Squeeze Momentum Indicator [LazyBear] added Alerting + webhookA modified version of Squeeze Momentum Indicator visualizing on Price Chart.
author: @LazyBear, modified by @KivancOzbilgic, and by @dgtrd
I took in all of the information as the script below is based on the V2 Script that @LazyBear posted and then added Alerting based on the math and the conditions that @dgtrd added.
Per the description here:
The Squeeze Indicator measures the relationship between Bollinger Bands and Keltner's Channels to help identify consolidations and signal when prices are likely to break out (whether up or down).
The Squeeze Indicator finds sections of the Bollinger Bands which fall inside the Keltner's Channels, and in this case, the market is said to be in a squeeze (indicator turns off, displayed with grey diamond shapes in this study).
When the volatility increases, so does the distance between the bands. Conversely, when the volatility declines, the distance also decreases, and in such cases, the squeeze is said to be released (indicator turns on, displayed with triangle up or triangle down shapes)
Taking the above information and what was in the script was able to base the alert conditions:
So when the condition:
Squeeze On or No Squeeze = In Squeeze
Squeeze Off = Squeeze Release Long or Squeeze Release Long based off conditions.
There are 2 separate alert Types.
1. App, Pop-up, eMail, play sound and Send email to SMS
2. It Is dedicated to Webhook for your various applications.
Alerting Options
i.imgur.com
App Notification
i.imgur.com
i.imgur.com
Webhook test into Discord
i.imgur.com
Keltner Channels (KC)
One-Sided Gaussian Filter w/ Channels [Loxx]One-Sided Gaussian Filter w/ Channels is a Gaussian Moving Average that is calculated using a Fibonacci weighting function. Keltner channels have been added to show zones of exhaustion. A better name would be "Half Gaussian bell weighted" or "Half normal distribution weighted" indicator, since the weights for calculation of the average (similar to linear weighted average) are taken from a normal distribution curve like function--but only the half of the curve is used for calculation.
Information of the Gaussian distribution can be found here : en.wikipedia.org and once you take a look at the standard normal distribution curve, it will be much clearer what is exactly done in this indicator.
After the Gaussian Filter is applied to the source input, an Ehlers' 2-Pole Super Smoother is applied to reduce noise without significant lag.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
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
4EMA+KC+BB+DC by MontyI combined these scripts for my friend.
This script contains some imported work from @PatekCharts and I added the KC channels.
It's not that difficult.
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 [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
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.
Hull Keltner ChannelThis script is a Keltner Channel that uses a Hull Moving Average as source, instead of the 20-period EMA.
A hull band improves on lag and smoothness to Simple and Exponential Moving Averages.
And ATR based envelop is generated from this improved MA to form the Keltner Channel.
Hull on EHMA source with 180 periods loopback, coupled with a 200 period loopback for the Keltner Channel and 2 and 6 standard deviations, are my fav settings on Bitcoin, but feel free to try new settings.
Use it as you would use a normal Keltner Channel or Bollinger Bands.
[kai]Keltner&BolingerIt is an indicator that simultaneously displays the Bollinger Bands (BB) and Keltner Channel (KC) calculated for the log scale.
* If you need the normal scale version, please turn off the log mode in the settings.
I think the usage is the same as normal BB and KC.
From here, it ’s an original way of thinking.
I thought about countermeasures for the phenomenon that the BB contracts (squeezes) and breaks, but for some reason it suddenly reverses and breaks greatly in the opposite direction or ends in misfire.
The main part of this Inge is KC, and I think that the range within KC is the range.
Considering that the bar broke above and below the range of KC and broke, the trend market started.
BB fits in KC and judges that the trend is game over
If it is within KC, it is contrarian at the upper and lower limits of KC.
