Cluster Reversal Zones📌 Cluster Reversal Zones – Smart Market Turning Point Detector
📌 Category : Public (Restricted/Closed-Source) Indicator
📌 Designed for : Traders looking for high-accuracy reversal zones based on price clustering & liquidity shifts.
🔍 Overview
The Cluster Reversal Zones Indicator is an advanced market reversal detection tool that helps traders identify key turning points using a combination of price clustering, order flow analysis, and liquidity tracking. Instead of relying on static support and resistance levels, this tool dynamically adjusts to live market conditions, ensuring traders get the most accurate reversal signals possible.
📊 Core Features:
✅ Real-Time Reversal Zone Mapping – Detects high-probability market turning points using price clustering & order flow imbalance.
✅ Liquidity-Based Support/Resistance Detection – Identifies strong rejection zones based on real-time liquidity shifts.
✅ Order Flow Sensitivity for Smart Filtering – Filters out weak reversals by detecting real market participation behind price movements.
✅ Momentum Divergence for Confirmation – Aligns reversal zones with momentum divergences to increase accuracy.
✅ Adaptive Risk Management System – Adjusts risk parameters dynamically based on volatility and trend state.
🔒 Justification for Mashup
The Cluster Reversal Zones Indicator contains custom-built methodologies that extend beyond traditional support/resistance indicators:
✔ Smart Price Clustering Algorithm: Instead of plotting fixed support/resistance lines, this system analyzes historical price clustering to detect active reversal areas.
✔ Order Flow Delta & Liquidity Shift Sensitivity: The tool tracks real-time order flow data, identifying price zones with the highest accumulation or distribution levels.
✔ Momentum-Based Reversal Validation: Unlike traditional indicators, this tool requires a momentum shift confirmation before validating a potential reversal.
✔ Adaptive Reversal Filtering Mechanism: Uses a combination of historical confluence detection + live market validation to improve accuracy.
🛠️ How to Use:
• Works well for reversal traders, scalpers, and swing traders seeking precise turning points.
• Best combined with VWAP, Market Profile, and Delta Volume indicators for confirmation.
• Suitable for Forex, Indices, Commodities, Crypto, and Stock markets.
🚨 Important Note:
For educational & analytical purposes only.
Cerca negli script per "algo"
Ehlers Maclaurin Ultimate Smoother [CT]Ehlers Maclaurin Ultimate Smoother
Introduction
The Ehlers Maclaurin Ultimate Smoother is an innovative enhancement of the classic Ehlers SuperSmoother. By leveraging advanced Maclaurin series approximations, this indicator offers superior market analysis and signal generation.
The indicator combines Ehlers' Ultimate Smoother with Maclaurin series approximations to create a more efficient and accurate smoothing mechanism:
Input price data passes through the initial smoothing phase
Maclaurin series approximates trigonometric functions
Enhanced high-pass filter removes market noise
Final smoothing phase produces the output signal
Why the Maclaurin Approach?
The Maclaurin series is a special form of the Taylor series, centered around 0. It provides an efficient way to approximate complex functions using polynomial terms. In this indicator, we use the Maclaurin approach to improve the sine and cosine functions, resulting in:
Faster Calculations: By using polynomial approximations, we significantly reduce computational complexity.
Improved Stability: The approximation provides a more stable numerical basis for calculations.
Preservation of Precision: Despite the approximation, we maintain the precision needed for price smoothing.
Calculations
The indicator employs several key mathematical components:
Maclaurin Series Approximation:
sin(x) ≈ x - x³/3! + x⁵/5! - x⁷/7! + x⁹/9!
cos(x) ≈ 1 - x²/2! + x⁴/4! - x⁶/6! + x⁸/8!
Smoothing Algorithm:
Uses exponential smoothing with optimized coefficients
Implements high-pass filtering for noise reduction
Applies dynamic weighting based on market conditions
Mathematical Foundation
Utilizes Maclaurin series for trigonometric approximation
Implements Ehlers' smoothing principles
Incorporates advanced filtering techniques
Technical Advantages
Signal Processing:
Lag Reduction: Faster signal detection with less delay.
Noise Filtration: Effective elimination of high-frequency noise.
Precision Enhancement: Preservation of critical price movements.
Adaptive Processing: Dynamic response to market volatility.
Visual Enhancements:
Smart color intensity mapping.
Real-time visualization of trend strength.
Adaptive opacity based on movement significance.
Implementation
Core Configuration:
Plot Type: Choose between the original and the Maclaurin enhanced version.
Length: Default set to 30, optimal for daily timeframes.
hpLength: Default set to 10 for enhanced noise reduction.
Advanced Parameters:
The indicator offers advanced control with:
Dual processing modes (Original/Maclaurin).
Dynamic color intensity system.
Customizable smoothing parameters.
Professional Analysis Tools:
Accurate trend reversal identification.
Advanced support/resistance detection.
Superior performance in volatile markets.
Technical Specifications
Maclaurin Series Implementation:
The indicator employs a 5-term Maclaurin series approximation for both sine and cosine, ensuring efficient and accurate computation.
Performance Metrics
Improved processing efficiency.
Reduced memory utilization.
Increased signal accuracy.
Licensing & Attribution
© 2024 Mupsje aka CasaTropical
Professional Credits
Original Ultimate and SuperSmoother concept: John F. Ehlers
Maclaurin enhancement: Casa Tropical (CT)
www.mathsisfun.com
True Amplitude Envelopes (TAE)The True Envelopes indicator is an adaptation of the True Amplitude Envelope (TAE) method, based on the research paper " Improved Estimation of the Amplitude Envelope of Time Domain Signals Using True Envelope Cepstral Smoothing " by Caetano and Rodet. This indicator aims to create an asymmetric price envelope with strong predictive power, closely following the methodology outlined in the paper.
