Hurst ALMA Channels With Signals [UAlgo]
In the pursuit of identifying potential market pivots, a single measurement of Average True Range (ATR), may not provide sufficient information on its own, lacking directional insights. However, by employing a Moving Average (MA), specifically the Arnaud Legoux MA with Hurst C. calculation applied, a potential trading range can be visualized, taking recent volatility into account.
The underlying assumption is that if volatility remains relatively stable and the price extends beyond this ATR-derived range, there is a high probability of a reversion to the mean. At this point, it is postulated that available buying or selling pressure is depleted, prompting a pivot back to the mean.
To enhance the analysis, multiple MAs of different lengths are plotted. While individual MAs alone may not convey substantial information, observing reversions to the mean between MAs of varying lengths becomes insightful. Shorter MAs may oscillate above or below longer MAs, returning to the mean and creating crossover patterns.
The key innovation lies in combining these two concepts. By utilizing three different length MAs with corresponding ATR lengths, a dynamic system is established. The smallest band fluctuates within the medium band, and the medium band oscillates within the large band, creating approximate short, medium, and long trading ranges relative to the MAs.
For instance, in a theoretical scenario, when the smallest band reaches the upper limit of the medium band, and simultaneously, the medium band reaches the upper limit of the large band, and the price surpasses all of them, there is a heightened probability of a market reversal.
It's important to emphasize that these observations are based on historical volatility patterns and are subject to adjustments based on specific market conditions and the chosen instrument.
The developed indicator generates three distinct signal types, each providing valuable insights into potential market pivots without disclosing specific parameters:
Large Triangles : Representing a high-probability pivot, this signal occurs when the price surpasses all bands, either at the top or bottom. It suggests an extreme point where a pivot is likely.
Medium Triangles : Indicating a notable market event, this signal emerges when the price exceeds both the small and medium bands but falls short of surpassing the large band. Additionally, the small band must have exceeded the medium band. This configuration points to a significant market move with a potential for reversion.
Small Triangles : This signal is observed when the price surpasses both the small and medium bands, yet does not breach the large band. Notably, the small band should not have exceeded the medium band. This signal type suggests a distinctive market condition where a pivot may be imminent.
These triangle signals are designed to identify key points in the market where historical patterns indicate a likelihood of reversion or significant price movement. It is crucial to note that the interpretation of these signals should be adapted to specific market conditions and instruments.
Good luck to you all !
Filtered
STD-Filtered, Regularized EMA/RMA [Loxx]STD-Filtered, Regularized EMA/RMA calculates and visualizes a standard deviation (STD) filtered, regularized version of the Exponential Moving Average (EMA) or Regular Moving Average (RMA) on a trading chart.
█ Understanding the Regularized Moving Average
The Regularized Moving Average, as conceptualized by Chris Satchwell, offers a more responsive interpretation compared to traditional moving averages. By incorporating a smoothing mechanism using "Lambda", this approach reduces lag without compromising the data's integrity.
In the realm of technical analysis, many regard it as a preferred alternative to the standard Moving Average and Exponential Moving Average.
█ How Does It Stand Out from Other Moving Averages?
While analysts traditionally shorten an indicator's length or period to minimize lag, the Regularized Moving Average uses a unique approach. By embedding "Regularization" within its computation, this method introduces Lambda (often symbolized as λ-calculus). This mathematical factor tames the moving average's undue fluctuations, offering more stability through its Lambda adjustments.
Pro Tip: For those analyzing smaller intraday timeframes, consider ramping up the Lambda setting to 6.0 or even higher. When tweaking these settings, always remember to backtest and observe how it impacts signal accuracy and noise filtering.
█ Standard Deviation Filtering:
This filtering mechanism is designed to smoothen price data by eliminating minor fluctuations that might be considered "noise". Here's how the process works:
For every data point, the standard deviation of prices over a specified period is calculated.
This standard deviation is then multiplied by a user-defined value to determine a threshold. This threshold defines the magnitude of change required in the price for it to be considered significant.
For each price, if the absolute difference between its current and previous value is less than this threshold, the price is kept unchanged (considered insignificant and thus filtered). If the difference exceeds the threshold, the price is considered significant and remains as is.
By applying this filter, minor price variations within the threshold are disregarded, resulting in a smoother representation of the price data.