If it breaks, Trend following
Profit if BB fits in KC
I'm thinking about how to use it
ログスケール用にログ計算したボリンジャーバンド（BB）とケルトナーチャンネル（KC）を同時に表示するインジケーターです
※通常スケール版が必要な時は設定のlog modeをOFFにしてください
使い方は普通のBBとKCとおなじで使用方法で良いと思います
ここからはオリジナルな使い方の考え方です
BBが収縮（スクイーズ）してブレイクしたのに何故か突然反転して反対の方に大きくブレイクしたり、不発に終わったりする現象の対策を考えました
このインジのメインはKCでKCの範囲内はレンジと考えます
KCの範囲外にバーが上抜け、下抜けして、ブレイクしたと考え、トレンド相場スタートとします
BBがKCの中に納まってトレンド終了と判定します
KC内の場合はKCの上限、下限で逆張り
ブレイクした場合は順張り
BBがKCの中に納まったら利確
という感じの使い方を考えています
[TTI] ATR channelsHISTORY AND CREDITS
Used by John Carter in his indicator’s toolbox. The ATR channels or the Keltner Channels represent the railroads or the natural movement of stocks.
WHAT IT DOES
Movements between the the The first multiplier lines (white) represent standard movement for the timeframe you are trading. Movements between the second multiplier (green/red lines) represent a 2stdv move of the stock in a single direction. Once a stock starts reaching the 3rd multiplier lines there’s an exponential chance that it will revert to the mean (cyan line)
Additionally, we have added the Institutional lines. These are thought in a Small Account Mastery class 2019 by John Carter, as the levels heavily watched by institutions. The default settings represent what John is teaching but they can be further customised.
HOW TO USE IT
ATRs channels or Keltner Channels can be great source for target or stop losses and can be used as a indicator for confluence with other technical tools like the Fibonacci lines.
Stochastic + Keltner Channels for ScalpingSimple arrow indicator, indicating the direction go the next slight movement. This indicator will work on any time frame or market.
How does this indicator work?
It will use Stochastic and Keltner Channels to detect potential reversals depending on the frequency you choose in the indicator's settings. The higher the frequency, the fewer candles will be used in the calculation.
When to use this indicator?
It will work better in higher time frames for low volatility indicators. You can mix with other indicators like RSI or ADX. This way, you will be able to check if the time selected frame has enough volatility to move the price enough to cover the spreads and fees of your broker.
When to exit the trade after the signal from this indicator?
A good target would be for 1x ATR value and stop-loss 2x the ATR value. Doing trailing stop will reduce your risk and secure some profits, but make sure to use values for possible fakeouts
Can this indicator be used alone as the main source of entry signal for the trades?
You can use it alone, but I recommend mixing with other trend-based indicators, like Moving Averages, so you get the best results. Since it's for scalping purposes, small moments, and reversals, it doesn't have the trend filter, but it can work trading in favor of a significant trend as well
this is a better version of my other script Scalping Arrows
Keltner Channels BandsKeltner Channel Bands
Great indicator for mean reversion strategies.
Alerts you can set:
Crossover EMA
Crossunder EMA
Crossover upper band
Crossunder upper band
Crossover lower band
Crossunder lower band
Have fun!
K's Volatility BandsVolatility bands come in all shapes and forms contrary to what is believed. Bollinger bands remain the principal indicator in the volatility bands family. K's Volatility bands is an attempt at optimizing the original bands. Below is the method of calculation:
* We must first start by calculating a rolling measure based on the average between the highest high and the lowest low in the last specified lookback window. This will give us a type of moving average that tracks the market price. The specificity here is that when the market does not make higher highs nor lower lows, the line will be flat. A flat line can also be thought of as a magnet of the price as the ranging property could hint to a further sideways movement.
* The K’s volatility bands assume the worst with volatility and thus will take the maximum volatility for a given lookback period. Unlike the Bollinger bands which will take the latest volatility calculation every single step of time, K’s volatility bands will suppose that we must be protected by the maximum of volatility for that period which will give us from time to time stable support and resistance levels.
Therefore, the difference between the Bollinger bands and K's volatility bands are as follows:
* Bollinger Bands' formula calculates a simple moving average on the closing prices while K's volatility bands' formula calculates the average of the highest highs and the lowest lows.