Due to the inherent limitations of Pine Script, the indicator utilizes a Kernel Density Estimator (KDE) in place of the original Cepstral Smoothing technique described in the paper. While this approach was chosen out of necessity rather than superiority, the resulting method is designed to be as effective as possible within the constraints of the Pine environment.
This indicator is ideal for traders seeking an advanced tool to analyze price dynamics, offering insights into potential price movements while working within the practical constraints of Pine Script. Whether used in dynamic mode or with a static setting, the True Envelopes indicator helps in identifying key support and resistance levels, making it a valuable asset in any trading strategy.
Key Features:
Dynamic Mode: The indicator dynamically estimates the fundamental frequency of the price, optimizing the envelope generation process in real-time to capture critical price movements.
High-Pass Filtering: Uses a high-pass filtered signal to identify and smoothly interpolate price peaks, ensuring that the envelope accurately reflects significant price changes.
Kernel Density Estimation: Although implemented as a workaround, the KDE technique allows for flexible and adaptive smoothing of the envelope, aimed at achieving results comparable to the more sophisticated methods described in the original research.
Symmetric and Asymmetric Envelopes: Provides options to select between symmetric and asymmetric envelopes, accommodating various trading strategies and market conditions.
Smoothness Control: Features adjustable smoothness settings, enabling users to balance between responsiveness and the overall smoothness of the envelopes.
The True Envelopes indicator comes with a variety of input settings that allow traders to customize the behavior of the envelopes to match their specific trading needs and market conditions. Understanding each of these settings is crucial for optimizing the indicator's performance.
Main Settings
Source: This is the data series on which the indicator is applied, typically the closing price (close). You can select other price data like open, high, low, or a custom series to base the envelope calculations.
History: This setting determines how much historical data the indicator should consider when calculating the envelopes. A value of 0 will make the indicator process all available data, while a higher value restricts it to the most recent n bars. This can be useful for reducing the computational load or focusing the analysis on recent market behavior.
Iterations: This parameter controls the number of iterations used in the envelope generation algorithm. More iterations will typically result in a smoother envelope, but can also increase computation time. The optimal number of iterations depends on the desired balance between smoothness and responsiveness.
Kernel Style: The smoothing kernel used in the Kernel Density Estimator (KDE). Available options include Sinc, Gaussian, Epanechnikov, Logistic, and Triangular. Each kernel has different properties, affecting how the smoothing is applied. For example, Gaussian provides a smooth, bell-shaped curve, while Epanechnikov is more efficient computationally with a parabolic shape.
Envelope Style: This setting determines whether the envelope should be Static or Dynamic. The Static mode applies a fixed period for the envelope, while the Dynamic mode automatically adjusts the period based on the fundamental frequency of the price data. Dynamic mode is typically more responsive to changing market conditions.
High Q: This option controls the quality factor (Q) of the high-pass filter. Enabling this will increase the Q factor, leading to a sharper cutoff and more precise isolation of high-frequency components, which can help in better identifying significant price peaks.
Symmetric: This setting allows you to choose between symmetric and asymmetric envelopes. Symmetric envelopes maintain an equal distance from the central price line on both sides, while asymmetric envelopes can adjust differently above and below the price line, which might better capture market conditions where upside and downside volatility are not equal.
Smooth Envelopes: When enabled, this setting applies additional smoothing to the envelopes. While this can reduce noise and make the envelopes more visually appealing, it may also decrease their responsiveness to sudden market changes.
Dynamic Settings
Extra Detrend: This setting toggles an additional high-pass filter that can be applied when using a long filter period. The purpose is to further detrend the data, ensuring that the envelope focuses solely on the most recent price oscillations.
Filter Period Multiplier: This multiplier adjusts the period of the high-pass filter dynamically based on the detected fundamental frequency. Increasing this multiplier will lengthen the period, making the filter less sensitive to short-term price fluctuations.
Filter Period (Min) and Filter Period (Max): These settings define the minimum and maximum bounds for the high-pass filter period. They ensure that the filter period stays within a reasonable range, preventing it from becoming too short (and overly sensitive) or too long (and too sluggish).
Envelope Period Multiplier: Similar to the filter period multiplier, this adjusts the period for the envelope generation. It scales the period dynamically to match the detected price cycles, allowing for more precise envelope adjustments.
Envelope Period (Min) and Envelope Period (Max): These settings establish the minimum and maximum bounds for the envelope period, ensuring the envelopes remain adaptive without becoming too reactive or too slow.
Static Settings
Filter Period: In static mode, this setting determines the fixed period for the high-pass filter. A shorter period will make the filter more responsive to price changes, while a longer period will smooth out more of the price data.
Envelope Period: This setting specifies the fixed period used for generating the envelopes in static mode. It directly influences how tightly or loosely the envelopes follow the price action.
TAE Smoothing: This controls the degree of smoothing applied during the TAE process in static mode. Higher smoothing values result in more gradual envelope curves, which can be useful in reducing noise but may also delay the envelope’s response to rapid price movements.
Visual Settings
Top Band Color: This setting allows you to choose the color for the upper band of the envelope. This band represents the resistance level in the price action.
Bottom Band Color: Similar to the top band color, this setting controls the color of the lower band, which represents the support level.
Center Line Color: This is the color of the central price line, often referred to as the carrier. It represents the detrended price around which the envelopes are constructed.
