The Bayesian Q OscillatorFirst of all the biggest thanks to @tista and @KivancOzbilgic for publishing their open source public indicators Bayesian BBSMA + nQQE Oscillator. And a mighty round of applause for @MarkBench for once again being my superhero pinescript guy that puts these awesome combination Ideas and ES stradegies in my head together. Now let me go ahead and explain what we have here.
I am gonna call it the Bayesian Q Oscillator I suppose. The goal of the script is to solve an issue both indicators on their own suffer from. QQE signals are not new and often the problem has always been false signals for them. They are good for scalping but the difference between a quality move and a small to nearly nonexistent move following a signal is not so clear. Kivanc made his normalized version to help reduce this problem by adding colors to his histogram type verision that would essentially represent if price was a trending move or in a ranging structure. As you can see I have kept this Idea but instead opted for lines as the oscillator. two yellow line (default color) is a ranging sideways area and when there is red or green it is trending up or down. I wanted to take this to the next level with combining the Bayesian probability oscillator that tista put together.
The Bayesian indicator is the opposite for its issue as it is a probability indicator that shows which candle or price movement is more likely to come next. Red rising means possibly down move soon and green means up soon. I will not go into the complex details of this indicator but will suggest others take a look at his and others to understand the idea behind them. The point I am driving at is that it show probabilities or likelyhood without the most effecient signal device to match it. This original was line form and now it is background filled colors.
The idea. is that you can potentially get some stronger and more accurate reversal signals with these two paired together. when you see a sell signal or cross with the towering or rising red... maybe it is a good jump potentially. The same for green. At the same time it is a double added filter effect from just having yellow represent it is ranging... but now if you get a buy signal (example) and have yellow lines (example) along wi5h a red rising or mountain color background... it not only is an indication of ranging, but also that there is potentially even a counter move coming based on the probabilities. Also if you get into a good trade and see dual yellow qqe crosses with no color represented by the bayesian background... it is possible it might only be noise.
I have found them to work decently in the 1 hour timframe. Let me know your experience.
I hope everyone takes a look at the originals to understand them. Full credit goes to those guys for this to be here. Let me know how it is working out for you.
Here are the original links.
bayesian
Normalized QQE
Filter
Exotic SMA Explorations Treasure TroveThis is my "Exotic SMA Explorations Treasure Trove" intended for educational purposes, yet these functions will also have utility in special applications with other algorithms. Firstly, the Pine built-in sma() is exceedingly more efficient computationally on TV servers than these functions will be. I just wanted to make that very crystal clear. My notes elaborate on this in the code blatantly.
Anyhow, the simple moving average(SMA) is one of the most common averaging filters used in a wide variety of algorithms. "Simply put," it's name says a lot about it. The purpose of this script, is to demonstrate variations of it's calculation in a multitude of exotic forms. In certain scenarios our algorithms may require a specific mathemagical touch that is pertinent to our intended goals. Like screwdrivers, we often need different types depending on the objective we are trying to attain. The SMA also serves as the most basic of finite impulse response(FIR) algorithms. For example, things like weighted moving averages can be constructed by using the foundational code of SMA.
One other intended demonstration of this script, is running multiple functions for comparison. I have had to use this from time to time for my own comparisons of performance. Also, imbedded into this code is a method to generically and recklessly in this case, adapt an algorithm. I will warn you, RSI was NEVER intended to adapt an algorithm. It only serves as a crude method to display the versatility of these different algorithms, whether it be a benefit or hinderance concerning dynamic adaptability.
Lastly, this script shows the versatility of TV's NEW additions input(group=) and input(inline=) upgrades in action. The "Immense Power of Pine" is always evolving and will continue to do so, I assure you of that. We can now categorize our input()s without using the input(type=input.bool) hackTrick. Although, that still will have it's enduring versatility, at least for myself.
NOTICE: You have absolute freedom to use this source code any way you see fit within your new Pine projects. You don't have to ask for my permission to reuse these functions in your published scripts, simply because I have better things to do than answer requests for the reuse of these functions. Sufficient accreditation regarding this script and compliance with "TV's House Rules" regarding code reuse, is as easy as copying the functions in their entirety as is. Fair enough? Good!
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
Efficient Trend Step Mod (v.3)This is a version 3 of my mod of the script by alexgrover - Efficient Trend Step.
The logic is based on calculation of Kaufman's efficiency ratio (ER):
ER = Direction / Volatility
where:
Direction = ABS (Close – Close )
Volatility = n ∑(ABS(Close – Close ))
n = The efficiency ratio period.
