Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
Fisher
SuperTrend Fisher [AlgoAlpha]🚀🌟 Introducing the "Super Fisher" by AlgoAlpha, a sophisticated and versatile tool crafted for the discerning trader. This innovative indicator merges the precision of the Fisher Transform with the adaptability of the SuperTrend methodology, offering a fresh perspective on market analysis. 📈🔍
Key Features:
🔶 Customizable Settings: Tailor the indicator to your trading style with adjustable inputs like "Fair-value Period" and "EMA Length". Choose your preferred "Up Color" and "Down Color" for a personalized visual experience.
🔶 Advanced Fisher Transform: At the heart of this tool is the Fisher Transform, an algorithm renowned for pinpointing potential price reversals by normalizing asset prices.
🔶 Integrated SuperTrend Functionality: This feature adds a layer of trend analysis, using the refined Fisher Transform values to generate dynamic, trend-following signals.
🔶 Enhanced Visualization: Clearly distinguishable bullish and bearish market phases, thanks to the color-coded plots of Fisher Transform and SuperTrend values.
🔶 Overbought/Oversold Levels: Visual plots and fills for these levels provide additional insights into market extremities.
🔶 Configurable Alerts: Stay informed with alerts for critical market movements like crossing the zero line or the SuperTrend.
Logic:
The "Super Fisher" operates on a sophisticated algorithm:
1. Fisher Transform Calculation: It starts by calculating the Detrended Price Oscillator (DPO) and its standard deviation. These values are then transformed using the Fisher Transform formula, which is subsequently smoothed with a Hull Moving Average.
2. SuperTrend Integration: The SuperTrend function employs the Fisher Transform values to create a dynamic trend-following tool. It calculates upper and lower bands and determines which one to use for market direction based on whether the fisher is above or below the bands, offering an insightful view of the price trend.
3. Overbought/Oversold Identification: The tool plots specific levels to indicate overbought and oversold conditions, aiding in the identification of potential reversal points.
Here's a closer look at the core calculations:
Calculates the Fisher Transform:
value = 0.0
value := round_(.66 * ((src - low_) / (high_ - low_) - .5) + .67 * nz(value ))
fish1 = 0.0
fish1 := .5 * math.log((1 + value) / (1 - value)) + .5 * nz(fish1 )
fish1 := ta.hma(fish1, l)
Calculates the SuperTrend:
supertrend(factor, atrPeriod, srcc) =>
src = srcc
atr = atrr(srcc, atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or srcc < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or srcc > prevUpperBand ? upperBand : prevUpperBand
int direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
direction := 1
else if prevSuperTrend == prevUpperBand
direction := srcc > upperBand ? -1 : 1
else
direction := srcc < lowerBand ? 1 : -1
superTrend := direction == -1 ? lowerBand : upperBand
How to Use:
📊 To maximize the potential of the "Super Fisher", follow these steps:
1. Customize Settings: Adjust the inputs to match your trading preferences. This includes setting the periods for the Fisher Transform and SuperTrend, as well as choosing colors for better visualization.
2. Analyze the Market: Observe the Fisher Transform and SuperTrend plots to gauge market direction. Pay special attention to color changes, as they indicate shifts in market sentiment.
3. Identify Extremes: Use the overbought and oversold plots to understand potential reversal points.
4. Set Alerts: Utilize the alert functionality to stay informed about significant market movements, ensuring you never miss an opportunity.
🔥 In summary the "Super Fisher" is a comprehensive market analysis tool designed to enhance your trading insights and decision-making process. 📉🌟🚨
Normalized Fisher Transformed VolumeGreetings Traders,
I am thrilled to introduce a game-changing tool that I've passionately developed to enhance your trading precision – the Normalized Fisher Transformed Volume indicator. Let's dive into the specifics and explore how this tool can empower you in the markets.
Unlocking Trading Precision:
Normalization and Transformation:
Normalize raw volume data to ensure a consistent scale for analysis.