Line Width: This determines the thickness of the plotted lines for the top band, bottom band, and center line. Thicker lines can make the envelopes more visible, especially when overlaid on price data.
Fill Alpha: This controls the transparency level of the shaded area between the top and bottom bands. A lower alpha value will make the fill more transparent, while a higher value will make it more opaque, helping to highlight the envelope more clearly.
The envelopes generated by the True Envelopes indicator are designed to provide a more precise and responsive representation of price action compared to traditional methods like Bollinger Bands or Keltner Channels. The core idea behind this indicator is to create a price envelope that smoothly interpolates the significant peaks in price action, offering a more accurate depiction of support and resistance levels.
One of the critical aspects of this approach is the use of a high-pass filtered signal to identify these peaks. The high-pass filter serves as an effective method of detrending the price data, isolating the rapid fluctuations in price that are often lost in standard trend-following indicators. By filtering out the lower frequency components (i.e., the trend), the high-pass filter reveals the underlying oscillations in the price, which correspond to significant peaks and troughs. These oscillations are crucial for accurately constructing the envelope, as they represent the most responsive elements of the price movement.
The algorithm works by first applying the high-pass filter to the source price data, effectively detrending the series and isolating the high-frequency price changes. This filtered signal is then used to estimate the fundamental frequency of the price movement, which is essential for dynamically adjusting the envelope to current market conditions. By focusing on the peaks identified in the high-pass filtered signal, the algorithm generates an envelope that is both smooth and adaptive, closely following the most significant price changes without overfitting to transient noise.
Compared to traditional envelopes and bands, such as Bollinger Bands and Keltner Channels, the True Envelopes indicator offers several advantages. Bollinger Bands, which are based on standard deviations, and Keltner Channels, which use the average true range (ATR), both tend to react to price volatility but do not necessarily follow the peaks and troughs of the price with precision. As a result, these traditional methods can sometimes lag behind or fail to capture sudden shifts in price momentum, leading to either false signals or missed opportunities.
In contrast, the True Envelopes indicator, by using a high-pass filtered signal and a dynamic period estimation, adapts more quickly to changes in price behavior. The envelopes generated by this method are less prone to the lag that often affects standard deviation or ATR-based bands, and they provide a more accurate representation of the price's immediate oscillations. This can result in better predictive power and more reliable identification of support and resistance levels, making the True Envelopes indicator a valuable tool for traders looking for a more responsive and precise approach to market analysis.
In conclusion, the True Envelopes indicator is a powerful tool that blends advanced theoretical concepts with practical implementation, offering traders a precise and responsive way to analyze price dynamics. By adapting the True Amplitude Envelope (TAE) method through the use of a Kernel Density Estimator (KDE) and high-pass filtering, this indicator effectively captures the most significant price movements, providing a more accurate depiction of support and resistance levels compared to traditional methods like Bollinger Bands and Keltner Channels. The flexible settings allow for extensive customization, ensuring the indicator can be tailored to suit various trading strategies and market conditions.
Hybrid Adaptive Double Exponential Smoothing🙏🏻 This is HADES (Hybrid Adaptive Double Exponential Smoothing) : fully data-driven & adaptive exponential smoothing method, that gains all the necessary info directly from data in the most natural way and needs no subjective parameters & no optimizations. It gets applied to data itself -> to fit residuals & one-point forecast errors, all at O(1) algo complexity. I designed it for streaming high-frequency univariate time series data, such as medical sensor readings, orderbook data, tick charts, requests generated by a backend, etc.
The HADES method is:
fit & forecast = a + b * (1 / alpha + T - 1)
T = 0 provides in-sample fit for the current datum, and T + n provides forecast for n datapoints.
y = input time series
a = y, if no previous data exists
b = 0, if no previous data exists
otherwise:
a = alpha * y + (1 - alpha) * a
b = alpha * (a - a ) + (1 - alpha) * b
alpha = 1 / sqrt(len * 4)
len = min(ceil(exp(1 / sig)), available data)
sig = sqrt(Absolute net change in y / Sum of absolute changes in y)
For the start datapoint when both numerator and denominator are zeros, we define 0 / 0 = 1
...
The same set of operations gets applied to the data first, then to resulting fit absolute residuals to build prediction interval, and finally to absolute forecasting errors (from one-point ahead forecast) to build forecasting interval:
prediction interval = data fit +- resoduals fit * k
forecasting interval = data opf +- errors fit * k
where k = multiplier regulating intervals width, and opf = one-point forecasts calculated at each time t
...
How-to:
0) Apply to your data where it makes sense, eg. tick data;
1) Use power transform to compensate for multiplicative behavior in case it's there;
2) If you have complete data or only the data you need, like the full history of adjusted close prices: go to the next step; otherwise, guided by your goal & analysis, adjust the 'start index' setting so the calculations will start from this point;
3) Use prediction interval to detect significant deviations from the process core & make decisions according to your strategy;
4) Use one-point forecast for nowcasting;
5) Use forecasting intervals to ~ understand where the next datapoints will emerge, given the data-generating process will stay the same & lack structural breaks.
I advise k = 1 or 1.5 or 4 depending on your goal, but 1 is the most natural one.
...
Why exponential smoothing at all? Why the double one? Why adaptive? Why not Holt's method?
