the RDMA, which isn't a sin in itself but is hardly grounds for releasing a new MA into the wild.
The actual initial problem I wanted to tackle was how to take in to account for the entire range of price action in a candle in a moving average. ohlc4 sort of does this, but it's still just one line that is an average of all these prices, and I thought there might be a better way not claiming that what I came upon is, but I like it).
My solution was to plot two moving averages: one an average of price highs, and the other an average of lows, thus creating a high/low price channel. Perhaps this is not a new thing at all. I don't know. This is just an idea I had that I figured I could implement easily enough.
Originally I had just applied this to a 21 period EMA, but then the idea sort of expanded into what you see here. I kept thinking "is 21 the best?" What about faster or slower? Then I thought about the RDMA and decided on this implimentation.
Further, I take the high and low moving averages and divide them by two in order to get a basis. You can turn all this stuff on or off, though I do like the default settings.
After that I wanted to add bands to it to measure volatility. There is an RDMA version that utilizes ATR bands, but I could never find myself happy with these.
I just wanted something... else. I also, actually made my own version of xkavalis' RDMA bands with some of the extra stuff I included here, but obviously didn't feel comfortable releasing it as an indicator as I hadn't changed it enough significantly in my mind to fairly do so. I eventually settled on Bollinger Bands as an appropriate solution to apply to the situation. I really like them. It took some fiddling because I had to create a standard deviation for both the high and low MAs instead of just one, and then figure out the best combination of moving averages and standard deviations to add and subtract to get the bands right.
Then I decided I wanted to add a few different moving averages to choose from instead of just an EMA even though I think it's the "best." I didn't want to make things too complicated, so I just went with the standards--EMA, SMA, WMA, HMA-- + 1, the ALMA (which gives some adjustability with its offset and sigma).
Also, you can run more than one moving average at a time (try running an HMA with a slower one).
Oh yeah, the bands? You can set them, in a dropdown box, to be based on which ever moving average you want.
Furthermore, this is a multi-timeframe indicator, so if you want to run it on a higher time frame than the one you are trading on, it's great for that.
ALSO, I actually have the basis color setup as multi-timeframe. What this means is that if you are looking at an hourly chart, you can set the color to a 4h (or higher) chart if you want, and if the current candle is above or below the previous close of the basis on that higher timeframe you will know simply by looking at the color of it ((while still being on the hourly chart). It's just a different way of utilizing higher timeframe information, but without the indicator itself plotted as higher timeframe.
I'm nearly finished. Almost last thing is a 233 period moving average. It's plotted as an average of the SMA, EMA, and Kijun-sen.
Lastly, there are alerts for price crossing the inner border of the bands, or the 233 MA.
Below is a zoomed in look at a chart.
Much credit and gratitude to xkavalis for coming up with the idea of an average of moving averages.
Optimized Keltner Channels SL/TP Strategy for BTCThis strategy is optimized for Bitcoin with the Keltner Channel Strategy, which is TradingView's built-in strategy. In the original Keltner Channel Strategy, it was difficult to predict the timing of entry because the Buy and Sell signals floated in the middle of the candle in real time. This strategy is convenient because if the bitcoin price hits the top or bottom of the Keltner Channel and closes the closing price, you can enter Buy or Sell at the next candle start price. In addition, this strategy provides Stop Loss and Take Profit functions to maximize profit.
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Recommended settings are below.
- length: 9
- multiplier: 1
- source: close
- (v) Use EMA
- Bands Style: Average True Range
- ATR Length: 19
- Stop Loss (%): 20
- Take Profit (%) : 20
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- length: 9
- multiplier: 1
- source: close
- (v) Use EMA
- Bands Style: Average True Range
- ATR Length: 18
- Stop Loss (%): 20
- Take Profit (%) : 5
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▶ Usefulness and Originality
- Stop Loss and Take Profit functions are available
- Convenient Buy and Sell entry compared to the original Keltner Channel Strategy
- Optimized for BTCUSD market (maximizing profits)
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이 전략은 TradingView의 Built-in 전략인 Keltner Channel Strategy를 비트코인에 맞게 최적화되었습니다. 기존의 Keltner Channel Strategy는 Buy, Sell 신호가 캔들 중간에 실시간으로 떠서 진입 시점을 예측하기 어려운 불편함이 있었지만 이 전략은 비트코인 가격이 Keltner Channel 상단 혹은 하단을 찍고 종가를 마감하면 그 다음 캔들 시작가에서 Buy 혹은 Sell 진입이 가능하여 편리합니다. 또한, 이 전략은 Keltner Channel을 만나서 캔들을 마감한 가격 (bprice, sprice)을 시각적으로 plot을 제공하여 타점 및 차트를 보기에 편리하며 손절가 및 목표가를 지정한 백테스팅이 가능합니다.