* Bollinger Bands' formula calculates a simple standard deviation on the closing prices while K's volatility bands' formula calculates the highest standard deviation for the lookback period.
Applying the bands is similar to applying any other volatility bands. We can list the typical strategies below:
* The range play strategy : This is the usual reversal strategy where we buy whenever the price hits the lower band and sell short whenever it hits the upper band.
* The band re-entry strategy : This strategy awaits the confirmation that the price has recognized the band and has shaped a reaction around it and has reintegrated the whole envelope. It may be slightly lagging in nature but it may filter out bad trades.
* Following the trend strategy : This is a controversial strategy that is the opposite of the first one. It assumes that whenever the upper band is surpassed, a buy signal is generated and whenever the lower band is broken, a sell signal is generated.
* Combination with other indicators : The bands can be combined with other technical indicators such as the RSI in order to have more confirmation. This is however no guarantee that the signals will improve in quality.
* Specific strategy on K’s volatility bands : This one is similar to the first range play strategy but it adds the extra filter where the trade has a higher conviction if the median line is flat. The reason for this is that a flat line means that no higher highs nor lower lows have been made and therefore, we may be in a sideways market which is a fertile ground for mean-reversion strategies.
Bollinger bands and Keltner bands
█ OVERVIEW
This is a Bollinger band Script, with Keltner Channel Bands and for scalping.
█ CONCEPTS
1 — Bollinger Bands, The Bollinger band component is make out from two part, the standard component represented by a white cloud.
This is the 2nd deviation and 3rd deviation filled.
The second part linear weight
This is the 2nd deviation, and is filled from the 3rd deviation from the standard bands. This give the effect of cutting in and out to proved a support and resistance cloud.
2 — Keltner bands, this is the normal calculation, nothing special, by default this is off and can be turned back on in styles.
3 Deviations with ALMA as the Basis
3 — Non-traditional basis
Like with you can change the base moving average
but to a lesser extent.
option are:
sma = Simple Moving Average
ema = Exponential Moving Average
wma = Weighted Moving Average
vwma = Volume Weighted Moving Average
rma = Running Moving Average
alma = Arnaud Legoux Moving Average
hma = Hull Moving Average
█ OTHER SECTIONS
• LIMITATIONS: again this is base on moving average so there is a lag factor, the cloud do not work without volume so if the indicator can not pull volume data you are left with the standard bands.
• NOTE this is a trimmed version of still functions the same.
• THANKS: rumpypumpydumpy for the inspiration
Keltner Center Of Gravity Channel ( KeltCOG )I have the ambition to create a ‘landscape’ which enables the user to see the ‘mood’ of the market about the price of an instrument, simply by looking where the candles go. Prices are a simple phenomenon , they go up or down or stay the same. This is represented quite well for the short term by a candle. I recommend to study candle patterns. Prices not only fluctuate but also trend up, down or go sideways. The user should analyze this by determining the COG (Center Of Gravity) and the ‘normal’ current range by using the historical data in a lookback period.
As a COG the center line of a Donchian Channel is often used. I.m.o. a COG should be a zone, in this channel I use the gray zone of my Donchian Fibonacci Channel, The ‘normal’ range is a multiple of Average True Range, as used in a Keltner Channel. Combining the two can give a cumbersome result, as one can see in my Keltner Fibonacci Channel. In this KeltCOG channel I solved this by not using all Fibonacci levels and by making the Keltner lines strictly parallel to the nearest COG line. To do this, I use the fact that the COG lines have horizontal stretches, there I make the Keltner lines horizontal too. Only where the COG lines change value, the Keltner lines are recalculated. This way the channel gets a very regular shape with three clear zones.
Interpretation of a chart by using the KeltCOG channel.
Overbought: If the candles go higher then the blue zone, the market is hyper enthusiast, creating an overbought situation. This is often followed by a reversion to the COG.