This version features volatility and volume filter and custom performance module.
Intraday SeasonalityDay trading trend filter indicator designed to hep get better entries or exits based on historical opens and closes each hour.
This indicator is NOT designed as an entry or exit signal. The purpose behind it is to give you statistical information about how likely certain times of day are either bullish, bearish or neutral and use that to confirm or reject other trading signals.
For example you might be anticipating a breakout based on your strategy or another indicator but see that the next few hours are usually bearish and re-evaluate entering the trade.
The Intraday Seasonality indicator calculates the percentage of candles per hour that had a higher close than open.
Default settings are:
- a look-back of 90 days.
- extreme bullish (bright green) above 74%
-extreme bearish (bright red) below 25%
- bullish (green) above 55%
- bearish (red) below 45%
- neutral (white) exactly 50%
- no trend (gray) 46% - 54%
All of these are updatable via the settings.
This indicator is designed to work only on the 1 hour timeframe.
To use the indicator set your local timezone offset in the indicator settings.
*Due to daylight savings and certain timezones changing throughout the year there is a timezone override in the indicator settings if the indicator doesn't pick up the correct local time.
Ehlers Laguerre Filter [CC]The Laguerre Filter was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pg 216) and this indicator works well with letting you know both the short and long term trend as well as a pretty good moving average. If the indicator line is above the black line then it is a long term uptrend and below the black line is a long term downtrend. Buy when the indicator line is green and sell when it turns red.
Let me know if there are other scripts you would like to see me publish or if you want something custom done!
Monthly SeasonalitySimple indicator designed as filter so you can easily see how the currency or asset performed during each month historically.
Can used to identify a possible month to enter or exit a trade in. For best results use in combination with another indicator or candle pattern to signal an entry in a historically bullish month
*This indicator is designed to be used only on the monthly chart.
Bandpass Filters v.02
This is an alternative way to do bandpass filtering. I Still need to update it to support moveable frequency bands. The lowBandpass() is just a 'trick,' as it simply subtracts the highBandpass() from the close data, so it is not really accurate in that it removes the low frequencies, just in a rather less-than-ideal manner.
The "spectrum" of the dataset to filter will always be from 0 to 100, so think of filter boundary as %. So, a boundary of 40% means: 40% of the low-frequencies have been removed from the original data to make the red graph, and 40% of the high-frequencies have been removed from the original data to make the green graph.
This came about after reading the excellent tutorial on signal processing in Pine Script (www.pinecoders.com), as the techniques listed there did not do exactly what I was looking for.
Here is a low-pass graph
Here is a hi-pass graph
[NLX-L2] Hurst Exponent Signal Filter- Hurst Exponent Signal Filter -
The Hurst Exponent Signal Filter is meant to be used with an external signal source, this can be any indicator with a signal plot output (-1 Sell / 1 Buy)
It filters out a lot of noisy signals and improves the performance of many indicators.
- Example: How to Use -
1. Add a trend Indicator like Trend Index MTF to your chart
2. Add an indicator with a signal plot like Fishers Stochastic Center of Gravity to your Chart and select the Trend Index MTF with Type L1 in the Settings as Signal Source
3. Add this Hurst Signal Filter to your Chart and select the Fishers Stochastic Center of Gravity with Type L2 in the Settings as Signal Source
4. Add the Backtest Module to your Chart and select the Hurst Signal Filter with Type L2 as Source
- Alerts for Automated Trading -
See my signature below. Contact me for the Alert module.
Computing FIR Filters Using Arrays [WMA Example]Over the years, many FIR filters have been proposed by the Pine community, with the standard way of computing them being `for` loops. The arrival of arrays allows for a new, more efficient way to compute them.
This script provides a template showing how you can compute FIR filters using Pine arrays.
FIR Filters
FIR stands for "Finite Impulse Response", and is associated with types of filters whose impulse response reaches a steady state.
FIR filters are calculated using convolution, or more simply put, using a weighted sum between a set of filter coefficients and past input values over a finite window.
In Pine, FIR filters are generally computed inside a `for` loop executing three processes:
1- Computing the coefficients.
2- Summing all the computed coefficients.
3- Performing the weighted sum between the inputs values and the computed coefficients.
Then we divide the result of our weighted sum by the sum of the coefficients obtained in step 2.