1) It's O(1) algo complexity & recursive nature allows it to be applied in an online fashion to high-frequency streaming data; otherwise, it makes more sense to use other methods;
2) Double exponential smoothing ensures we are taking trends into account; also, in order to model more complex time series patterns such as seasonality, we need detrended data, and this method can be used to do it;
3) The goal of adaptivity is to eliminate the window size question, in cases where it doesn't make sense to use cumulative moving typical value;
4) Holt's method creates a certain interaction between level and trend components, so its results lack symmetry and similarity with other non-recursive methods such as quantile regression or linear regression. Instead, I decided to base my work on the original double exponential smoothing method published by Rob Brown in 1956, here's the original source , it's really hard to find it online. This cool dude is considered the one who've dropped exponential smoothing to open access for the first time🤘🏻
R&D; log & explanations
If you wanna read this, you gotta know, you're taking a great responsability for this long journey, and it gonna be one hell of a trip hehe
Machine learning, apprentissage automatique, машинное обучение, digital signal processing, statistical learning, data mining, deep learning, etc., etc., etc.: all these are just artificial categories created by the local population of this wonderful world, but what really separates entities globally in the Universe is solution complexity / algorithmic complexity.
In order to get the game a lil better, it's gonna be useful to read the HTES script description first. Secondly, let me guide you through the whole R&D; process.
To discover (not to invent) the fundamental universal principle of what exponential smoothing really IS, it required the review of the whole concept, understanding that many things don't add up and don't make much sense in currently available mainstream info, and building it all from the beginning while avoiding these very basic logical & implementation flaws.
Given a complete time t, and yet, always growing time series population that can't be logically separated into subpopulations, the very first question is, 'What amount of data do we need to utilize at time t?'. Two answers: 1 and all. You can't really gain much info from 1 datum, so go for the second answer: we need the whole dataset.
So, given the sequential & incremental nature of time series, the very first and basic thing we can do on the whole dataset is to calculate a cumulative , such as cumulative moving mean or cumulative moving median.
Now we need to extend this logic to exponential smoothing, which doesn't use dataset length info directly, but all cool it can be done via a formula that quantifies the relationship between alpha (smoothing parameter) and length. The popular formulas used in mainstream are:
alpha = 1 / length
alpha = 2 / (length + 1)
The funny part starts when you realize that Cumulative Exponential Moving Averages with these 2 alpha formulas Exactly match Cumulative Moving Average and Cumulative (Linearly) Weighted Moving Average, and the same logic goes on:
alpha = 3 / (length + 1.5) , matches Cumulative Weighted Moving Average with quadratic weights, and
alpha = 4 / (length + 2) , matches Cumulative Weighted Moving Average with cubic weghts, and so on...
It all just cries in your shoulder that we need to discover another, native length->alpha formula that leverages the recursive nature of exponential smoothing, because otherwise, it doesn't make sense to use it at all, since the usual CMA and CMWA can be computed incrementally at O(1) algo complexity just as exponential smoothing.
From now on I will not mention 'cumulative' or 'linearly weighted / weighted' anymore, it's gonna be implied all the time unless stated otherwise.
What we can do is to approach the thing logically and model the response with a little help from synthetic data, a sine wave would suffice. Then we can think of relationships: Based on algo complexity from lower to higher, we have this sequence: exponential smoothing @ O(1) -> parametric statistics (mean) @ O(n) -> non-parametric statistics (50th percentile / median) @ O(n log n). Based on Initial response from slow to fast: mean -> median Based on convergence with the real expected value from slow to fast: mean (infinitely approaches it) -> median (gets it quite fast).
Based on these inputs, we need to discover such a length->alpha formula so the resulting fit will have the slowest initial response out of all 3, and have the slowest convergence with expected value out of all 3. In order to do it, we need to have some non-linear transformer in our formula (like a square root) and a couple of factors to modify the response the way we need. I ended up with this formula to meet all our requirements:
alpha = sqrt(1 / length * 2) / 2
which simplifies to:
alpha = 1 / sqrt(len * 8)
^^ as you can see on the screenshot; where the red line is median, the blue line is the mean, and the purple line is exponential smoothing with the formulas you've just seen, we've met all the requirements.
Now we just have to do the same procedure to discover the length->alpha formula but for double exponential smoothing, which models trends as well, not just level as in single exponential smoothing. For this comparison, we need to use linear regression and quantile regression instead of the mean and median.
Quantile regression requires a non-closed form solution to be solved that you can't really implement in Pine Script, but that's ok, so I made the tests using Python & sklearn:
paste.pics
^^ on this screenshot, you can see the same relationship as on the previous screenshot, but now between the responses of quantile regression & linear regression.
I followed the same logic as before for designing alpha for double exponential smoothing (also considered the initial overshoots, but that's a little detail), and ended up with this formula:
alpha = sqrt(1 / length) / 2
which simplifies to:
alpha = 1 / sqrt(len * 4)
Btw, given the pattern you see in the resulting formulas for single and double exponential smoothing, if you ever want to do triple (not Holt & Winters) exponential smoothing, you'll need len * 2 , and just len * 1 for quadruple exponential smoothing. I hope that based on this sequence, you see the hint that Maybe 4 rounds is enough.
Now since we've dealt with the length->alpha formula, we can deal with the adaptivity part.
Logically, it doesn't make sense to use a slower-than-O(1) method to generate input for an O(1) method, so it must be something universal and minimalistic: something that will help us measure consistency in our data, yet something far away from statistics and close enough to topology.
There's one perfect entity that can help us, this is fractal efficiency. The way I define fractal efficiency can be checked at the very beginning of the post, what matters is that I add a square root to the formula that is not typically added.
