Average Daily Range - without open barBasic ADR-indicator that is showing the daily range on lower timeframes as well, without using the current open daily bar for calculation.
Also plots as line in a separate indicator window. Updates displayed value when hovering over the candles on the chart to see historical Numbers.
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[RS]Volume Price ChangeEXPERIMENTAL
calculates, price change * volume over a specific time window.
It reflects trend, momentum and volume participation.
It can be used to find divergences.
Predictive EMAFrom the MQL5 Indicator database, here is what the author said about the script,
"Goal of this indicator:
Given three EMA's of varying lengths, use their values
for a estimator of "where we are now" or will be in the near future.
This is a very simplistic method, better ones are probably found
in the signal processing and target tracking literature.
A Kalman filter has been known since the 1950's 1960's and there
is better still. Nevertheless this is easily programmable in the
typical environments of a retail trading application like Metatrader4.
Method:
An an exponential moving average (EMA) or a simple moving average (SMA), for that
matter, have a bandwidth parameter 'L', the effective length of the window. This
is in units of time or, really, inverse of frequency. Higher L means a lower
frequency effect.
With a parameter L, the weighted time index of the EMA and SMA is (L-1)/2. Example:
take an SMA of the previous 5 values: -5 -4 -3 -2 -1 now. The average "amount of time"
back in the past of the data which go in to the SMA is hence -3, or (L-1)/2. Same applies
for an EMA. The standard parameterization makes this correspondence between EMA
and SMA.
Therefore the idea here is to take two different EMA's, a longer, and
a shorter of lengths L1 and L2 (L2 <L1). Now take the pairs:
which defines a line.
Extrapolate to , solve for y and that is the predictive EMA estimate.
Application:
Traditional moving averages, as simple-minded linear filters, have significant group delay.
In engineering that isn't so important as nobody cares if your sound from your iPod is delayed
a few milliseconds after it is first processed. But in markets, you can't
trade on the smoothed price, only the actual noisy, market price now. Hence you
ought to estimate better.
This statistic (what math/science people call what technical analysts call an 'indicator')
may be useful as the "fast" moving average in a moving average crossover trading system.
It could also be useful for the slow moving average as well.
For instance, on a 5 minute chart:
try for the fast: (will be very wiggly, note)
LongPeriod 25.0
ShortPeriod 8.0
ExtraTimeForward 1.0
and for the slow:
LongPeriod 500.0
ShortPeriod 50.0 to 200.0
ExtraTimeForward 0.0
But often a regular MA for the slow can work as well or better, it appears from visual inspection.
Enjoy.
In chaos there is order, and in that order there is chaos and order inside again.
Then, surrounding everything, pointy haired bosses. "
I may have done it incorrectly, feel free to revise
Mikes 5 min HHLL SpotterAttempts to find higher highs and lower lows in the 5 minute window. When the light blue graph line peaks , you should investigate selling , when the light blue graph line dips you should investigate buying.
This is good for identifying oversold and over bought positions
Rolling ATR Momentum - EnhancedATR Rolling Momentum Indicator – User Manual
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🔍 Overview
The ATR Rolling Momentum Indicator is a dynamic volatility tool built on the Average True Range (ATR). It not only tracks increasing or decreasing momentum but also provides early warnings and confirmation signals for potential breakout moves. It’s especially powerful for futures and options traders looking to align with expanding price action.
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📊 Core Components
✅ ATR Delta (Rolling ATR)
- Definition: Difference between current ATR and past ATR (user-defined lookback).
- Use: Tells whether volatility is expanding (positive delta) or contracting (negative delta).
- Visual: Green line for rising momentum, red for declining.
🟣 ATR Delta Slope
- Definition: Measures acceleration in momentum.
- Use: Helps identify early signs of breakout buildup.
- Visual: Purple line. Watch for slope turning up from below.
🟡 Volatility Squeeze (Yellow Dot)
- Definition: Current ATR is significantly lower than its 20-period average.
- Use: Indicates the market is coiling—possible breakout ahead.
🔼 Momentum Start (Green Triangle)
- Definition: ATR Delta slope turns from negative to positive.
- Use: Early warning to prepare for volatility expansion.
🔷 Breakout Confirmation (Blue Label Up)
- Definition: ATR Delta exceeds its high of the last 10 candles.
- Use: Confirms volatility breakout—trade opportunity if direction aligns.
🟩/🟥 Background Color
- Green Background: Momentum rising (positive ATR delta)
- Red Background: Momentum falling (negative ATR delta)
- Yellow Tint: Active squeeze zone
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✅ How to Use It (Futures/Options Focus)
Step-by-Step:
1. Squeeze Detected (Yellow Dot) → Stay alert. Market is coiling.
2. Green Triangle Appears → Momentum is starting to rise.
3. Background Turns Green → Confirmed rising momentum.
4. Blue Label Appears → Confirmed breakout (enter trade if trend aligns).
Directional Bias:
- Use your main chart setup (price action, EMAs, trendlines, etc.) to decide direction (Call or Put, Long or Short).
- ATR Momentum only tells you how strong the move is—not which way.
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⚙️ Inputs & Settings
- ATR Period: Default 14 (core volatility measure)
- Rolling Lookback: Used to calculate delta (default 5)
- Slope Length: Used to measure acceleration (default 3)
- Squeeze Factor: Default 0.8 — lower = more sensitive squeeze detection
- Breakout Lookback: Checks ATR delta against last X bars (default 10)
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🧠 Pro Tips
- Works great when paired with EMA stacks, price structure, or breakout patterns.
- Avoid taking trades based only on squeeze or momentum—combine with chart confirmation.
- If background turns red after a breakout, it may be losing momentum—book partials or tighten stops.
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🧭 Ideal For:
- Nifty/BankNifty Futures
- Option directional trades (call/put buying)
- Index scalping and momentum swing setups
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Use this tool as your volatility compass—it won't tell you where to go, but it'll tell you when the wind is strong enough to move fast.
End of Manual
Bradley SiderographThis indicator functions as a Planetary Barometer, bringing the Bradley-Siderograph directly onto your TradingView chart. Designed for tracking the algebraic sum of planetary aspects and declination values in relation to market movements, it analyzes sidereal potential, long-term and mid-term planetary aspects, and the declination factor to provide insight into potential shifts in mass psychology. The built-in gauges act like a barometer, visually measuring the intensity and range of the components.