Uptrend: If the candles form in the blue zone, the market is enthusiast and willing to pay more.
Hopeful: If the candles form in or near the upper uncolored zone, the market is hopeful and is thinking about paying more. Sometimes prices go a little up.
Content: If the candles form in the gray zone, which represents COG, the market is happy with the current prices, so these move sideways
Disappointed: If the candles form in or near the lower uncolored zone, the market is disappointed and contemplates paying less, sometimes prices go a little down.
Downtrend: If the candles form in red zone, the market doesn’t like the instrument at all, rejects the current price and is only prepared to pay less.
Oversold: If the candles form below the red zone, the market overdoes its disgust, creating an oversold situation, often followed by a reversion to the COG.
HPH's SuperKeltnerThis indicator combines the Supertrend (to determine the main trend direction) with two Keltner channels (used for add and take profit signals) to construct a trend trading system.
These are the available settings:
General
UseTrendChange ➞ toggle trend change alerts and labels
UseAdds ➞ toggle add to position alerts and labels
UseTakeProfits ➞ toggle take profit alerts and labels
PrematureAdds ➞ toggle adding to position as soon as the add channels are left (default is false, so the add signal will only fire once the channels are re-entered)
PrematureTakeProfits ➞ toggle taking profit as soon as the tp channels are left (default is false, so the tp signal will only fire once the channels are re-entered)
Visualization
Show Add Keltner ➞ toggle display of the channels used for adding to the position
Show TP Keltner ➞ toggle display of the channels used for taking profit
Show SuperTrend ➞ toggle display of the Supertrend
Keltner
Standard Keltner channels settings except for the fact that there are two different multipliers. The Keltner TP Multiplier should generally be bigger than the Keltner Add Multiplier , as the channels are hit differently in trending markets. I recommend you to use the visualization settings to show the channels and adjust the settings to your liking.
Supertrend
Standard Supertrend settings, nothing to add here.
Alerts
Use the alert messages to customize what alert text the indicator will send. This makes it possible to use the script to automate trading bots.
By default, the alerts are sent after the candle has closed. This ensures that no repainting is happening. If you like the risk, you can toggle the corresponding WaitFor Confirmation if you wish to receive the signals earlier (max. once per bar).
Enjoy!
Williams Vix Fix BB + RVI + LinReg & Squeeze (Keltner) BBW + %BLegend:
Entery signal: When line color turns to lime (lighter green) after a blue dot appears
Exit signal: When line color turns to red (darker red) after a red dot appears
Note: it is more affective as an entry signal (Bottom is stronger)
- When line touches or crosses red band it is Top signal (Williams Vix Fix)
- When line touches or crosses blue band it is Bottom signal (Williams Vix Fix)
- Red dot at the top of indicator is a Top signal (Relative Volatility Index)
- Blue dot at the top of indicator is a Bottom signal (Relative Volatility Index)
- Gray dot at the bottom of indicator is a Keltner Squeeze signal (filtered by either BBW or %B)
- Silver dot at the bottom of indicator is a weaker Keltner Squeeze signal (Doesn't meet either BBW or %B filter)
- Purple is a 'Half Squeeze' only 1 Bollinger Band crossed the Keltner Channel
This is an attempt to make use of the main features of all 6 of these Volatility tools:
- Williams Vix Fix + Bollinger Bands
- Relative Volatility Index (RVI)
- Linear Regression (detects Vix Fix starts to rise or fall to a certain degree in order to help validate bottom/top)
Note : There is also added precision on Linear Regression entry by dividing WVF by square roots of basis.
- The crossing of Keltner Channel by the Bollinger Bands (Squeeze)
Conditions to Help Filter Keltner Squeeze:
- When the Bollinger Bands Width (BBW) value is lower than the lowest value within a period plus a margin of error (percentage)
- When the %B value goes up or down by the impulse value (threshold value in setting) detailed in LazyBears indicator. (www.tradingview.com)
If it meets one of these 2 filters and there is a Keltner Channel Squeeze than gray color or else if the squeeze doesn’t meet one of the 2 filters than silver color (weaker Squeeze).