As explained in the description of my metric QSFS , one of the reasons for SQRT-transformed values of fractal efficiency applied in moving window mode is because they start to closely resemble normal distribution, yet with support of (0, 1). Data with this interesting property (normally distributed yet with finite support) can be modeled with the beta distribution.
Another reason is, in infinitely expanding window mode, fractal efficiency of every time series that exhibits randomness tends to infinitely approach zero, sqrt-transform kind of partially neutralizes this effect.
Yet another reason is, the square root might better reflect the dimensional inefficiency or degree of fractal complexity, since it could balance the influence of extreme deviations from the net paths.
And finally, fractals exhibit power-law scaling -> measures like length, area, or volume scale in a non-linear way. Adding a square root acknowledges this intrinsic property, while connecting our metric with the nature of fractals.
---
I suspect that, given analogies and connections with other topics in geometry, topology, fractals and most importantly positive test results of the metric, it might be that the sqrt transform is the fundamental part of fractal efficiency that should be applied by default.
Now the last part of the ballet is to convert our fractal efficiency to length value. The part about inverse proportionality is obvious: high fractal efficiency aka high consistency -> lower window size, to utilize only the last data that contain brand new information that seems to be highly reliable since we have consistency in the first place.
The non-obvious part is now we need to neutralize the side effect created by previous sqrt transform: our length values are too low, and exponentiation is the perfect candidate to fix it since translating fractal efficiency into window sizes requires something non-linear to reflect the fractal dynamics. More importantly, using exp() was the last piece that let the metric shine, any other transformations & formulas alike I've tried always had some weird results on certain data.
That exp() in the len formula was the last piece that made it all work both on synthetic and on real data.
^^ a standalone script calculating optimal dynamic window size
Omg, THAT took time to write. Comment and/or text me if you need
...
"Versace Pip-Boy, I'm a young gun coming up with no bankroll" 👻
∞
PrimeMomentum 1.1The PrimeMomentum indicator is not just an adaptation of classic tools like MA, BB, RSI, or WaveTrend. It is an innovative tool that combines several key elements and offers a unique methodology for market analysis. Its primary goal is to help traders avoid false entries and provide signals for making trading decisions.
What Makes PrimeMomentum Unique?
Integration of Multi-Timeframe Data with a Unique Signal Filtering Approach
PrimeMomentum processes data from four timeframes simultaneously, not merely to display trends but to assess the synchronization of momentum across each timeframe. This allows traders to receive signals only when all intervals confirm the direction. This approach minimizes the risk of false signals often encountered with standard tools.
PrimeMomentum analyzes the market across four timeframes:
TF1 (long-term): Displays the overall market direction.
TF2 (medium-term): Refines the current dynamics.
TF3 (short-term): Provides detailed analysis.
TF4 (very short-term): Confirms entry or exit points.
The combination of data from these timeframes allows traders to avoid frequent switching between intervals, simplifying analysis.
Innovative Reversal Logic
PrimeMomentum features a specialized algorithm for identifying trend reversals. Its uniqueness lies in the interaction between dynamic smoothing (EMA) and multi-level momentum assessment, enabling accurate identification of potential trend reversal points.
Dynamic Adaptation to Market Conditions
The indicator automatically adjusts smoothing parameters and threshold values based on market volatility. This enables it to adapt effectively to both calm and volatile markets.
Signals for entering Long or Short positions are generated only when the following conditions are met:
- Momentum shifts from negative to positive (for Long) or from positive to negative (for Short).
- Dynamic smoothing confirms the trend.
- Defined thresholds are reached.
Trend Strength Assessment
Unlike traditional indicators, PrimeMomentum evaluates not only the direction but also the strength of a trend by analyzing the relationship between momentum across each timeframe. This helps traders understand how stable the current market movement is.
The indicator analyzes price changes over a specific period, determining how much current prices deviate from previous ones. This data allows for assessing the strength of market movements.
Combination of Classic Elements with Proprietary Logic
While PrimeMomentum may utilize some widely known components like EMA, its algorithm is built on proprietary logic for evaluating market conditions. This sets it apart from standard solutions that merely display basic indicators without deeper analysis.
Added Value of PrimeMomentum
Trend Visualization with Concept Explanations
PrimeMomentum provides traders with clear visual signals, simplifying market analysis. Each element (color, line direction) is based on momentum and trend-smoothing concepts, enabling traders to make decisions quickly.
Results are displayed as color-coded lines:
- Dark violet: Long-term trend.
- Blue: Medium-term trend.
- Turquoise and light blue: Short-term trends.
If all momentum lines reach a peak and begin turning downward, it may indicate an approaching bearish trend.
If all lines reach a bottom and start turning upward, it may signal the beginning of a bullish trend.
Reversals can also serve as signals for exiting positions.
MoneyFlow
The PrimeMomentum indicator includes a visualization of MoneyFlow, allowing traders to assess capital flows within the selected timeframe. This functionality helps to analyze market trends more accurately and make well-informed decisions.
MoneyFlow Features:
Dynamic MoneyFlow Visualization:
MoneyFlow is displayed as an area that changes color based on its value:
- Green (with transparency) when MoneyFlow is above zero (positive flow).
- Red (with transparency) when MoneyFlow is below zero (negative flow).
Automatic Scaling:
MoneyFlow values automatically adjust to the chart’s scale to ensure visibility alongside the Momentum lines.
Double Smoothing:
To ensure a smoother and more representation, MoneyFlow uses double smoothing based on EMA.
Customizable Colors and Transparency:
Traders can customize the colors for positive and negative MoneyFlow and adjust the transparency level to fit their preferences.
How MoneyFlow Works:
- MoneyFlow calculations are based on the MFI (Money Flow Index), which considers both price and volume.