As Donald Bradley states in Stock Market Prediction:
" The siderograph is nothing more than a time chart showing a wavy line, which represents the algebraic total of the declination factor, the long terms, and the middle terms. It can be computed for any period—past or future—for which an ephemeris is available. Every aspect, whether long or middle term, is assigned a theoretical value of 10 at its peak. The value of the declination factor is half the algebraic sum of the given declinations of Venus and Mars, with northern declination considered positive and southern declination negative. "
How the Bradley-Siderograph Works:
The Siderograph assigns positive and negative valencies based on the transits of inner and outer planets, categorized into long-term and mid-term aspects.
Each aspect (15° orb) is given a theoretical value, with the peak set at ±10. The approach and separation phases influence the weighting of each aspect leading up to its peak.
The sign of the valency depends on the type of aspect:
Squares and oppositions are assigned negative values
Trines and sextiles are assigned positive values
Conjunctions can be either positive or negative, depending on the planetary combination
Formula Used:
The Siderograph is computed as follows:
𝑃 = 𝑋 (𝐿 + 𝐷) + 𝑀
Where:
P = Sidereal Potential (final computed value)
X = Multiplier (to weight long-term aspects)
L = Long-term aspects (10 aspect combinations)
D = Declination factor (half the sum of Venus and Mars declinations)
M = Mid-term aspects
The long-term component (L + D) can be multiplied by a chosen factor (X) to emphasize its influence relative to the mid-term aspects.
How to Use the Indicator:
Once applied, the Siderograph line overlays on the chart, using the left-side scale for reference.
The indicator provides separate plots for:
Sidereal potential
Long-term aspects
Mid-term aspects
Declination factor
Each component can be toggled on or off for deeper analysis.
Gauges "provided by @faiyaz7283 library" display the high and low range for each curve, allowing quick identification of extreme values.
The indicator also marks the yearly high and low of the current year’s sidereal potential, providing a reference for when the market is trading above or below key levels. This feature was inspired by an observation made by Bradley in his book, which I wanted to incorporate here.
Users can fully customize the indicator by:
Switching between geocentric and heliocentric views.
Adjusting the orb of planetary transits to refine aspect sensitivity.
Multiplier (to weight long-term aspects)
Explore the Bradley-Siderograph and experiment with its settings.
Main Use Case
The Siderograph can be thought of as a psychological wind sock, gauging shifts in mass sentiment in response to planetary influences. Rather than forecasting market direction outright, it serves as an early warning system, signaling when conditions may be primed for changes in collective psychology.
As Donald Bradley notes in Stock Market Prediction:
" A limitation of the siderograph is that it cannot be construed as a forecast of secular trend. In statistical terminology, 'lines of regression' fitted to the market course and to the potential should not be expected to completely agree, for reasons obvious to everybody with keen business sense or commercial training. However, the siderograph may be depended upon to reward its analyst with foreknowledge of coming conditions in general, so that the non-psychological factors may be evaluated accordingly. By this, we mean that the potential will afford one with clues as to how the mass mind will 'take' the other mechanical or governmental vicissitudes affecting high finance. The siderograph may be thought of as a principle 'symptom' in diagnosing current market circumstances and as a sounding-board for prognoses concerning further developments. "
Planned Improvement:
While Bradley did not construct the Siderograph for direct forecasting, an enhancement to this indicator would be the ability to project each curve forward in time, providing a clearer view of how upcoming planetary aspects.
This indicator is being released as open source with the hope of further refining and expanding its capabilities—particularly in developing future plots that improve visualization and analysis. Contributions and feedback are encouraged to enhance its usability and advance the study of planetary influences in market behavior.
Credits & Acknowledgments:
Inspired by Donald Bradley and his work in Stock Market Prediction: The Planetary Barometer and How to Use It.
Built using Astrolib, developed by @BarefootJoey
Built using Gauges, developed by @faiyaz7283
WIPFunctionLyaponovLibrary "WIPFunctionLyaponov"
Lyapunov exponents are mathematical measures used to describe the behavior of a system over
time. They are named after Russian mathematician Alexei Lyapunov, who first introduced the concept in the
late 19th century. The exponent is defined as the rate at which a particular function or variable changes
over time, and can be positive, negative, or zero.
Positive exponents indicate that a system tends to grow or expand over time, while negative exponents
indicate that a system tends to shrink or decay. Zero exponents indicate that the system does not change
significantly over time. Lyapunov exponents are used in various fields of science and engineering, including
physics, economics, and biology, to study the long-term behavior of complex systems.
~ generated description from vicuna13b
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To calculate the Lyapunov Exponent (LE) of a given Time Series, we need to follow these steps:
1. Firstly, you should have access to your data in some format like CSV or Excel file. If not, then you can collect it manually using tools such as stopwatches and measuring tapes.
2. Once the data is collected, clean it up by removing any outliers that may skew results. This step involves checking for inconsistencies within your dataset (e.g., extremely large or small values) and either discarding them entirely or replacing with more reasonable estimates based on surrounding values.
3. Next, you need to determine the dimension of your time series data. In most cases, this will be equal to the number of variables being measured in each observation period (e.g., temperature, humidity, wind speed).
4. Now that we have a clean dataset with known dimensions, we can calculate the LE for our Time Series using the following formula:
λ = log(||M^T * M - I||)/log(||v||)
where:
λ (Lyapunov Exponent) is the quantity that will be calculated.
||...|| denotes an Euclidean norm of a vector or matrix, which essentially means taking the square root of the sum of squares for each element in the vector/matrix.
M represents our Jacobian Matrix whose elements are given by:
J_ij = (∂fj / ∂xj) where fj is the jth variable and xj is the ith component of the initial condition vector x(t). In other words, each element in this matrix represents how much a small change in one variable affects another.