The goal is to find the best tool to find bottoms and top relative to volatility and filter squeeze.
Note: You can also change the threshold for RVI top and bottom.
And this work builds on my last indicators:
- Williams Vix Fix + BB & RVI (Top/Bottom) & Squeeze ()
- Williams Vix Fix BB + RVI & Squeeze (Keltner) filtered BBW + %B ()
If you have ideas on this work or have ideas on potential combinations please message me, I always want to learn or get perspective on how it can be improved.
Sharing is how we get better (Parameter tuning, ideas, discussion)
I don’t reinvent the wheel, just trying to make the wheel better.
Multiband Oscillator - Zigzag versionJust variation of Multi Band oscillator present here: Multi-Band-Channel-Oversold-Overbought-Oscillator
Changes are:
Instead of regular moving average, here I am using Zigzag Moving average. This is calculated in similar to as explained in: Zigzag-Cloud
Instead of ATR, using AZR (Average Zigzag Range) - Average-Zigzag-Range-AZR
Rest of the logic remains same.
Number of bands used 100 - which means, calculate 100 Bollinger bands with Std Dev Multiplier starting from 0.1 and with step 0.1 for the next one.
Which divides price ranges into 200 equal parts. Calculate what is the current range and plot them.
Overbought - Oversold levels are dynamics. They are dependent on the max and min state price has reached in last 80 days. Offset and factor can be used to adjust overbought oversold levels.
Keltner Worm ForecastBeta V0.1.0
This Keltner Channel Worm gives 6 different KCs at max, and allows you to set a multiplier for the offset and worm settings (exponential).
The idea behind this script is that the overall brightness of the Keltner Channel will indicate the strength of the forecast. If the candles are shrouded by darkness, a correction is due.
Enjoy and let me know if you have any suggestions for improvements down below!
<3 Happy Trading
Sir Poggy
Dual Mean Reversion Channel (adjusted lower band)This is a public and open-source lighter version compared to the "Overextended Price Channel" which is provided complimentaty to the Trend Insight System.
Introduction :
Channels are very useful tools to assess overextended price, volatility and upcoming retracement or impulsive moves (such as Bollinger Band squeezes). It is an indispensable addition to any trader using Mean Reversion theory for a scalp-trade or swing-trade.
This script contains :
- 2 channels Keltner-style, using the True Range for volatility
- customizable volatility (channel width) and smoothing period
- a standard selection of moving average ; SMA, EMA, VWMA
- an embedded readjustment of the lower bands to avoid the drop on a logarithmic scale (see explanation below)
Why another channel indicator ?
I have found most conventional channels to be either not based on "proper" volatility (e.g. standard deviation of price action for Bollinger Band), or the bottom channel to be ill adapted to the logarithmic scale and plunges to 0 on some high volatility periods, messing with readability on logarithmic auto-scaled chart.
Also, I find the channels to be most useful when superimposed with another one of longer length; especially a pair of channels with a 50 and 200 period moving average respectively. Mean Reversion traders that mostly trade the 50 and 200 SMA/EMA know what I am talking about as having a channel helps to have a better visual for a proper of entry and exit point.
Disclaimer :
This indicator was originally intended to be used along with the Trend Insight System to improve performance, and the default configuration mostly backtested on BTCUSD.
Please use with caution, proper risk management and along with your favorite oscillator, candlestick reading and signals system.
Some explanation :
Based on Mean Reversion paradigm, everything has a tendency to revert back to the mean :
- when the price enters the upper channel, it is supposed to be (or start getting) overbought as the market is getting overheated, thus prone to correction,
- on the other hand, when the price enters the lower channel, it is supposed to be (or getting) oversold and the market looks favorable for a buy-in.
Depending on the trading style used, a trader will usually either wait until the price leaves the channel towards the mean before taking action (conservative style) or you will set limit orders inside the channel as you expect a reversion to the mean (more agressive/risky style).