- MoneyFlow values are integrated into the overall PrimeMomentum chart and combined with other signals for deeper analysis.
Advantages of the New Functionality:
- Helps quickly identify capital flows into or out of the market.
- Complements Momentum analysis to provide a more comprehensive view of market conditions.
- Enhances decision-making efficiency through flexible visualization settings.
Note: MoneyFlow adapts to the selected timeframe and displays data corresponding to the current interval on the price chart.
Simplicity for Beginners and Depth for Professionals
The indicator is designed to be user-friendly for traders of all experience levels. Beginners benefit from intuitive signals, while experienced traders can leverage in-depth analysis for more complex strategies.
PrimeMomentum Usage Modes
PrimeMomentum adapts to various strategies and supports three modes:
Short-term: Recommended to use a 2H timeframe. Optimal for intraday trading with small TakeProfit levels.
Medium-term: Recommended to use a 1D timeframe for trades lasting several days.
Long-term: Use the 1W timeframe for analyzing global trends.
Support for Different Strategies
Thanks to its flexible settings and support for multiple timeframes, PrimeMomentum is suitable for both day trading and long-term analysis.
Why Is PrimeMomentum Worth Your Attention?
Unlike standard indicators, which often rely solely on basic mathematical models or publicly available components, PrimeMomentum offers a comprehensive approach to market analysis. It combines unique momentum assessment algorithms, multi-timeframe analysis, and volatility adaptation. This not only provides traders with signals but also helps them understand the underlying market processes, making it a truly innovative solution.
Disclaimer
The PrimeMomentum indicator is designed to assist traders in market analysis but does not guarantee future profitability. Its use should be combined with traders' own research and informed decision-making.
Fourier Extrapolation of PriceThis advanced algorithm leverages Fourier analysis to predict price trends by decomposing historical price data into its frequency components. Unlike traditional algorithms that often operate in lower-dimensional spaces, this method harnesses a multidimensional approach to capture intricate market behaviors. By utilizing additional dimensions, the algorithm identifies and extrapolates subtle patterns and oscillations that are typically overlooked, providing a more robust and nuanced forecast.
Ideal for traders seeking a deeper understanding of market dynamics, this tool offers an enhanced predictive capability by aligning its calculations with the complexity of real-world financial systems.
ViPlay Signal Indicator ProViPlay Signal Indicator Pro is an innovative tool designed for traders looking to enhance the accuracy and effectiveness of their trading decisions. It provides a comprehensive approach to market analysis, generating informative trend change signals based on in-depth market analysis and advanced algorithms.
By adjusting the RISK parameter, traders can customize the signal frequency to match their preferences and trading strategies. This versatile tool is suitable for various trading styles and assets, including Forex, stocks, cryptocurrencies, and commodities, helping traders make informed decisions across any market.
Key Features of the Indicator
1. The RISK parameter controls the frequency of trend change signals. The lower the value, the more frequent the signals will appear, and vice versa. This gives users flexibility in adjusting the indicator according to their strategy.
2. Signal Generation:
Modified Range Oscillator (MRO):
This is the core element of the indicator's functionality. It works in two stages:
– MRO1: This stage focuses on short-term price movements, identifying volatility peaks and potential reversal points that may indicate an upcoming trend change. It is particularly useful for traders looking for quick opportunities.
– MRO2: This stage analyzes long-term trends, filtering out minor market fluctuations. It helps traders focus on more stable movements, reducing the impact of noise.
Williams %R:
This indicator works in conjunction with MRO, confirming reversal points by analyzing market overbought or oversold conditions. This reduces the likelihood of false signals, providing additional confidence in forecasts.
The combination of MRO and Williams %R ensures that traders receive reliable and timely signals, reflecting both immediate market conditions (via MRO1) and long-term trends (via MRO2), making the tool suitable for different trading horizons.
How the components work together:
MRO performs the primary task of identifying potential trend reversal points, dividing the analysis into short-term and long-term perspectives. In the first stage (MRO1), it evaluates market volatility and predicts potential reversals. In the second stage (MRO2), it filters out random fluctuations, providing more stable signals. Williams %R acts as an additional layer of confirmation: if MRO indicates a trend reversal and Williams %R confirms it by showing overbought or oversold conditions, the signal is considered more reliable.
In an uptrend, MRO1 indicates a reversal when the price reaches a local high, while MRO2 confirms the trend's stability. Williams %R further validates this signal, reducing the likelihood of a false entry. In a downtrend, the indicator works similarly, helping traders lock in profits or open short positions.
Williams %R:
Complements MRO by assessing market conditions for overbought or oversold levels. If MRO1 indicates a reversal and Williams %R confirms it, the likelihood of a false signal is significantly reduced.
RISK parameter:
Controls the sensitivity of MRO1 to changes in volatility. At higher values, minor fluctuations are filtered out, which is useful for long-term strategies. At lower values, the signals become more frequent, making it suitable for scalping.
3. Visual Signals:
– Green Up Arrow: Marks potential upward trends.
– Red Down Arrow: Marks potential downward trends, helping traders identify possible entry points
4. How levels are calculated:
Support and resistance levels are calculated based on historical price data. Specifically:
Support 1: This is the minimum price (low) over the last 200 bars.
Support 2: This is the minimum price over the last 500 bars.
Support 3: This is the minimum price over the last 1000 bars.
Resistance 1: This is the maximum price (high) over the last 200 bars.
Resistance 2: This is the maximum price over the last 500 bars.
Resistance 3: This is the maximum price over the last 1000 bars.