I denotes an identity matrix whose elements are all equal to 1 (or any constant value if you prefer). This term essentially acts as a baseline for comparison purposes since we want our Jacobian Matrix M^T * M to be close to it when the system is stable and far away from it when the system is unstable.
v represents an arbitrary vector whose Euclidean norm ||v|| will serve as a scaling factor in our calculation. The choice of this particular vector does not matter since we are only interested in its magnitude (i.e., length) for purposes of normalization. However, if you want to ensure that your results are accurate and consistent across different datasets or scenarios, it is recommended to use the same initial condition vector x(t) as used earlier when calculating our Jacobian Matrix M.
5. Finally, once we have calculated λ using the formula above, we can interpret its value in terms of stability/instability for our Time Series data:
- If λ < 0, then this indicates that the system is stable (i.e., nearby trajectories will converge towards each other over time).
- On the other hand, if λ > 0, then this implies that the system is unstable (i.e., nearby trajectories will diverge away from one another over time).
~ generated description from airoboros33b
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Reference:
en.wikipedia.org
www.collimator.ai
blog.abhranil.net
www.researchgate.net
physics.stackexchange.com
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This is a work in progress, it may contain errors so use with caution.
If you find flaws or suggest something new, please leave a comment bellow.
_measure_function(i)
helper function to get the name of distance function by a index (0 -> 13).\
Functions: SSD, Euclidean, Manhattan, Minkowski, Chebyshev, Correlation, Cosine, Camberra, MAE, MSE, Lorentzian, Intersection, Penrose Shape, Meehl.
Parameters:
i (int)
_test(L)
Helper function to test the output exponents state system and outputs description into a string.
Parameters:
L (float )
estimate(X, initial_distance, distance_function)
Estimate the Lyaponov Exponents for multiple series in a row matrix.
Parameters:
X (map)
initial_distance (float) : Initial distance limit.
distance_function (string) : Name of the distance function to be used, default:`ssd`.
Returns: List of Lyaponov exponents.
max(L)
Maximal Lyaponov Exponent.
Parameters:
L (float ) : List of Lyapunov exponents.
Returns: Highest exponent.
Ehlers Instantaneous Phase Dominant Cycle [CC]The Instantaneous Phase Dominant Cycle was created by John Ehlers (Stocks & Commodities V. 18:3 (16-27)) and this is one of many similar indicators that I will be publishing from Ehlers in the next few months that calculate the current dominant cycle period. The cycle period can be used in multiple ways but generally this means that if the stock is currently at a low then the current cycle period will tell you when the next lowest low will get hit or vice versa. This is also useful for using this cycle period as an input for other indicators to provide a very good adaptive length. Let me know how you wind up using these indicators in your daily trading. I have included the same buy and sell signals from my recent Hilbert Transform and so buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Ehlers Hilbert Transform [CC]The Hilbert Transform was created by John Ehlers (Stocks & Commodities V. 18:3 (16-27)) and this indicator can work pretty well as a trend confirmation. This essentially transforms the underlying price data into a soundwave and when you compare the two (blue is positive and red is negative) then it provides fairly clear buy and sell signals. Ehlers did warn in his original article that this indicator has a lag of 4 bars so you have to keep that in mind. I have found that this indicator works pretty well when you buy when the blue line goes over the red line and sell when the blue lines hits the zero line. You could also ignore the red line and buy when the blue line crosses over the zero line and sell when it crosses under. Let me know how you wind up using this indicator in your trading.
Let me know if there are any other scripts you would like to see me publish!
Trigrams based on Candle PatternThis script matches a Trigram for the current candle from its pattern Bullish/Bearish: Marubozu, Hammer, Inverted Hammer, Spinning Top.
The source for Trigram to candlestick pattern can be found online. I'm missing the reputation to add the link here.
Heaven = Bearish Marubozu
Earth = Bullish Marubozu
Thunder = Bearish Spinning Top
Water = Bullish Inverted Hammer
Mountain = Bullish Hammer
Wind = Bullish Spinning Top
Flame = Bearish Hammer
Lake = Bearish Inverted Hammer
The idea is simple. It takes the current candles pattern to match the Trigram.
Inspired by the Trigram Script from ByzantineSC
Anyways, not sure what use it is yet, but if there is anyone else out there interested in I Ching, Yin/Yang theory and trading, this is for you.
Ultimate Oscillator [Long] StrategyAfter I published Short Selling strategy with RSIofUO , I have been working for Long side strategy with same indicator.
but for Long strategy , I have used only the Ultimate Oscillator ... (Not the RSI of UO)
Logic behind this is , when UO goes below oversold level , high chance of possible reversal from there ...
Ultimate Oscialltor values , I have used are 5, 10 and 15
Signal Line 9
Above values are best/defaulted based on testing the strategy multiple symbols
BUY
when UO crossing up buyLine and close > open ( if the cross over is already done , it will wait for 3 candles to see a green bar i.e close>open )
Note when the bar color changes to orange , that means startegy is ready to take LONG position on next bar. But dont jump here , waith for the startegy take the Long Position :-)
Add
Signal appears when there is divergence (marked in yellow color ) ... strategy doesnt add the position , it is ony indicating you could add to existing OR if you missed the BUY signal you could enter here
Partial Exit
when UO crossing down partial exit level
Exit
When UO crossing down sell line
StopLoss
stop loss defaulted to 3%
Please note , I have slightly modified stop loss exit in this strategy.
Even though price hits 3% stoploss , strategy wont wind up the position ...
First , it will check if RSIofUO is above 30 , then it will hold on to the Long position.
Very reason behind this is , price is falling down and UO is going up ... That means there is bullish divergence here .. so it might turn this losing position to profitable one or will exit you with less than 3% loss.
Tested with SPY , QQQ , TSLA on 30mins to 4hrs. Though winning rate is average , net profit is exponential ...
Best working on 30 mins and 1 HR chart for QQQ
Warning
For the eductional purposes only ...
This is not a financial advise , before taking trading decission please do your own research
[RS]Shadows Of Past, Present and FutureExperimental:
session projection into the future..
Past, Present, Future
Tell me, tell me, smiling child,
What the past is like to thee ?
'An Autumn evening soft and mild
With a wind that sighs mournfully.’
Tell me, what is the present hour ?
'A green and flowery spray
Where a young bird sits gathering its power
To mount and fly away.’
And what is the future, happy one ?