With two channels, more complex (and maybe precise) rules can be built to optimize one's trading strategy.
Important notes :
In the end, sticking with 50/200 length and a single setting on volatility might be wiser, be wary of overoptimization which is risky at best and counter productive at worst (according to legendary traders such as Mark Douglas). Even if, needless to say, the volatility needs to be adjusted between a nascent and volatile market (such as crypto) compared to standard call markets that are much less volatile.
End notes :
It will always be considered a work in progress to help bring out the best of trading with channels, any comment and suggestion are welcomed.
Squeeze Momentum [Plus]The "Momentum" in this indicator is smoothed out using linear regression. The Momentum is what is displayed on the indicator as a histogram, its purpose is obvious (to show momentum).
What is a Squeeze? A squeeze occurs when Bollinger Bands tighten up enough to slip inside of Keltner Channels .
This is interpreted as price is compressing and building up energy before releasing it and making a big move.
Traditionally, John Carter's version uses 20 period SMAs as the basis lines on both the BB and the KC.
In this version, I've given the freedom to change this and try out different types of moving averages.
The original squeeze indicator had only one Squeeze setting, though this new one has three.
The gray dot Squeeze, call it a "low squeeze" or an "early squeeze" - this is the easiest Squeeze to form based on its settings.
The orange dot Squeeze is the original from the first Squeeze indicator.
And finally, the yellow dot squeeze, call it a "high squeeze" or "power squeeze" - is the most difficult to form and suggests price is under extreme levels of compression.
Now to explain the parameters:
Squeeze Input - This is just the source for the Squeeze to use, default value is closing price.
Length - This is the length of time used to calculate the Bollinger Bands and Keltner Channels .
Bollinger Bands Calculation Type - Selects the type of moving average used to create the Bollinger Bands .
Keltner Channel Calculation Type - Selects the type of moving average used to create the Keltner Channel.
Color Format - you to choose one of 5 different color schemes.
Draw Divergence - Self explanatory here, this will auto-draw divergence on the indicator.
Gray Background for Dark Mode - to make them more visually appealing.
Added ADX (Average Directional Index) that measure a trend’s strength. The higher the ADX value, the stronger the trend. The ADX line is white when it has a positive slope, otherwise it is gray. When the ADX has a very large dispersion with respect to the momentum histogram, increase the scale number.
Added "H (Hull Moving Average) Signal". Hull is a extremely responsive and smooth moving average created by Alan Hull in 2005. Have option to chose between 3 Hull variations.
Added "Williams Vix Fix" signal. The Vix is one of the most reliable indicators in history for finding market bottoms. The Williams Vix Fix is simply a code from Larry Williams creating almost identical results for creating the same ability the Vix has to all assets.
The VIX has always been much better at signaling bottoms than tops. Simple reason is when market falls retail traders panic and increase volatility, and professionals come in and capitalize on the situation. At market tops there is no one panicking... just liquidity drying up.
The FE green triangles are "Filtered Entries"
The AE green triangles are "Aggressive Filtered Entries"
(JS) Interchanging ATR & VWAP BandsOkay so this is pretty simple, but I think it's a great tool for day trading especially. I just took the default VWAP and Keltner channel scripts and combined them together.
The top option allows you to choose which one you'd prefer to use, "Use ATR instead of VWAP" .
The next options, "ATR Source", "KC Length", and "ATR Length" are the parameters for the ATR Bands.
"Number of Bands" allows you to choose how many bands you'd like to be on display (you can choose 1-8).
"Use Expoential MA" and "Band Style" are more default parameters from Keltner Channels used to set up the ATR Bands.
The "ATR Bands" are just stacked Keltner Channels separated by 1 ATR each, whereas the "VWAP Bands" are separated by standard deviation just like the default script from Trading View.
In these example chart, you can see the weekly VWAP with 8 deviation bands and 5 ATR bands with Keltner Channels.