█ Moving Average Calculation:
The script provides an option to calculate either a regularized Exponential Moving Average (EMA) or a Regular Moving Average (RMA). Here's how these are approached:
If the EMA option is selected: A weighted formula is used where more recent prices have a higher influence on the average than older prices. This is achieved by applying a fraction that's inversely related to the chosen period. The outcome is an average that reacts more quickly to recent price changes.
If the RMA option is selected: The average is computed by giving equal weight to all prices within the chosen period.
Both these averages then undergo a regularization process. Regularization, in this context, refers to adjusting the moving average using a factor to make it potentially more sensitive or responsive to price changes.
This regularized moving average can offer a refined perspective on price trends by being more adaptive to recent changes, potentially highlighting turning points or trend continuations more effectively.
█ Extras
Signals
Alerts
Bar coloring
Filtered Momentum Indicator (FMI)The Filtered Momentum Indicator (FMI) is a tool created to assist traders in identifying changes in momentum and gaining insights into potential shifts in price trends. By combining the concepts of momentum and Bollinger Bands, the FMI offers a unique perspective on momentum values and their relationship to price movements, helping traders make informed trading decisions. The FMI is calculated using two main components:
-- Momentum Calculation : Momentum measures the strength and velocity of price changes. It is calculated by comparing the current price to the price 14 (default) periods ago and expressing it as a percentage.
-- Bollinger Bands Calculation : Bollinger Bands are based on the momentum values and provide a range within which the momentum is expected to fluctuate. The upper and lower bands are determined using a specified period (default of 20) and deviations (default of 2.0).
The FMI consists of two lines : F+ (Filtered Plus) and F- (Filtered Minus). These lines help gauge the strength of bullish and bearish momentum:
-- F+ represents the difference between the upper Bollinger Band and the momentum values. It indicates the strength of bullish momentum. F+ is colored aqua.
-- F- represents the difference between the momentum values and the lower Bollinger Band. It indicates the strength of bearish momentum. F- is colored yellow.
When analyzing the FMI, pay attention to the relationship between F+ and F-:
-- If F- is greater than F+ , it suggests potential bullish momentum, indicating that prices may have room to rise.
-- If F+ is greater than F- , it suggests potential bearish momentum, indicating that prices may have room to decline.
Coloration of the FMI enhances its interpretability - when F- is greater than F+, the indicator color is set to lime (green), signaling potential bullish momentum; when F+ is greater than F-, the indicator color is set to fuchsia (purple), signaling potential bearish momentum.
The FMI can be applied in various ways for trading strategies:
-- Identifying Potential Reversals : Watch for crossovers between the F- and F+ lines, as they may indicate a potential shift in momentum and offer opportunities to enter or exit trades.
-- Confirmation Tool : Combine the FMI with other technical indicators or price patterns to validate potential trend reversals or continuations. By aligning signals from different indicators, you can strengthen your trading decisions.
-- Trade Timing : Consider taking trades in the direction of the dominant FMI color. When the indicator shows strong bullish momentum (F- > F+), consider going long. Conversely, when it shows strong bearish momentum (F+ > F-), consider going short.
It is essential to be aware of the limitations of the FMI:
-- False Signals : The FMI, like any indicator, may generate false signals, especially during low volatility or choppy market conditions. Always use the FMI in conjunction with other analysis techniques for confirmation.
-- Lagging Nature : The FMI relies on historical price data, causing it to lag behind sudden market moves. Keep in mind that the FMI provides insights based on past momentum and may not capture immediate changes in market conditions.
By combining momentum and Bollinger Bands, this indicator provides a unique perspective for making informed trading decisions. Utilize the FMI in conjunction with other analysis techniques, considering its limitations, to enhance your trading strategy and improve decision-making.
Step-MA Filtered Stochastic [Loxx]Step-MA Filtered Stochastic is a stochastic indicator with step moving average filtering. This smooths the signal by filtering out noise.
What is the Stochastic Indicator?
The stochastic oscillator, also known as stochastic indicator, is a popular trading indicator that is useful for predicting trend reversals. It also focuses on price momentum and can be used to identify overbought and oversold levels in shares, indices, currencies and many other investment assets.