'A sea beneath a cloudless sun ;
A mighty, glorious, dazzling sea
Stretching into infinity.’
by Emily Brontë
EQma - Adaptive Smoothing Based On Optimal Markets DetectionIntroduction
"You don’t put sunscreen when there is no sun, you don’t use an umbrella when there is no rain, you don’t use a kite when there is no wind, so why would you use a trend following strategy when there is no trend ?"
This is how i start my 4th paper "A New Technical Indicator For Optimal Markets Detection" where i present two new technical indicators. We talked about the first one, running equity, which aim to detect the best moment to enter trades, based on this new metric i made an adaptive moving average.
You can see the full paper here figshare.com
The Indicator
The moving average is based on exponential averaging and use a smoothing variable alpha based on the running equity metric, in order to calculate alpha the running equity is divided by the optimal equity which show the best returns possible for the conditions used. Basically the indicator work as follow :
When the running equity is close to the optimal equity it means that the price need no/little filtering since it does not contain information that need to be filtered, therefore alpha is high, however when the running equity is far from the optimal equity this mean that the price posses malign information that need to be removed.
This is why the indicator will be closer to the price when length is high :
See the full paper for an explanation on how this work.
I added various options for the indicator, one will reduce the lag by squaring alpha, thus giving for length = 14 :
The efficient option will make use of recursion to provide a more efficient indicator :
In green the efficient version, note how this option can allow a better fit with the price.
Conclusion
This is an indicator but at its core its rather a framework, if you have read the paper you'll see that the conditions are just 1 and -1 that changes with time, basically its like making a strategy with :
Condition = if buy then 1 else if sell then -1 else Precedent value of condition.
So those two indicators allow to give useful and usable information about your strategy. I hope it can be of use for anyone here, if so don't hesitate to send me what you made using the proposed indicator (and with all my indicators in general). If you are writing a paper and you think this indicator could fit in your work then let me know so i can be aware of it :)
Thanks for reading !
Acknowledgement
My papers are quite ridiculous but they still manage to get some views, some researchers don't even reach those number in so little time which is quite unfortunate but also really motivating for me, so thanks to those who take time to read them and give me some feedback :)
Kent Directional Filter🧭 Kent Directional Filter
Author: GabrielAmadeusLau
Type: Filter
📖 What It Is
The Kent Directional Filter is a directionality-sensitive smoothing tool inspired by the Kent distribution, a probability model used to describe directional and elliptical shapes on a sphere. In this context, it's repurposed for analyzing the angular trajectory of price movements and smoothing them for actionable insights.
It’s ideal for:
Detecting directional bias with probabilistic weighting
Enhancing momentum or trend-following systems
Filtering non-linear price action
🔬 How It Works
Price Angle Estimation:
Computes a rough angular shift in price using atan(src - src ) to estimate direction.
Kent Distribution Weighting:
κ (kappa) controls concentration strength (how sharply it prefers a direction).
β (beta) controls ellipticity (bias toward curved vs. linear moves).
These parameters influence how strongly the indicator favors movements at ~45° angles, simulating a directional “lens.”
Smoothing:
A Simple Moving Average (SMA) is applied over the raw directional probabilities to reduce noise and highlight the underlying trend signal.
⚙️ Inputs
Source: Price series used for angle calculation (default: close)
Smoothing Length: Window size for the moving average
Pi Divisor: Pi / 4 would be 45 degrees, you can change the 4 to 3, 2, etc.
Kappa (κ): Controls how focused the directionality is (higher = sharper filter)
Beta (β): Adds curvature sensitivity; higher values accentuate asymmetrical moves
🧠 Tips for Best Results
Use κ = 1–2 for moderate directional filtering, and β = 0.3–0.7 for smooth elliptical bias.
Combine with volume-based indicators to confirm breakout strength.
Works best in higher timeframes (1h–1D) to capture macro directional structure.
I might revisit this.
[Pandora] Laguerre Ultimate Explorations MulticatorIt's time to begin demonstrations differentiating the difference between known and actual feasibility beyond imagination... Welcome to my algorithmic twilight zone .
INTRODUCTION:
Hot off my press, I present this Laguerre multicator employing PSv6.0, originally formulated by John Ehlers for TASC - July 2025 Traders Tips. Basically I transcended Ehlers' notions of transversal filtration with an overhaul of his Laguerre design with my "what if" Pandora notions included. Striving beyond John Ehlers' original intended design. This action packed indicator is a radically revamped version of his original filter using novel techniques. My aim was to explore whether providing even more enhanced responsiveness and lesser lag is possible and how. Presented here is my mind warping results to witness.
EHLERS' LAGUERRE EXPLAINED:
First and foremost, the concept of Ehlers' Laguerre-izing method deserves a comprehensive deep dive. Ehlers' Laguerre filter design, as it functions originally, begins with his Ultimate Smoother (US) followed by a gang of four LERP (jargon for Linear intERPolation) filters. Following a myriad of cascading LERPs is a window-like FIR filter tapped into the LERP delay values to provide extra smoothness via the output.
On a side note, damping factor controlled LERP filters resemble EMAs indeed, but aren't exactly "periodic" filters that would have a period/length parameter and their subsequent calculations. I won't go into fine-grained relationship details, but EMA and LERP are indeed related in approach, being cousins of similar pedigree.
EXAMINING LAGUERRE:
I focused firstly on US initialization obstacles at Pine's bar_index==0 with nz() in abundance. The next primary notion of intrigue I mostly wondered about was, why are there four LERP elements instead of fewer or more. Why not three or why not two LERPs, etc... 1-4-6-4-1, I remember seeing those coefficients before in high pass filters.
Gathering my thoughts from that highpass knowledge base, I devised other tapped configuration modes to inspect their behavior out of curiosity. Eureka! There is actually more to Laguerre than Ehlers' mind provided, now that I had formulated additional modes. Each mode exhibits it's own lag/smoothness characteristics better than the quad LERPed version. I narrowed it down to a total of 5 modes for exploration. Mode 0 is just the raw US by itself.
ANALYZING FILTER BEHAVIORS:
Which option might be possibly superior, and how may I determine that? Fortunately, I have a custom-built analyzer allowing me to thoroughly examine transient responses across multiple periodicities simultaneously, providing remarkable visual insights.