Because the computations inside the `for` loop execute on each bar, execution time can be significant when the calculation of coefficients is complex. This is where arrays are handy, as we can compute the coefficients just once, store them into an array, and use them in a weighted sum without the need to recalculate them over and over. This drastically reduces the computation time required to calculate a FIR filter.
The new `array.sum()` function helps eliminate step 2, thus further decreasing computation time.
How to Use This Template
All you need to do is to put the code that computes your coefficients in the first `for` loop (variable `w`). If the code that computes your coefficients contains more than one line, just make sure your final coefficient is placed in variable `w` (or change the `value` argument in `array.push()`). Another option is to declare a function that computes the coefficients and use it instead of variable `w`.
Look first. Then leap.
Ehlers 3 Pole Butterworth Filter V2 [CC]The 3 Pole Butterworth Filter was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 196-197) and this indicator is a moving average that also works well as a trendline. Buy when the indicator line turns green and sell when it turns red.
Let me know if you would like me to publish other indicators or if you want something custom done!
Ehlers 2 Pole Super Smoother Filter V2 [CC]The 2 Pole Super Smoother Filter was created by John Ehlers (Cycle Analytics For Traders pg 32) and this follows the price very closely and very useful because it is consistent with uptrends and falls sharply during a sudden downtrend so it should be able to help you stay more profitable. Buy when the indicator line turns green and sell when it turns red.
Let me know if there are other indicators you would like to see me publish or if you want something custom done!
Percentile Nearest Rank Using Arrays [LuxAlgo]The new array feature is extremely powerful, as it will allow pinescript users to do more complex things, or compute existing calculations more efficiently, it will also be possible to shine some light to some already existing functions, one of them being percentile_nearest_rank .
We have been working on this new feature with our pal alexgrover, and made this script which computes a rolling percentile using the nearest rank method.
Settings
Length: Window of the rolling percentile, determine the number of past data to be used.
Percentage: Return the current value if Percentage % of the data fall below that value, the setting is in a range (0,100).
Src: Input source of the indicator.
Usage
A rolling percentile can have many usages when it comes to technical analysis, this is due to its ability to return the value of three common rolling statistics, the rolling median, which can be obtained using a percentage equal to 50, the rolling maximum, obtained with a percentage equal to 100, and the rolling minimum, obtained with a percentage equal to 0.
When we use our rolling percentile as a rolling median, we can obtain a robust estimation of the underlying trend in the price, while using it as a rolling maximum/minimum can allow us to determine if the market is trending, and at which direction. The rolling maximum/minimum is a rolling statistic used to calculate the well known stochastic oscillator and Donchian channel indicator.
We can also compute rolling quartiles, which can be obtained using a percentage of 25 or 75, with one of 25 returning the lower quartile and 75 the upper quartile.
In blue the upper rolling quartile (%75), in orange the lower rolling quartile (%25), both using a window size of 100.
Details
In order to compute a rolling percentile nearest rank, we must first take the most recent length closing prices, then order them in ascending order, we then return the value of the ordered observations at index (percentage/100*length) - 1 (we use - 1 because our array index starts at 0).
Bollinger Bands Breakout StrategyBollinger Bands Breakout Strategy is the strategy version of Bollinger Bands Filter study version, which can be found under my scripts page. The strategy goes long when price closes above the upper band and goes short signal when price closes below the lower band.
Bollinger Bands is a classic indicator that uses a simple moving average of 20 periods, along with plots of upper and lower bands that are 2 standard deviations away from the basis line. These bands help visualize price volatility and trend based on where the price is, in relation to the bands.
The strategy doesn't take into account any other parameters such as Volume / RSI / Fundamentals etc, so user must use discretion based on confirmations from another indicator or based on fundamentals. The strategy results are based on purely long and short trades and doesn't take into account any user defined targets or stop losses.
The strategy works great when the price closes above/below upper/lower bands with continuation on next bar. It is definitely useful to have this strategy or the Bollinger Bands filter along with other indicators to get early glimpse of breach/fail of bands on candle close during BB squeeze or based on volatility .
This can be used on Heikin Ashi candles for spotting trends, but HA candles are not recommended for trade entries as they don't reflect true price of the asset.
The strategy settings default is 55 SMA and 1 standard deviation for Bollinger Bands filter, but these can be changed from settings.
It is definitely worth reading the 22 rules of Bollinger Bands written by John Bollinger if interested in trading Bollinger Bands successfully.