The levels are not static; they update with every bar, allowing traders to see current price zones. Users can enable or disable the display of different levels through parameters.
Support and resistance levels help traders identify key points for potential price reversals. The indicator automatically calculates these levels and displays them on the chart, allowing the user to use them for making trading decisions.
How to Use ViPlay Signal Indicator Pro
1. Add the Indicator to the Chart
2. Choose a Timeframe suitable for your trading strategy. The indicator supports all timeframes.
3. Customize Parameters:
Adjust the RISK parameter to control signal frequency (1–49, default 49).
Set the Take-Profit percentage (default 7%).
Configure moving average periods.
Adjust support and resistance levels.
4. Analyze:
– Use informative buy and sell signals based on market analysis.
– Use a customizable Take-Profit level based on the entry price to determine optimal exit points.
– Utilize key support and resistance levels on the selected timeframe to identify optimal entry and exit points.
– The information in the table indicates the strength of the current trend. When the value reaches 0 or 100, the trend changes.
* Note that the indicator serves as an analytical tool and does not replace sound trading strategies.
Uniqueness and Originality
1. Innovative Algorithms
The combination of Modified Range Oscillator (MRO) and Williams %R is not a standard pairing in trading tools. The two-phase approach of MRO provides users with a comprehensive understanding of the market, offering information on both short-term fluctuations and long-term trends, while Williams %R serves as an additional filter to eliminate false signals.
2. The indicator uses mathematical functions such as True Range (TR) to analyze volatility and identify potential entry and exit points.
3. Versatility
The indicator supports all financial market assets, including Forex, stocks, cryptocurrencies, and commodities. It adapts to any trading style or strategy. Additionally, it is compatible with all timeframes, benefiting both short-term and long-term traders.
4. Ease of Use
5. All elements of the indicator can be customized or hidden according to the user’s needs, making it a convenient tool for market analysis. The indicator is compatible with all financial market assets, including Forex, stocks, cryptocurrencies, and commodities.
Important Notes
This indicator is an analytical tool and does not guarantee profits. Signals should be used alongside personal analysis and risk management strategies. Traders should note that no indicator can provide 100% accurate predictions, and there is always a possibility of false signals.
The Forexation: Super Trend SignalsOverview:
The Forexation: Super Trend Signals (STS) indicator was crafted to enhance visualization of market trends by integrating multiple technical analysis tools and adding logic to them so they color bullish, bearish, counter trends, and cautious trends. By combining standard and higher-timeframe Supertrends with dynamic EMAs and VWAP, STS offers a multi-dimensional view of market dynamics. This synergy allows traders to:
Assess Trend Strength and Alignment
Identify Momentum Shifts and Reversals
Gauge Market Sentiment through Volume-Weighted Pricing
Filter Out Market Noise for Clearer Signals
Key Features and Synergy:
1. Dual Supertrend Analysis:
Standard Supertrend:
Utilizes the Average True Range (ATR) and a multiplier factor to detect immediate market trends.
Customizable ATR Length and Factor to adjust sensitivity to market volatility.
Used as a guide to help follow the trend and identify where if price breaks through we can be reversing trend or entering a counter/cautious trend.
Higher Time Frame (HTF) Supertrend:
Integrates Supertrend data from a higher timeframe for a broader market perspective.
Smoothing applied via an EMA to reduce lag and false signals.
**Synergistic Effect:
Trend Alignment: By analyzing both standard and HTF Supertrends, STS identifies when short-term trends align with long-term trends, increasing the reliability of trend signals.
Dynamic Adjustments: Traders can adjust parameters to fine-tune the balance between responsiveness and stability.
2. Customized EMAs with Contextual Color-Coding:
Fast and Slow EMAs:
Customizable periods to match different trading strategies and timeframes.
EMAs are used to identify momentum shifts and potential reversals through crossovers.
Dynamic Color-Coding:
EMA lines change color based on their relationship with each other, the Supertrends, and VWAP.
Visual Interpretation:
Bullish Alignment: Fast EMA above Slow EMA, both above Supertrend and VWAP, signals strong upward momentum.
Bearish Alignment: Fast EMA below Slow EMA, both below Supertrend and VWAP, signals strong downward momentum.
Caution Zones: Misalignment or crossovers indicate potential reversals or consolidation.
**Synergistic Effect:
Momentum Confirmation: EMA crossovers are validated against Supertrend directions, reducing false signals.
Support and Resistance Zones: The area between EMAs acts as dynamic support/resistance, visualized through an optional fill.
3. VWAP Integration for Volume-Weighted Insights:
VWAP Analysis:
Calculates the average price weighted by volume, providing insights into institutional trading levels and market sentiment.
**Synergistic Effect:
Trend Validation: Confirms trend strength by analyzing whether price and EMAs are above or below VWAP.
Counter-Trend Detection: Identifies potential pullbacks or reversals when price interacts with VWAP against the prevailing trend of the standard and higher time frame SuperTrend.
4. Composite Signal Generation:
Color-Coded Market Conditions:
Bullish Signals (Green): Strong upward trends with alignment across standard + HTF Supertrend, EMAs, and price above VWAP.
Bearish Signals (Red): Strong downward trends with inverse alignment.
Caution State (Orange): Potential market reversals or uncertainty when indicators are misaligned. (Example: price above VWAP but under HTF SuperTrend)
Counter-Trend Conditions (Yellow): Signals possible pullbacks or consolidations when price or EMAs cross VWAP. (Example: Price is above VWAP & HTF SuperTrend but the EMAs and Standard SuperTrend are in a down trend)
**Synergistic Effect:
Enhanced Signal Accuracy: By requiring multiple confirmations across different indicators and timeframes, STS filters out noise and increases the probability of trends in the market.