While Ehlers has meagerly touched upon presenting general frequency responses in his books, I have excelled far beyond that. This robust filter analysis capability enables me to observe finer aspects hidden to others, ultimately leading to the deprecation of numerous existing filters. Not only this, but inventing entirely new species of filtration whether lowpass, highpass, or bandpass is already possible with a thorough comprehensive evaluation.
Revealing what's quirky with each filter and having the ability to discover what filters may be lacking in performance, is one of it's implications. I'm just going to explain this: For example US has a little too much overshoot to my liking, along with nonconformant cutoff frequency compliance with the period parameter. Perhaps Ehlers should inspect US coefficients a bit closer... I hope stating this is not received in an ill manner, as it's not my intention here.
What this technically eludes to is that UltimateSmoother can be further improved, analogous to my Laguerre alterations described above. I will also state Laguerre can indeed be reformulated to an even greater extent concerning group delay, from what I have already discussed. Another exciting time though... More investigative research is warranted.
LAGUERRE CONCLUSIONS:
After analyzing Laguerre's frequency compliance, transient responses, amplitudes, lag, symmetry across periodicities, noise rejection, and smoothness... I favor mode 3 for a multitude of reasons over the mode 4 configuration, but mostly superb smoothing with less lag, AND I also appreciated mode 1 & 2 for it's lower lag performance options.
Each mode and lag (phase shift) damping value has it's own unique characteristics at extremes, yet they demonstrate additional finesse in it's new hybrid form without adding too much more complexity. This multicator has a bunch of Laguerre filters in the overlay chart over many periodicities so you can easily witness it's differing periodic symmetries on an input signal while adjusting lag and mode.
LAGUERRE OSCILLATOR:
The oscillator is integrated into the laguerreMulti() function for the intention of posterity only. I performed no evaluation on it, only providing the code in Pine. That wasn't part of my intended exploration adventure, as I'm more TREND oriented for the time being, focusing my efforts there.
Market analysis has two primary aspects in my observations, one cyclic while the other is trending dynamics... There's endless oscillators, but my expectations for trend analysis seems a little lesser explored in my opinion, hence my laborious trend endeavors. Ehlers provided both indicator facets this time around, and I hope you find the filtration aspect more intriguing after absorption of this reading.
FUNCTION MODULES EXPLAINED:
The Ultimate Smoother is an advanced IIR lowpass smoothing filter intended to minimize noise in time series data with minimal group delay, similar to a traditional biquad filter. This calculation helps to create a smoother version of the original signal without the distortions of short-term fluctuations and with minimal lag, adjustable by period.
The Modified Laguerre Lowpass Filter (MLLF) enhances the functionality of US by introducing a Laguerre mode parameter along side the lag parameter to refine control over the amount of additional smoothing/lag applied to the signal. By tethering US with this LERPed lag mechanism, MLLF achieves an effective balance between responsiveness and smoothness, allowing for customizable lag adjustments via multiple inputs. This filter ends with selecting from a choice of weighted averages derived from a gang of up to four cascading LERP calculations, resulting with smoother representations of the data.
The Laguerre Oscillator is a momentum-like indicator derived from the output of US and a singular LERPed lowpass filter. It calculates the difference between the US data and Laguerre filter data, normalizing it by the root mean square (RMS). This quasi-normalization technique helps to assess the intensity of the momentum on any timeframe within an expected bound range centered around 0.0. When the Laguerre Oscillator is positive, it suggests that the smoothed data is trending upward, while a negative value indicates a downward trend. Adjustability is controlled with period, lag, Laguerre mode, and RMS period.
Kyber Cell's – TTM Wave AThe Kyber Cell’s Wave A – TTM Squeeze Momentum Histogram
⸻
1. Introduction
Wave A is the momentum core of the TTM Squeeze system. As the most dynamic and visually responsive of the three “waves,” it captures the ebb and flow of price strength using linear regression techniques. This histogram-based indicator is typically displayed below the chart and serves as an early warning system for potential breakouts, as well as a momentum health monitor during trades.
Built for traders who value precision, timing, and visual clarity, Kyber Cell’s Wave A re-engineers the traditional TTM Wave A with enhanced color logic, momentum sensitivity, and integration-readiness with multi-wave systems. Whether you’re scalping intraday volatility or riding longer-term swings, this tool gives you the pulse of the move — before the price fully commits.
⸻
2. Core Concept and Calculation
Wave A focuses on momentum as deviation from equilibrium, using a linear regression of the smoothed price difference between:
• The current close
• And the average of the Bollinger Band basis and a mid-range average of highs and lows
The result is a histogram that expands and contracts based on how far and how fast price is moving away from its mean. This makes it ideal for identifying when markets are building pressure (compression), releasing energy (expansion), or losing steam (divergence).
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3. Visual Output and Color Logic
The Wave A histogram dynamically changes color based on the direction and acceleration of momentum:
• Bright Cyan: Bullish momentum increasing
• Dark Blue: Bullish momentum weakening
• Bright Red: Bearish momentum increasing
• Dark Red: Bearish momentum weakening
This 4-color system helps traders instantly identify not just the direction of momentum, but the quality of that move:
• Increasing color brightness = momentum is building
• Dimming colors = momentum is fading
This is especially useful in squeeze trades — a rising Wave A during a green dot (squeeze fire) confirms breakout direction. Conversely, a fading Wave A may suggest to delay entry or prepare to exit.
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4. Ideal Use Case
Wave A is most effective when used in conjunction with a TTM Squeeze dot indicator (such as your Squeeze Pro) and optional Wave B/C overlays. The typical workflow:
1. Watch for Compression: Red, orange, or blue squeeze dots from the main chart indicator.
2. Confirm with Wave A: Enter long if Wave A flips cyan and is rising, or short if it flips bright red and is increasing.
3. Monitor the Bars: Fading bars may signal divergence, exhaustion, or false breakouts.
4. Exit Gracefully: When the histogram flips against your position and starts rising in the opposite color, it’s often a signal to consider tightening stops or taking profit.
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5. Configuration and Customization
Wave A is intentionally minimal in external configuration, focusing instead on clean visuals and fast response. However, key parameters typically include:
• Length of the linear regression (commonly set to match the Squeeze window)
• Price smoothing options (if enabled)
• Bar coloring toggle (to adapt for personal theme preferences or integration into multi-wave dashboards)
This keeps Wave A lightweight and compatible with a wide range of strategies, while remaining highly informative in real-time.