[A618]Improved Wave channel 3D The Script is an Amalgamation of Two prominent Scripts in One
1. Ehlers 2 Pole ButterWorth Filter
2. Wave Channel 3D
Intuitively,
Buy when Candles are above all the filter Lines
Sell when Candles are below the Filter Lines
CREDITS
[A618] Vortex Indicator Alert Screener [Noise Filtered]This Indicator helps you get alerts from Vortex Indicator if a trend is Established.
One of my followers asked me to do this: @Kiran_05
How this is made ?
1. Vortex Crossovers are taken into consideration in a noise filtered manner
2. Noise filtering is done by trend establishment due to Ehlers 2 pole ButterWorth Filter and EMA50 Crosses
How to use it ?
1. Can be used as a screener on the Script to generate the screened Securities from a Watchlist of Securities
2. Wait for a Candle break above of the generate green signal to get into trade, and vice versa
Credits :
@CheatCountry
For Ehlers 2 Pole Butterworth Filter V2
Hope this Helps
Band-Pass FilterJust a clean script that can be applied on top of other indicators/sources or you can take the function out of the source and use it in other scripts.
The idea for this was taken from www.pinecoders.com except I am utilizing an EMA instead of SMA. Simply put, we are combining a low-pass filter (moving average) with a high-pass filter (smoothed difference between the source and moving average). The result is a filter/moving average that provides a great combination of minimizing noise while still reacting strongly to price and trend changes.
I like to use this filter in place of other MAs in Pine Scripts to smooth my data. So instead of doing something like sma(stochastic,5) I can easily plug in bp(stochastic,5). It works just fine for your primary moving averages against price as well.
Tool: Chop & Trade ZonesA simple yet powerful way to filter out choppy ranges or sideways moves without missing out on good trades
It calculates the %-distance of the price to a moving average so you can ignore buy/sell signals around the center line.
The upper and lower line are thresholds to catch reversals of the trend when the distance to moving average is increasing.
Thanks @dgtrd and @imzeeshan for the inspiration 🙏
KINSKI Laguerre Filter WaveThe "Laguerre Filter Wave" Indicator usually shows market cycles and is a perfect fit for swing traders who trade with market fluctuations. Upward-trends are shown as green lines and optional bands. Downward trends are represented by the color red. Each of the 18 available lines can be adjusted to your own preferences via a gamma factor.
You also have the following display options:
- "Up/Down Movements: On/Off" - Shows ascending and descending of lines
- "Bands: On/Off" - Fills the space between the lines with colors to indicate up or down trends
- "Bands: Transparency" - sets the transparency of the fill color
- "MA Line: Size" - sets the width of the lines
- "MA Line: Transparency" - sets the transparency of the lines
Index Trend Filter - Weekend Trend TraderThis little script simply gives you a quick visual cue of where price is compared to a particular EMA of another security or underlying index.
It is based on Nick Radge's broader market filter weekend trend trader system, but can be applied to other timeframes if you want to confirm if the index is in an up trend or down trend.
• Green means the underlying index price is above the EMA
• Red means the underlying index price is below the EMA
Ehlers 2 Pole Butterworth Filter V2 [CC]The 2 Pole Butterworth Filter was created by John Ehlers (Cycle Analytics For Traders pg 32) and this is an updated version of his original 2 pole Butterworth Filter script that seems to follow the price even closer. Buy when the indicator line turns green and sell when it turns red.
Let me know if there are other scripts you would like to see me publish or if you want something custom done!
Ehlers 2 Pole Butterworth Filter V1 [CC]The 2 Pole Butterworth Filter was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pg 192) and this is one of his many filters that cuts out the noise and follows the price very closely. I recommend combining a 2 pole and 3 pole system of the same type of filter. Buy when the indicator line is green and sell when it is red.
Let me know if there are other indicators you would like to see or if you want something custom done!
Ehlers Super PassBand Filter [CC]The Super PassBand Filter was created by John Ehlers (Stocks & Commodities V. 34:07 (10–13)) and this is a pretty useful indicator to let you know how volatile the market is right now. This is useful for scalpers because this lets you avoid the choppy markets (usually when the rms is 1.50 or less but feel free to choose your own level) and gives you good entry and exit points. Buy when the indicator line is green and sell when it is red.
Let me know if there are other indicators you would like to see me publish or if you want something custom done!
Ehlers 2 Pole Super Smoother Filter V1 [CC]The 2 Pole Super Smoother Filter was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pg 202) and this one of his filters that follows the price very closely. I would recommend to change the default settings to what fits your trading style the best. Buy when the indicator line turns green and sell when it turns red.
Let me know if there are other scripts you would like to see or if you want something custom done!