The Fisher Transformation converts normalized volume data into a Gaussian distribution, providing enhanced insights into trend dynamics.
Flexible Modes for Tailored Strategies:
Choose from three distinct modes:
Volume T3 (MA) + Heatmap: Identify trends with T3 Moving Average and visualize volume strength with Heatmap.
Volume Percent Rank: Evaluate the position of current volume relative to historical data.
Volume T3 (MA) Percent Rank: Combine T3 Moving Average with percentile ranking for a comprehensive analysis.
Heatmap Visualization for Quick Insights:
Heatmap Zones and Lines visually represent volume strength relative to historical data.
Customize threshold multipliers and color options for precise Heatmap interpretation.
T3 Moving Average Integration:
Smoothed representation of volume trends with the T3 Moving Average enhances trend identification.
Percent Rank Analysis for Context:
Gauge the position of normalized volume within historical context using Percent Rank analysis.
User-Friendly Customization:
Easily adjust parameters such as length, T3 Moving Average length, Heatmap standard deviation length, and threshold multipliers.
Intuitive interface with colored bars and customizable background options for personalized analysis.
How to Use Effectively:
Mode Selection:
Identify your preferred trading strategy and select the mode that aligns with your approach.
Parameter Adjustment:
Fine-tune the indicator by adjusting parameters to match your preferred trading style.
Interpret Heatmap and T3 Analysis:
Leverage Heatmap and T3 Moving Average analysis to spot potential trend reversals, overbought/oversold conditions, and market sentiment shifts.
Conclusion:
The Normalized Fisher Transformed Volume indicator is not just a tool; it's your key to unlocking precision in trading. Crafted by Simwai, this indicator offers unique insights tailored to your specific trading needs. Dive in, explore its features, experiment with parameters, and let it guide you to more informed and precise trading decisions.
Trade wisely and prosper,
simwai
Fisher+ [OSC]The Fisher Transform Indicator is classified as an oscillator, meaning that its value swings above and below a central point. This characteristic allows traders to identify overbought and oversold conditions, providing potential clues about market reversals. As mentioned previously, it is an oscillator so the strength of the move is displayed by how long the fisher line stays above/below zero. Indicator can be used to aid in confluence near supply/demand zones.
White Line = Fisher
Red/Blue Line = Moving Average
--Changes color whether fisher line is above/below the MA
Red/Blue Shaded Line = Moving Average
--Changes color based on a smoothing factor
Red/Blue Shaded Fill = Asset in Overbought/Oversold Conditions
Red/Blue Circles = Asset in Extreme Overbought/Oversold Conditions
Red/Blue Triangles = MACD Signals Below/Above "0"
Divergence Labels = Asset Signaling Divergence
The moving average line will turn red/blue as long as the fisher line is below/above the moving average. The shaded MA line will switch colors based on if it is moving in an up/down trend. The MA can also be used as a signal and treated similar to an oscillator. Market trending conditions will either keep the MA below/above the dashed zero line.
MACD code credited to LazyBear's MACD Leader indicator. It is used to filter out/confirm any signals such as divergences. As long as the MACD Leader line is above both the MACD line and signal lines then it'll signal with with a triangle. MACD divergences will be added at a later time.
Limited Fisher Transformwhat is Limited Fisher Transform?
This indicator is a compressed version of the Fisher transform indicator between 100 and 0 values.
what it does?
It allows us to define overbought and oversold zones by compressing the values of the "fisher transform" indicator between 0 and 100. also these zones are the same for every timeframe and trading pair, just like RSI.
how it does it?
it use this formula:
x = fisher transform values
a = average
how to use it?
its use is indistinguishable from the standard fisher. You can use it to set alarms for overbought and oversold zones. so you will be notified when a possible opportunity arises in the market.
Adaptive Fisherized CMOIntroduction
Heyo, here is another no-repaint adaptive fisherized indicator.
I added Inverse Fisher Transform, Ehlers dominant cycle analysis and smoothing to the Chande Momentum Oscillator (CMO).