+ ALMA Trend DetectorHi, again. Here I have a nice moving average script designed to get you into trends and keep you in trends until the opportune moment comes to exit. And, as with any indicator, or suite of indicators, designed to get one into trends and keep him/her in a trend, they do not do so well in chop/ranging/mean reversion conditions, though I would say this one is better than most, otherwise I wouldn’t be fitting it into my trading system.
This is a huge improvement, in my opinion, over an indicator I found recently, and like quite a bit by samsmilesam, which you can find here: www.tradingview.com
In this adaptation of his script I changed a bunch of things, but kept the spirit of the indicator true.
This indicator utilizes three different length Arnaud Legoux moving averages, known for being extremely low lag, and incredibly adjustable (though I find the original authors settings excellent).
While he has buy and sell signals triggering regardless of the fast and slow ma’s position to the trending ma, I actually take the trending ma into account. Furthermore, I wouldn’t say I coded in signals indicating buying and selling, but that I coded in signs that answer the question “what kind of trend are we in?” as well as possible ideal trade exits (which couuuuuld also be taken as entries, but aren’t necessarily meant to).
So, the deets on this:
1) 5 period, 20 period, and 70 period ALMAs. Fast, slow and trend. All customizable independent of each other (unlike the sam’s). All three also change color based on their own individual trends.
2) Uptrends are identified when price is closing above the Trend ma, and both Fast and Slow ma’s are above the Trend ma, and vice versa for downtrends. There are in-between points when a trend is not identified, and this is when price closes above or below the Trend ma, but the other two ma’s have not crossed it. Background color is used to identify the trend.
3) Trade exits are based on closing price and Fast and Slow ma’s relative to the Trend ma, once again. To signal exiting an uptrend price must close below both Fast and Slow ma’s and both Fast and Slow ma’s must be above the Trend ma; and vice versa for exiting a down trend. Obviously there may be false signals, but there are fewer signals, and I think it’s a better strategy than most. I prefer to filter out as much noise as possible. There’s little worse in my opinion than an indicator that gives too many false signals, but obviously it’s impossible to remove them all. Some discretion is necessary on the part of the trader.
4) So what does this mean for trade entries? Well, you can certainly enter a trade on a signal for an exit (go long on a short exit signal) if the chart looks good for that. Or you can wait for trend confirmation with the background color, entering on a pullback to the ma’s perhaps. Or you can enter in the “no man’s land” in between trends. If you’ve exited and price continues on trending your best bet would be to wait for a pullback into the ma’s or a s/r level, or look for the next candle that closes beyond the Fast and Slow ma’s. These are just thoughts of mine.
5) Lastly, there are alert conditions set for uptrends, downtrends and both long and short exits!
Enjoy the indicator! I think with some sort of bands or channels for those times when the market is rangebound or in chop, you could really crush it with this.
Optimized Keltner Channels Strategy for BTCThis strategy is optimized for Bitcoin with the Keltner Channel Strategy, which is TradingView's built-in strategy. In the original Keltner Channel Strategy, it was difficult to predict the timing of entry because the Buy and Sell signals floated in the middle of the candle in real time. This strategy is convenient because if the bitcoin price hits the top or bottom of the Keltner Channel and closes the closing price, you can enter Buy or Sell at the next candle start price. In addition, this strategy provides a visual plot of the price (bprice, sprice) at which the candle is closed by hitting Keltner Channel.
▶ Usefulness and Originality
- Convenient Buy and Sell entry compared to the original Keltner Channel Strategy
- Optimized for BTCUSD market (maximizing profits)
___________________________________________
이 전략은 TradingView의 Built-in 전략인 Keltner Channel Strategy를 비트코인에 맞게 최적화되었습니다. 기존의 Keltner Channel Strategy는 Buy, Sell 신호가 캔들 중간에 실시간으로 떠서 진입 시점을 예측하기 어려운 불편함이 있었지만 이 전략은 비트코인 가격이 Keltner Channel 상단 혹은 하단을 찍고 종가를 마감하면 그 다음 캔들 시작가에서 Buy 혹은 Sell 진입이 가능하여 편리합니다. 또한, 이 전략은 Keltner Channel을 만나서 캔들을 마감한 가격 (bprice, sprice)을 시각적으로 plot을 제공하여 타점 및 차트를 보기에 편리합니다.