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6. Alerts and Add-ons
While Wave A itself is primarily visual, it can be enhanced with optional alert logic:
• Histogram flip from negative to positive (bullish)
• Histogram flip from positive to negative (bearish)
• Momentum peak or divergence alert (custom-coded for advanced users)
Traders often link this with a squeeze-fire signal or Wave B trend alignment to trigger more sophisticated alerts or automation workflows.
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7. Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading based on this tool involves risk, and all decisions should be made in context of broader technical and fundamental analysis, appropriate risk management, and your own trading strategy.
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Vortex strategy🧠 Overview
The Vortex Strategy is a sophisticated trend-following and volatility-based trading algorithm designed for precision entries during directional market phases. It leverages Jurik smoothing, velocity filtering, and Vortex Indicator derivatives, enhanced with advanced risk management and hourly optimization. This strategy is best suited for futures and high-volume intraday markets like the CME E-Mini S&P 500 (ES1!).
🔧 Core Features
🔄 Vortex Indicator with Velocity Filter
Uses a velocity-enhanced form of the classic Vortex Indicator (VIP and VIM) to capture directional momentum.
Smooth VMP/VMM via SS & BW and pass that through a custom velocity function using RMS-scaled filtering.
📉 Super Smoother Trend Filter
Implements Ehlers' Super Smoother Filter to define trend bias dynamically.
Acts as a directional filter for long/short entry conditions, avoiding whipsaws.
🔊 Volume Velocity Confirmation
Entry signals require increasing volume velocity, calculated using RMS scaling and normalized via bandpass filtering.
🧠 Signal Conditions
Long Entry: VIP crosses above VIM, price above smoothed trend filter, and volume velocity increasing.
Short Entry: VIM crosses above VIP, price below trend filter, and volume velocity increasing.
🛡️ Risk & Trade Management
🎯 Dynamic Stop Loss & Take Profit
SL and TP are calculated using ATR smoothed with Jurik MA.
TP multiplier is customizable by hour, optimizing profit capture per trading session.
🕐 Hourly Optimization
Define up to 3 specific trade hours, each with:
Unique risk % allocation
Unique TP multipliers
Falls back to user-defined default settings if outside optimized hours, (Asia, New York).
🪙 Position Sizing
Risk-based sizing per trade.
Contracts are calculated dynamically using user/hourly risk and stop distance.
Rounded down to whole units to comply with futures contract rules.
⚙️ Advanced Tools
Jurik Moving Average (JMA): Smoothing with minimal lag
T3 Moving Average: Tilson’s smoother with configurable alpha
Laguerre Ultimate Smoother: Custom low-pass filter for signal confirmation
Hann Window FIR Filter: Optional for fine-tuned smoothing
Butterworth High-Pass & Bandpass Filters: For noise reduction and signal isolation
Z-Score Normalization: Detect extreme moves
Modular MA Framework: Plug-and-play MA type selector for quick experiments
⚙️ User Inputs (Grouped)
📌 Strategy Settings
Trade Direction: Long, Short, or Both
User-defined base risk (%)
📌 Entry Filters
Source type (hl2 default)
Vortex Length and Velocity Length
Super Smoother length
Volume Velocity length
📌 Risk & TP Settings
ATR Length, SL Multiplier, TP Multiplier
Per-hour TP/SL & risk percentages
📌 Time Filter
Toggle & configure 3 active trade hours
✅ Execution Logic
Strategy orders are submitted using strategy entry with calculated qty and a stop trigger.
Exits are handled by strategy exit with both SL and TP conditions.
Ensures each entry aligns with direction, trend filter, and volume momentum.
📈 Ideal For
Intraday futures traders (e.g., CME ES1!)
Traders needing hour-by-hour performance tuning
Strategies requiring advanced smoothing and signal validation
Quantitative backtesters analyzing risk-adjusted performance
PSX OBV Divergence Labels (1H/4H/1D/1W, Enhanced)This script identifies and labels bullish and bearish OBV divergences on the price chart, specifically optimized for swing trading in the Pakistan Stock Exchange (PSX) but also works well across global equities, indices, and crypto.
🔍 What It Does
📈 Bullish OBV Divergence (Green “BUY” label):
Price makes a new low while OBV forms a higher low — suggesting accumulation and a potential reversal.
📉 Bearish OBV Divergence (Red “SELL” label):
Price makes a new high while OBV forms a lower high — indicating distribution and potential weakness.
All signals are confirmed on candle close and filtered for smart volume and OBV stability, helping reduce noise and false positives.
⚙️ How It Works
OBV Divergence Lookback: Scans the last N bars (default 20) for divergence patterns
Volume Spike Filter: Bullish divergences are only considered valid if volume exceeds a smoothed average × multiplier
OBV Slope Confirmation: Confirms that OBV is moving in the expected direction across recent bars before signaling
Multi-Timeframe Support: Designed for 1H, 4H, 1D, and 1W timeframes — ideal for position and swing traders
📈 Best Use Cases
✅ PSX stocks (KSE100, KMI30)
✅ Crypto, indices, or commodities where volume data is available
✅ Works best when combined with price action, support/resistance, or market structure
📎 Parameters
OBV Divergence Lookback: Length of historical window to evaluate OBV vs. price divergence
Volume Smoothing: Period for volume moving average
Volume Spike Multiplier: Threshold for volume strength (default = 1.0x)
OBV Stability Confirmation Bars: OBV must show consistent direction across this many bars before confirming divergence
🧠 Pro Tip
Use divergence signals in confluence with:
Fair Value Gaps
Market Structure Breaks (BMS)
HTF Order Blocks or key SR levels
… for much stronger trade setups.
Weekly Range ProjectionsWeekly Range Projections
Inspired by toodegrees' excellent "ICT Friday's Asian Range" indicator
This indicator is a modified and enhanced version of the original Friday's Asian Range indicator created by toodegrees. While studying their brilliant work, I realized the concept could be expanded beyond just Friday's Asian session to create a more versatile tool for weekly price projections.