Usage
The CMO is a momentum oscillator which shows the usual movement of an asset.
I recommend to use it from a lower timeframe with a higher timeframe set.
Signals
(Signal mode will come soon.)
Zero Line
CMO crosses above zero line => enter long
CMO cross below zero line => ente short
Overbought/Oversold
CMO crosses above bottom band => enter long
CMO crosses under top band => enter short
MA (Maybe this signals will vary. Then, check update notes.)
CMO crosses above MA => enter long
CMO crosses below MA => enter short
Enjoy and share your experience with it!
More to read: CMO Explanationsp
Adaptive Fisherized KSTIntroduction
Heyo guys, here is a new adaptive fisherized indicator of me.
I applied Inverse Fisher Transform, Ehlers dominant cycle analysis,
smoothing and divergence analysis on the Know Sure Thing (KST) indicator.
Moreover, the indicator doesn't repaint.
Usage
I didn't backtest the indicator, but I recommend the 5–15 min timeframe.
It can be also used on other timeframs, but I have no experience with that.
The indicator has no special filter system, so you need to find an own combo in order to build a trading system.
A trend filter like KAMA or my Adaptive Fisherized Trend Intensity Index could fit well.
If you find a good combo, let me know it in the comments pls.
Signals
Zero Line
KST crossover 0 => Enter Long
KST crossunder 0 => Enter Short
Cross
KST crossover KST MA => Enter Long
KST crossunder KST MA => Enter Short
Cross Filtered
KST crossover KST MA and KST above 0 => Enter Long
KST crossunder KST MA and KST under 0 => Enter Short
KST crossunder 0 => Exit Long
KST crossover 0 => Exit Short
More to read: KST Explanation
Enjoy and let me know your opinion!
--
Credits to
- @tista
- @blackcat1402
- @DasanC
- @cheatcountry
Adaptive Fisherized Trend Intensity Index Introduction
Here, I modified the script "Trend Intensity Index" (TII) of @everyget.
TTI was developed by M.H. Pee, who also published other trend analysis indicators like the Trend Trigger/Continuation Factor
It helps to determine how strong the current trend is.
The stronger the trend, the higher the chance the price may continue moving in the current direction.
Features
Adaptive mode (based on Ehlers dominant cycle determination) => automatically determines the length
Inverse Fisher Transform => gives sharper signals
Customizable MA Types => discover the impact of different ma bases
Hann Window and NET smoothing => state-of-the-art smoothing
Trend Visualization => shows you the up/down/side trend
Usage
This indicator here offers a perfect trend filtering system. It is capable of up/down/side trend detection.
There are a lot of trend indicators which don't respect sidetrends, which makes this indicator pretty useful.
A lot of traders use trend-following trading systems.
A trader will usually make his/her entry in the market during a strong trend and ride it, until the TII provides an indication of a reversal.
For mean-revertive trading systems, you could use TII to just trade in side trend.
A lot of mean-revertive signal emitters like Bollinger Bands or RSI work most of the times better in side trend.
Furthermore, every timeframe could be used, but higher timeframes have more impact because trends are stronger there.
Signals
Green zone (Top) => Etablished bullish trend
"Peachy" Zone (Middle) => Sidetrend/flat market
Red Zone (Bottom) => Etablished bearish trend
Enjoy guys!
(Let me know your opinions!)
--
Credits to:
@blackcat1402
@DasanC
@cheatcountry
@everget
Adaptive Fisherized ROCIntroduction
Hello community, here I applied the Inverse Fisher Transform, Ehlers dominant cycle determination and smoothing methods on a simple Rate of Change (ROC) indicator
You have a lot of options to adjust the indicator.
Usage
The rate of change is most often used to measure the change in a security's price over time.
That's why it is a momentum indicator.
When it is positive, prices are accelerating upward; when negative, downward.
It is useable on every timeframe and could be a potential filter for you your trading system.
IMO it could help you to confirm entries or find exits (e.g. you have a long open, roc goes negative, you exit).