The stochastic oscillator measures the momentum of price movements. Momentum is the rate of acceleration in price movement. The idea behind the stochastic indicator is that the momentum of an instrument’s price will often change before the price movement of the instrument actually changes direction. As a result, the indicator can be used to predict trend reversals.
The stochastic indicator can be used by experienced traders and those learning technical analysis. With the help of other technical analysis tools such as moving averages, trendlines and support and resistance levels, the stochastic oscillator can help to improve trading accuracy and identify profitable entry and exit points.
Included:
Bar coloring
3 signal variations w/ alerts
Loxx's Expanded Source Types
STD-Filtered Variety RSI of Double Averages w/ DSL [Loxx]STD-Filtered Variety RSI of Double Averages w/ DSL is a standard deviation step filtered RSI indicator that is calculated using double smoothing. The user can choose from 8 different RSI types and 38 different double smoothing types. This indicator uses Discontinued Signal Lines instead of regular signals and levels. This allows the signals to be more precise in catching early trend breakouts and breakdowns.
Things to note
Double smoothing of the source does not function like DEMA, for example. This double smoothing is just smoothing of smoothing of source
There are two types of smoothing for Discontinued Signals Lines: Regular EMA and Fast EMA
T3 RSI has been added on top of Loxx's Variety RSI library
Contained inside this indicator
Loxx's Moving Averages
Loxx's Variety RSI
Related indicators
Corrected RSI w/ Floating Levels
Adaptive, Jurik-Filtered, Floating RSI
Variety RSI w/ Dynamic Zones
Included
Bar coloring
Alerts
2 types of signals with precision adjustment
Loxx's Variety RSI
Loxx's Moving Averages
Jurik Smoothed Stochastic - TraderHalaiJurik Smoothed Stochastic
The stochastic indicator has been long used by traders to identify inflection points in the price and to give a direction on Bullish and Bearish bias.
This indicator aims to improve on the plots the %K value smoothed using a Jurik Filter instead of a simple moving average. This allows for a more adaptive K value average price, whilst also providing superior smoothing to traditional moving averages.
As the Jurik Filter is a proprietary and non-open-source implementation, this script uses a common filters library implementation of Jurik MA which is a suitable proxy to the actual Jurik MA filter.
Big thanks to LastGuru for making his version freely available. You can find his version of the Jurik Filters in the credits section below.
%K is the Jurik Smoothed Version of the original Stochastic Formula
%D is calculated using the following formula. This idea was borrowed from John Ehler’s stochastic implementation and can be seen below:
%D = 0.05 + 0.95 * K
Features
%K line, Overbought and Oversold level and Mid Line Level
Oversold / Overbought reversal indicators and signals - Shown in Red and Green
Bullish / Bearish Divergences – Including Hidden divergences to spot reversals and continuations of trend (Big thanks to the developers of the built-in RSI Divergence indicator) - Shown as below:
Bullish / Bearish crossover of %K with %D - Shown in Cyan and Fuschia
Alerts for all of the above conditions
Double Jurik smoothing mode - similar to slow Stochastic
Credits :
Massive shoutout to the following scripts:
LastGuru JurikMA implementation (Common Filters Library)
Divergence Indicator – Built into TradingView and coded by TradingView Developers
This script is published as open source to allow for criticism, further development of this strategy and use by the community. Feel free to use this indicator/source code as you see fit.
Enjoy! :)
Pips-Stepped, OMA-Filtered, Ocean NMA [Loxx]Pips-Stepped, OMA-Filtered, Ocean NMA is an Ocean Natural Moving Average Filter that is pre-filtered using One More Moving Average (OMA) and then post-filtered using stepping by pips. This indicator is quadruple adaptive depending on the settings used:
OMA adaptive
Hiekin-Ashi Better Source Input Adaptive (w/ AMA of Kaufman smoothing)
Ocean NMA adaptive
Pips adaptive
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA , harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
What is the Ocean Natural Moving Average?
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programed to do so. For more info, read his guide "Ocean Theory, an Introduction"
What's the difference between this indicator and Sloan's original NMA?
Sloman's original calculation uses the natural log of price as input into the NMA , here we use moving averages of price as the input for NMA . As such, this indicator applies a certain level of Ocean theory adaptivity to moving average filter used.