What's New?
I've transformed the original concept into a fully customizable range projection tool that allows traders to:
Select Any Day of the Week - Not limited to just Fridays anymore
Define Custom Time Ranges - Set your own start and end times to capture any session (Asian, London, New York, or custom ranges)
Flexible Deviation Levels - Choose between 1-9 standard deviations instead of the fixed 5
Toggle Body/Wick Ranges - Show or hide body and wick projections independently
Updated to Pine Script v6 - Taking advantage of the latest Pine Script features
How It Works
The indicator captures the price range (body and/or wick) during your specified time window on your chosen day, then projects standard deviation levels from that range. These levels often act as significant support/resistance throughout the week.
Use Cases
Weekly Opening Range - Capture Monday's opening range for week-long projections
Session-Based Analysis - Define any session on any day for targeted analysis
Multi-Timeframe Projections - Create different instances for various time ranges
ICT Concepts - Perfect for traders following ICT methodologies with customizable ranges
Credits
Huge thanks to toodegrees for creating the original Friday's Asian Range indicator and sharing it with the community. Their clean code structure and innovative approach to range projections inspired this modification. The core logic and visual presentation style remain true to their original vision, with added flexibility for broader applications.
If you find this useful, please also check out toodegrees' original indicators - they create fantastic tools for the TradingView community!
Settings Guide
Range Settings - Choose your day and define start/end times
Range Type - Toggle body and/or wick ranges
Deviations - Select how many standard deviation levels to display
Styling - Customize colors and line styles for both range types
Alerts - Set up alerts for price crossing specific deviation levels
Remember to use this on 5-minute or 15-minute charts as intended by the original design.
Note: This indicator follows the Mozilla Public License 2.0
Student-t Weighted Acceleration & Velocity⚙️ Student-t Weighted Acceleration & Velocity
Author: © GabrielAmadeusLau
Category: Momentum, Smoothing, Divergence Detection
🔍 Overview
Student-t Weighted Acceleration & Velocity is a precision-engineered momentum indicator designed to analyze the rate of price change (velocity) and rate of change of velocity (acceleration). It leverages Student-t weighted smoothing, bandpass filtering, and divergence detection to reveal underlying momentum trends, shifts, and potential reversals with high sensitivity and low noise.
🧠 Key Features
🌀 1. Student-t Weighted Moving Average
Applies Student-t distribution weights to price data.
Controlled by:
ν (Degrees of Freedom): Lower ν increases weight on recent data, improving sensitivity to fast-moving markets.
Window Length: Sets the lookback period for weighted averaging.
🚀 2. Velocity & Acceleration Calculation
Velocity: Measures how fast price is moving over time.
Acceleration: Measures the change in velocity, revealing turning points.
Both are calculated via:
Butterworth High-pass Filter
Super Smoother Low-pass Filter
Fast Root Mean Square (RMS) normalization
Optionally smoothed using a Super Smoother EMA.
🎯 3. Signal Conditions
Strong Up: When smoothed velocity crosses above the overbought threshold and acceleration is positive.
Strong Down: When smoothed velocity crosses below the oversold threshold and acceleration is negative.
Visual cues:
Green & red triangle shapes for signals.
Colored histogram & column plots.
Optional bar coloring based on A/V behavior.
🔎 4. Divergence Detection Engine
Built-in multi-timeframe divergence system with:
Bullish/Bearish Regular Divergence
Bullish/Bearish Hidden Divergence
Customizable settings:
Pivot detection, confirmation logic, lookback limits.
Heikin Ashi mode for smoothed divergence detection.
Configurable line style, width, and color.
Visual plots of divergence lines on price chart.
⚙️ Custom Inputs
A/V Calculation Parameters:
Lookback period, filter lengths (Butterworth, Super Smoother, RMS), EMA smoothing.
Divergence Settings:
Enable/disable confirmation, show last divergence only.
Adjustable pivot period and max lookback bars.
Heikin Ashi Mode:
Option to use Heikin Ashi candles for divergence detection only (without switching chart type).
Thresholds:
Overbought/Oversold Sigma levels for strong signal detection.
🔔 Alerts Included
Strong Up Alert: Momentum and acceleration aligned bullishly.
Strong Down Alert: Momentum and acceleration aligned bearishly.
All Divergence Types:
Bullish/Bearish Regular Divergence
Bullish/Bearish Hidden Divergence
Aggregated Divergence Alerts
📌 Use Cases
Spot momentum bursts and reversals with confirmation from both velocity and acceleration.
Identify divergence-based signals for early entries/exits.
Apply across multiple timeframes or pair with other trend filters.
Gabriel's Weibull Stdv. SuperTrend📈 Gabriel's Weibull Stdv. SuperTrend
Description:
Gabriel’s Weibull Stdv. SuperTrend is a custom trend-following indicator that blends the statistical rigor of the Weibull Moving Average with the adaptive nature of the Standard Deviation-based SuperTrend.
This hybrid system dynamically adjusts its trend bands using a Weibull-weighted average, emphasizing more recent price action while allowing the curve to flexibly adapt based on two key Weibull parameters: Shape (k) and Scale (λ). The bands themselves are shifted by a multiple of standard deviation, offering a volatility-sensitive approach to trend detection.
🔧 Key Components:
Weibull Moving Average (WMA):
A smoothing function that assigns weights to historical prices using the Weibull distribution, controlled via Shape and Scale parameters.
SuperTrend Logic with Adaptive Bands:
Standard deviation is calculated over a user-defined length and scaled with a factor to set upper and lower thresholds around the WMA.
Trend Direction Detection:
The algorithm identifies bullish or bearish states based on crossover logic relative to the dynamic bands.
Visual Enhancements:
Bright green/red lines for SuperTrend direction.
Midpoint overlay and color-coded candles for clarity.
Filled zones between price and trend for visual emphasis.
⚙️ User Inputs:
Source: Price data to analyze (default: close).
Stdv. Length: Period for calculating standard deviation.
Factor: Multiplier to widen or narrow the SuperTrend bands.
Window Length: Lookback period for the Weibull MA.
Shape (k): Controls the skewness of the Weibull distribution.
Scale (λ): Stretches or compresses the weighting curve.