If you use a trend-following strategy, you could maybe look out for red zones in an in uptrend or green zones in a downtrend to confirm your entry on a pullback.
Signals
ROC above 0 => confirms bullish trend
ROC below 0 => confirms bearish trend
ROC hovers near 0 => price is consolidating
Enjoy! 🚀
Gaussian Filter MACD [Loxx]Gaussian Filter MACD is a MACD that uses an 1-4 Pole Ehlers Gaussian Filter for its calculations. Compare this with Ehlers Fisher Transform.
What is Ehlers Gaussian filter?
This filter can be used for smoothing. It rejects high frequencies (fast movements) better than an EMA and has lower lag. published by John F. Ehlers in "Rocket Science For Traders". First implemented in Wealth-Lab by Dr René Koch.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve. In the case of low-pass filters, only the upper half of the curve describes the filter. The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
A gaussian filter with...
one pole is equivalent to an EMA filter.
two poles is equivalent to EMA ( EMA ())
three poles is equivalent to EMA ( EMA ( EMA ()))
and so on...
For an equivalent number of poles the lag of a Gaussian is about half the lag of a Butterworth filters: Lag = N * P / (2 * ¶2), where,
N is the number of poles, and
P is the critical period
Special initialization of filter stages ensures proper working in scans with as few bars as possible.
From Ehlers Book: "The first objective of using smoothers is to eliminate or reduce the undesired high-frequency components in the eprice data. Therefore these smoothers are called low-pass filters, and they all work by some form of averaging. Butterworth low-pass filtters can do this job, but nothing comes for free. A higher degree of filtering is necessarily accompanied by a larger amount of lag. We have come to see that is a fact of life."
References John F. Ehlers: "Rocket Science For Traders, Digital Signal Processing Applications", Chapter 15: "Infinite Impulse Response Filters"
Included
Loxx's Expanded Source Types
Signals, zero or signal crossing, signal crossing is very noisy
Alerts
Bar coloring
TheATR: Fisher Oscillator.Fisher Oscillator(FO).
The Fisher Oscillator is inspired by John Ehlers "Fisher Transform".
The oscillator highlights when prices have moved to an extreme, based on recent prices.
The FO may help in spotting turning points, in the short-medium trends of an asset, also, it helps in recognizing the asset's trends themselves, giving a picture of mkt conditions affected by less noise.
Fisher Oscillator Components.
Fisher V1 -> Main FO.
Fisher V2 -> Past Candle FO.
0-line threshold -> Directional Component.
How to read the Fisher Oscillator.
The FO is super easy to read by itself.. also, I coded some features which make it even easier to read.
It's suggestions, which we can call "Signals", come from 2 different sources, accessible thanks to the variable "Signals Type".
- 0-Line Crosses:
When the "Fisher V1" upcrosses the oscillator 0-line, the oscillator suggests a Long scenario.
When the "Fisher V1" downcrosses the oscillator 0-line, the oscillator suggests a Short scenario.
- Classic Lines Crosses:
When the "Fisher V1" upcrosses the "Fisher V2", the oscillator suggests a Long scenario.
When the "Fisher V1" downcrosses the "Fisher V2", the oscillator suggests a Short scenario.
Users will be able to recognise these Signals visually, thanks to some color customisation to the "Fisher V1" line, and thanks to the ability of the oscillator of plotting Signals.
TheATR Documentation regarding TheATR: Fisher Oscillator.
Researching and backtesting the FO, I noticed it's skill of being able to dynamically identify trend reversals with a nice degree of reliability.
Also, the FO's able to keep up with trends up to their tops/bottoms, as it's very responsive.
This makes the FO a trend-following oscillator in my personal view, because its nature of being very fast in detecting reversals will lead to many false reversals as well.
On the other face of this coin, if we look at the FO as a source for confirmations for a trend-following strategy, may be very useful.
To conclude, I would use the FO as a confirmation oscillator, in a trend-following strategy that needs to have other components.
Thanks for reading,
TheATR.