Included:
Bar coloring
Alerts
Expanded source types
Signals
Flat-level coloring for scalping
Double RSI FilterI've seen several youtubers using 2 RSI's on top of one another to filter trades for their strategies. I figured I would just code it up as an all-in-one indicator for people who have the basic package. This way they have an extra slot for another indicator if they need one and also for convenience.
Longs only when RSI 1 is above RSI 2 and shorts only when opposite. The arrows show where crosses of the RSI's occur.
Let me know if there is something else like this where it would just be very convenient to have 2 indicators on one window or other such things and I'll see if I can do something for you guys in my spare time. I'm just an amateur coder, but learning as I do more of these for people.
Thank you!
Hope this helps someone! :)
ATR Without OutliersIt is an ATR indicator which filters out outliers.
Outliers are values which are higher than the standard deviation of the true range.
It may be better than normal ATR for stop loss, because it does not keep large values after pump or dump.
It is very useful for high volatile markets like crypto markets.
Filtered Waves [NXT2017] #Linda Raschke #basics on Arthur MerrilHI BIG PLAYERS,
this script I wrote for an enquiry of a tradingview-user. It should represent the Filtered Waves idea from Arthur Merril and used by Linda Raschke.
It's similar like a visualization of Elliott Waves.
On YouTube title "MTA UK Chapter Presentation with Linda Raschke" between 34-36 minutes Linda Raschke shows the rules for her Filterd Waves.
Any questions? Ask me!
King regards
NXT2017
========
TO MY PERSON
I'm the second winner of the official German Forex Trading Competition in 2018.
Look here to the ranks:
deutsche-trading-meisterschaften.de
I speak german, english and russian.
My strength in trading are Wolfe Wave pattern.
Bollinger Band Oscillator Filtered Long/Short Entries This script calculates entries using Bollinger Bands paired with a series of oscillators. Simply set the Bollinger Band length, as well as the length of the oscillators, and you're good to go. Filtered entries as well as unfiltered entries are plotted by default. Excellent results on longer timeframes (1 hour and higher), although scalping can be done on lower timeframes as well. Filtered entries give safer long/short entries, but plenty of good signals are generated by the unfiltered data as well. Has been tested and found to be effective on several stocks and cryptocurrencies.
Message me to try this script out, thanks!
BB Filtered AlertsBollinger Band signals filtered with dual RSIs and EMA.
EMA confirms trend.
Signals above EMA are filtered with "Uptrend RSI" filter
Signals below EMA are filtered with "Downtrend RSI" filter
There is no "one size fits all" setting. Settings are very period and name specific, depending on ATR.
CM_Pivot Points_M-W-D-4H-1H_FilteredFamous Filtered Pivots Indicator -Many TimeFrames Available
CM_Pivot Points_M-W-D-4H-1H_Filtered
***Special Thanks to TheLark...AKA...The Coding Genius For Providing His Expertise...
***New Feature - Ability to turn On/Off Pivot Moving Average
***New Feature - Ability to turn On/Off Filtered Pivots (Explained Below)
Available Timeframes (Change In Inputs Tab):
1 Hour
4 Hour
Daily
Weekly
Monthly
Yearly
***All Features Available in Inputs Tab
-Ability to Plot just 1, or all Pivot Timeframes
-Defaults to Monthly Pivots
-Ability to turn On/Off Pivot Moving Average
-Ability to turn On/Off Filtered Pivots
-Ability to Plot S3 and R3 on 1 Hour and 4 Hour Pivots
***FILTERED PIVOTS!!!
-THIS IS A WAY TO FIND THE HIGHEST PROBABILITY MOVES
-IF CURRENT PIVOT IS GREATER THAN PREVIOUS PIVOT (INCLUDING MARKET THRESHOLD CALCULATION) THEN PIVOT, S1, & R2 PLOT
-IF CURRENT PIVOT IS LESS THAN PREVIOUS PIVOT (INCLUDING MARKET THRESHOLD CALCULATION) THEN PIVOT, S2, & R1 PLOT
-***THIS IS A WAY TO FILTER OUT PIVOTS AND ONLY PLOT THE LEVELS THAT ARE EXPECTED TO BE MAJOR SUPPORT AND RESISTANCE
***VIDEO COMING SOON WHERE i WILL GO OVER IN DETAIL THE THOUGHT PROCESS AND METHODOLOGY