Keltner Channel [LINKUSDT] 1HThis is a long-only strategy tested on LINK/USDT, 1 hour bar, from Feb 2019. The entry is determined by the breakout of upper Keltnel Channel and when the +DI is higher than 32. Instead of a fixed stop-loss from the original script , I change the exit to the middle band of the Keltnel Channel. 1st profit target will close 20% of the position. 2nd profit target will close 30% of the position. While the remaining 50% position will be closed when the price closes below the middle band of the Keltnel Channel, to take advantage of big trend. All parameters are adjustable. I added another option to enable or disable the ribbon trend filter.
My thoughts: For the same period, LINK appreciated 3000%. So I guess most in and out strategies couldn’t beat a buy and hold strategy during this period. But this doesn’t mean that this strategy is not feasible as each strategy is designed to only take advantage of a certain pattern or behavior of the market. Also, short term strategies allow you to use leverage and hence enable you to use you capital efficiently. Commission is set to 0.1%, taking account of the slippage.
Suggestion: Please perform walk forward analysis before you use real money for trading. Parameters need to be adjusted from time to time depends on your analysis. Can try using ATR for profit targets as over a longer term, the volatility might drop hence a high fixed % profit targets might not be realistic.
Any suggestions are welcome!
Combo Backtest 123 Reversal & Keltner Channel This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The Keltner Channel, a classic indicator
of technical analysis developed by Chester Keltner in 1960.
The indicator is a bit like Bollinger Bands and Envelopes.
WARNING:
- For purpose educate only
- This script to change bars colors.
Keltner Color count [DinhChienFX]Use the synchronization of the 3 lines Basis, Upper, Lower to calculate whether the trend will continue or not.
1. Color the 3 lines Basis, Upper, Lower of the Keltner channel
- If the value of 3 Basis, Upper, and Lower lines in front of a candle increases, fill in green.
- If the value of 3 Basis, Upper, and Lower lines in front of one candle decreases, color in red.
- If 1 of the 3 lines Basis, Upper, and Lower are not in the same direction, paint in gray.
2. Identify the trend.
a. Assign a score for the channel color.
... If blue plus 1 point.
... If red subtracts 1 point.
... If gray gives 0 points.
b. Formula for calculating trend:
Take the total number of past candles. If total> 0 is an Up trend. If total <0 is the downtrend. If total = 0 is sideways.
...Uptrend
...Downtrend
Example: Counting 25 past candles equates to 1 day + 1 hour to determine a trend.
SVIEWThis is momentum based indicator
Input
1. Two EMA
2. Stochastic
Thought process
1. Difference between fast and slow ema has a oscillating nature.
2. Stochastic %k %d crossover gives early signals
3. early entry gives low risk high reward setup
Calculation
1. A= EMA (fast) - EMA (slow)
2. B =Stochastic(%K)-Stochastic(%D)
When A is increasing and B is positive, bar is green
When A is decreasing and B is negative, bar is red
Else, bar is black
Use
This is an early entry signal system. When used with Channel trading system, it gives high probability, low risk high reward setups
Example
When price has breached below -2 Keltner channel, and impulse candle turns green, go long (or sell put options )
29 minutes ago
Release Notes:
This is combination of
1. Ema diff
2. stochastic
3. Keltner channel
4. Bollinger bands
5. bunch of EMAs
Thought process
1. Difference between fast and slow ema has a oscillating nature.
2. Stochastic %k %d crossover gives early signals
3. early entry gives low risk high reward setup
Calculation
1. A= EMA (fast) - EMA (slow)
2. B =Stochastic(%K)-Stochastic(%D)
When A is increasing and B is positive, bar is green
When A is decreasing and B is negative, bar is red
Else, bar is black
Use
This is an early entry signal system. When used with Channel trading system, it gives high probability, low risk high reward setups
Example
When price has breached below -2 Keltner channel, and impulse candle turns green, go long (or sell put options )
Keltner Channel AlertSimple Keltner Indicator with a custom alert.
The alert should ring when any Band has the price crossing.