Fisher Transform of MACD w/ Quantile Bands [Loxx]Fisher Transform of MACD w/ Quantile Bands is a Fisher Transform indicator with Quantile Bands that takes as it's source a MACD. The MACD has two different source inputs for fast and slow moving averages.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What is Quantile Bands?
In statistics and the theory of probability, quantiles are cutpoints dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one less quantile than the number of groups created. Thus quartiles are the three cut points that will divide a dataset into four equal-size groups (cf. depicted example). Common quantiles have special names: for instance quartile, decile (creating 10 groups: see below for more). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.
q-Quantiles are values that partition a finite set of values into q subsets of (nearly) equal sizes. There are q − 1 of the q-quantiles, one for each integer k satisfying 0 < k < q. In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables. When the cumulative distribution function of a random variable is known, the q-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values {1/q, 2/q, …, (q − 1)/q}.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
Signals
Loxx's Expanded Source Types
35+ moving average types
Fisher Transform w/ Dynamic Zones [Loxx]What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
3 signal types
Bar coloring
Alerts
Channels fill
Loxx's Expanded Source Types
Fisher OscillatorThe indicator highlights when prices have moved to an extreme level, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
VHF Adaptive Fisher Transform [Loxx]VHF Adaptive Fisher Transform is an adaptive cycle Fisher Transform using a Vertical Horizontal Filter to calculate the volatility adjusted period.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
Zero-line and signal cross options for bar coloring
Customizable overbought/oversold thresh-holds
Alerts
Signals
CFB Adaptive Fisher Transform [Loxx]CFB Adaptive Fisher Transform is an adaptive cycle Fisher Transform using Jurik's Composite Fractal Behavior Algorithm to calculate the price-trend cycle period.
What is Composite Fractal Behavior (CFB)?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
Zero-line and signal cross options for bar coloring
Customizable overbought/oversold thresh-holds
Alerts
Signals
Phase Accumulation Adaptive Fisher Transform [Loxx]Phase Accumulation Adaptive Fisher Transform is an adaptive Fisher Transform using a modified version of Ehlers Phase Accumulation Cycle Period. This version of Phase Accumulation Cylce Period accepts as inputs: 1) total number of cycles you wish to inject into the calculation, this works as a multiplier so the higher this number, the longer the period output; 2) filter is to change the alpha value of the final smother before returning the period output.
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
Zero-line and signal cross options for bar coloring
Customizable overbought/oversold thresh-holds
Alerts
Signals
RAVI FX Fisher [Loxx]RAVI FX Fisher is a special implementation of RAVI using WMA moving averages and ATR and then normalized like Fisher Transform. If the histogram falls between the white lines, the market is too choppy to trade. This indicator is tuned for Forex.
What is RAVI?
The Range Action Verification Index (RAVI) indicator shows the percentage difference between current prices and past prices to identify market trends. It is calculated based on moving averages of different lengths.
Included:
-Change bar colors
Fisher Transform, clone of MT4 "Fisher_no_repainting" [Loxx]The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.1 The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
- Oversold and overbought regions
This is an exact clone of the "Fisher_no_repainting" MT4 indicator
Indicator Direction Table With Bullish & Bearish LabelsINDICATOR DIRECTION TABLE WITH BULLISH AND BEARISH LABELS
This is a table that shows the bullish, bearish or neutral trend for nine different popular indicators. Each indicator label will change color in real time to make you aware of each change in direction. This way you don’t have to read and analyze a bunch of different indicators constantly and you can focus on price action instead.
Look for the entire table to turn green or red before taking positions.
You can also set alerts for when the entire table of indicators is bullish or bearish.
The indicator settings allow customization of indicator lengths & values, table position and turning the indicator table on or off.
The length and other values for each indicator can be customized to suit your preferences, but by default all of them are set to the normal default settings that Tradingview supplies the indicators with. Typically 14 as the length.