🔔 Alerts:
Long Entry Alert: Triggered when the trend flips bullish.
Short Entry Alert: Triggered when the trend flips bearish.
🧠 Use Cases:
Catch early reversals using custom-tailored smoothing.
Identify high-confidence trend shifts with dynamic volatility.
Combine with other confirmation indicators for enhanced entries.
Ultimate ATR ProUltimate ATR Pro - Professional Volatility Analysis Tool
Unlock Market Turning Points with Precision Volatility Analysis
Key Features
1. Advanced ATR Calculation Engine
4 MA Types: RMA (Wilder's), SMA, EMA, WMA
Customizable Period: Adjust ATR length (default: 14)
Multi-Timeframe Compatible: Works on all chart intervals
2. Smart Volatility Extremum Detection
Low Volatility Signals: Identifies ATR contraction periods
High Volatility Signals: Detects ATR expansion phases
Custom Lookback Period: Set detection window (10-500 bars)
3. Professional Divergence System
Bullish Divergence: Price ↑ while ATR ↓ (trend continuation signal)
Bearish Divergence: Price ↓ while ATR ↑ (trend acceleration signal)
Visual Connection Lines: Dotted lines highlight price-ATR relationships
4. Visual Extreme Value Lines (NEW!)
Lowest ATR Line: Customizable dotted line showing minimum volatility level
Highest ATR Line: Customizable dotted line marking maximum volatility level
Dynamic Positioning: Auto-updates with each new bar
5. Complete Customization System
Full Color Control:
Signal markers (low/high volatility)
Divergence labels
ATR line
Extreme value lines
Background highlights
Toggle Features: Enable/disable any visual element
6. Intelligent Alert System
Dual Alert Types:
Volatility Extremes (Low/High ATR)
Divergence Signals (Bullish/Bearish)
Smart Cooldown: Prevent alert fatigue with adjustable cooldown period
Visual Alert Tags: Color-coded notifications at chart top
7. Professional Dashboard
Real-time status monitoring:
Current volatility state
Cooldown timers
Extreme ATR values
Divergence detection status
Color-coded for instant recognition
How Traders Benefit
Strategic Applications
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| SIGNAL | MARKET CONDITION | TRADING IMPLICATION |
|-----------------------|---------------------------|------------------------------------|
| Low Volatility | Contraction/Consolidation | Prepare for breakout strategies |
| High Volatility | Expansion/Climax | Watch for reversals or pauses |
| Bullish Divergence | Price↑ ATR↓ | Trend continuation opportunity |
| Bearish Divergence | Price↓ ATR↑ | Trend acceleration warning |
| Lowest ATR Line Break | Volatility breakout | Confirm directional movement |
Risk Management Tools
ATR-Based Position Sizing: Use extreme values to calculate optimal trade size
Dynamic Stop Loss: Adjust stops based on current volatility regime
Volatility Filtering: Avoid trading during uncertain high-volatility periods
Setup Recommendations
Parameter Guide
pine
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length: 14 // Standard ATR period
lookback: 50 // Optimal for swing trading
cooldownPeriod: 14// Balanced alert frequency
minLineColor: #00C853 // Bright green for low volatility
maxLineColor: #FF3D00 // Bright red for high volatility
Professional Configurations
Day Trading: Lookback=20-30, Cooldown=5-10
Swing Trading: Lookback=50-100, Cooldown=10-20
Position Trading: Lookback=100-200, Cooldown=20-50
Why Choose Ultimate ATR Pro?
"Transforms complex volatility analysis into clear, actionable visual cues - the essential tool for breakout traders and risk managers alike."
Install Now To:
Spot consolidation before big moves
Identify exhaustion at trend extremes
Automate volatility-based position sizing
Receive instant alerts at critical volatility turns
Gain professional-grade insights into market dynamics
Master market rhythms with the most advanced ATR analysis tool on TradingView!
Compatibility: Works flawlessly across stocks, forex, crypto, and commodities on all timeframes.
Version: 2.0 (Enhanced with Extreme Value Lines)
Category: Volatility Analysis | Risk Management | Professional Trading
[Teyo69] T1 Wyckoff Aggressive A/D Setup📘 Overview
The T1 Wyckoff Aggressive A/D Setup is a dual-mode indicator that detects bullish accumulations and bearish distributions using core principles from the Wyckoff Method. It identifies price/volume behavior during Selling/Buying Climaxes, ARs, SOS/SOW, and triggers based on trend structure.
🔍 Features
✅ Automatic detection of:
Automatic Rally (AR)
Automatic Reaction (AR)
Sign of Strength (SOS) or Sign of Weakness (SOW)
🧠 Trend-sensitive logic with linear regression slope filters
⚙️ Configurable options for Reversal vs Trend Following mode
🎯 Smart structure timing filters using barssince() logic
🔊 Volume spike and wide-range candle detection
📊 Visual cues for bullish (green) and bearish (red) backgrounds
🛠 How to Use
Reversal Mode
Triggers early signals after a Climax + AR
Ideal for catching turning points during consolidations
Trend Following Mode
Requires Climax, AR, and confirmation (SOS or SOW)
Waits for structure confirmation before signaling
Use this when you want higher probability trades
⚙️ Configuration
Volume MA Length - Determines baseline volume to detect spikes
Wick % of Candle - Filters candles with long tails for SC/BC
Close Near Threshold - Ensures candles close near high/low
Breakout Lookback - Sets structure breakout level
Structure Threshold - Controls timing window for setups
Signal Option - Switch between Reversal or Trend Following mode
⚠️ Limitations
Doesn't confirm macro structure like full Wyckoff phase labeling (A–E)
May repaint on lower timeframes during volatile candles
Works best when combined with visual range recognition and market context
🧠 Advanced Tips
Use in confluence with:
Volume Profile ranges
Trendlines and supply/demand areas
Ideal timeframes: 8H to 1D for crypto and forex markets
Combine this with LPS/UTAD patterns for refined entries
📝 Notes
SC/AR/SOS = Bullish
BC/AR/SOW = Bearish
Trend coloring adapts background (green = rising slope, red = falling slope)
🛡️ Disclaimer
This tool is a market structure guide, not financial advice. Past behavior does not guarantee future performance. Always use proper risk management.