The indicators used in this table are as follows:
MACD - Moving Average Convergence Divergence
Stochastic RSI - Stochastic Relative Strength Index
Vortex - Vortex Indicator
Momentum - Momentum Indicator
RSI - Relative Strength Index
PSAR - Parabolic Stop & Reverse
DMI - Directional Movement Index
MFI - Money Flow Index
Fisher - Fisher Transform Price Action
***MARKETS***
This indicator can be used as a signal on all markets, including stocks, crypto, futures and forex.
***TIMEFRAMES***
This indicator table can be used on all timeframes.
***TIPS***
Try using numerous indicators of ours on your chart so you can instantly see the bullish or bearish trend of multiple indicators in real time without having to analyze the data. Some of our favorites are our Auto Fibonacci, Directional Movement Index + Fisher Price Action, Volume Profile With Buy & Sell Pressure, Auto Support And Resistance and Money Flow Index in combination with this indicator direction table. They all have unique features to help you make better and faster trading decisions.
Directional Movement Index + Fisher Price Action With LabelsDIRECTIONAL MOVEMENT INDEX + FISHER PRICE ACTION WITH LABELS
Directional Movement Index shows buy and sell pressure.
Fisher transform shows price action trending bullish or bearish.
Caution dots notify you of conflicting trends.
***HOW TO USE***
The top lines are the fisher transform showing you the price action trend.
The bottom lines filled with color shows the DMI directional movement index.
The yellow dots at the bottom tell you if these two indicators are currently giving conflicting signals.
DMI
If the green line is above the red line and the background is colored green, there is more market buying than selling.
If the red line is above the green line and the background is colored red, there is more market selling than buying.
FISHER TRANSFORM
If the lines are painted green, the price action is trending up.
If the lines are painted red, the price action is trending down.
CAUTION DOTS
If a yellow dot shows up at the bottom of the chart, it is notifying you that the DMI and Fisher Transform are currently giving opposite signals…. so use caution.
***BULLISH/BEARISH LABEL***
There is also a label on the right side that tells you whether there is more buying or selling. This table updates in real time and changes colors so you can get an easy, quick interpretation of the current buy/sell pressure without having to look at the indicator data so you can make faster decisions on whether to enter or exit a trade.
Green means more market buying than selling.
Red means more market selling than buying.
Blue means an equal amount of market buying and selling.
If buying pressure is bullish but below the 20 level, a second label will show up in purple letting you know there is weak buying pressure so use caution.
If selling pressure is bearish but below the 20 level, a second label will show up in purple letting you know there is weak selling pressure so use caution.
There is a third label showing the current trend of the fisher transform. Green means bullish price action. Red means bearish price action.
The fourth label is orange and only shows up when the DMI and Fisher Transform are currently giving opposite signals, so make sure you use caution during those times.
***MARKETS***
This indicator can be used as a signal on all markets, including stocks, crypto, futures and forex.
***TIMEFRAMES***
This directional movement index + fisher transform indicator can be used on all timeframes.
***TIPS***
Try using numerous indicators of ours on your chart so you can instantly see the bullish or bearish trend of multiple indicators in real time without having to analyze the data. Some of our favorites are our Auto Fibonacci, Volume Profile, Momentum, Auto Support And Resistance and Money Flow Index in combination with this Directional Movement Index + Fisher Transform. They all have real time Bullish and Bearish labels as well so you can immediately understand each indicator's trend.
Ehlers Fisher Stochastic Relative Vigor Index [CC]The Fisher Stochastic Relative Vigor Index was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 101-104) and this is a many layered indicator created from his original Relative Vigor Index turned into a stochastic and then performing a Fisher transform on the results. I have included extra smoothing to provide clearer buy and sell signals as well as normal and strong buy and sell signals. As always strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Inverse Fisher Transform on Williams %RInverse Fisher Transform On Williams %R
Since Williams R indicator produces negative values, I preferred to add 50 instead of subtracting 50.
It produces values between 0.5 and -0.5.
Generates clear buy and sell signals.
Williams %R determines overbought and oversold levels.
You can see more softly.