Timely Alerts: Alerts are generated when critical conditions are met, keeping traders informed of significant market movements.
Underlying Concepts and Calculations:
Supertrend Algorithm:
Calculation:
Supertrend is calculated using ATR to set a dynamic trailing stop that follows price movements.
The indicator switches between bullish and bearish modes when price crosses the Supertrend line.
Customization:
ATR Length and Factor can be adjusted to make the Supertrend more or less sensitive to price changes.
In STS: Both standard and HTF Supertrends are used, with the HTF providing longer-term trend context.
Exponential Moving Averages (EMAs):
Calculation:
EMAs apply more weight to recent prices, making them more responsive than Simple Moving Averages (SMAs).
Crossovers between Fast and Slow EMAs signal potential momentum shifts.
Customization:
Periods for Fast and Slow EMAs are user-defined to suit different trading styles.
In STS: EMA behavior is analyzed in conjunction with Supertrend and VWAP to validate signals.
Volume Weighted Average Price (VWAP):
Calculation:
VWAP accumulates total dollars traded (price times volume) divided by total volume over a specific period.
Reflects the average price at which the instrument has traded throughout the day based on both price and volume.
**In STS:
VWAP serves as a dynamic support/resistance level.
Interaction with VWAP can indicate shifts in market sentiment, especially when combined with other indicators.
Justifying the Value of STS:
Holistic Market Analysis:
STS doesn't just merge indicators; it creates a cohesive system where each component validates and enhances the others.
This integrated approach offers a more reliable analysis than using individual indicators in isolation.
Customizable and Adaptive:
Traders have control over key parameters, allowing STS to be tailored to different markets and trading styles.
The ability to adjust sensitivity helps in adapting to varying market conditions.
Enhanced Decision-Making:
By providing clear visual cues and alerts, STS aids in quick interpretation of complex market data.
The indicator helps in identifying high-probability trend opportunities and managing risk effectively with trailing SuperTrend guidance.
Unique Signal Filtering:
The combination of multiple confirmations reduces the likelihood of false trend signals.
The use of higher timeframe data and volume-weighted analysis adds depth to trend assessment.
How to Use STS Effectively:
1. Configuring Settings:
Supertrend Settings:
Adjust ATR Length and Factor to set the desired sensitivity.
Select the Higher Time Frame for the HTF Supertrend to align with your trading horizon.
Set the Smoothing Period for the EMA applied to the HTF Supertrend.
EMA Settings:
Define periods for Fast and Slow EMAs based on your strategy.
Ensure the Fast EMA period is shorter than the Slow EMA for effective crossovers.
Color and Display Settings:
Customize colors for different market conditions to enhance visual clarity.
Choose whether to display the HTF Supertrend, EMA lines, EMA fill, and VWAP.
2. Interpreting Signals:
Bullish Scenario:
Supertrends indicate an uptrend.
Fast EMA crosses above Slow EMA, both trending upwards.
Price and EMAs are above VWAP.
Action: Consider long positions, using the standard Supertrend as a trailing stop.
Bearish Scenario:
Supertrends indicate a downtrend.
Fast EMA crosses below Slow EMA, both trending downwards.
Price and EMAs are below VWAP.
Action: Consider short positions. using the standard Supertrend as a trailing stop
Caution and Counter-Trend Signals:
Misalignment between indicators or color changes to orange/yellow.
Action: Exercise caution, tighten stops, or wait for clearer signals.
4. Setting Up Alerts:
Access the Alerts menu.
Configure alerts for:
Supertrend Direction Changes
EMA Crossovers
Price Crossing VWAP
Set alert actions and ensure they trigger on confirmed data by selecting "Once Per Bar Close."
Example Trading Strategies:
Trend Following:
Use STS to identify strong trends where all indicators are aligned.
Enter positions in the direction of the trend.
Use Supertrend lines as dynamic stop-loss levels.
Pullback Entries:
Wait for price to pull back to the EMA fill area or VWAP in a prevailing trend.
Look for bounce signals off these levels when supported by Supertrend direction.
Counter-Trend Opportunities:
Identify potential reversals when caution or counter-trend signals appear.
Confirm with additional analysis or indicators before taking positions against the main trend.
Disclaimer:
This indicator is intended to aid in technical analysis and should be used as part of a comprehensive trading strategy. It does not guarantee profits and carries the risk of loss. Trading financial instruments involves significant risk; please consult with a qualified financial advisor before making any investment decisions. Past performance is not indicative of future results.
Final Notes:
The Forexation: Super Trend Signals (STS) indicator represents a thoughtfully engineered tool that brings together multiple technical elements to provide a more nuanced understanding of market behavior. By leveraging the strengths of Supertrend, EMAs, and VWAP in unison, STS aims to enhance trading precision and confidence in the trends the market creates but also guide risk management levels for managing a trade and stop loss areas.
We are committed to continuous improvement and value user feedback. Please share your experiences and suggestions to help us refine the indicator further.
Happy Trading!
Volume Based Price Prediction [EdgeTerminal]This indicator combines price action, volume analysis, and trend prediction to forecast potential future price movements. The indicator creates a dynamic prediction zone with confidence bands, helping you visualize possible price trajectories based on current market conditions.
Key Features
Dynamic price prediction based on volume-weighted trend analysis
Confidence bands showing potential price ranges
Volume-based candle coloring for enhanced market insight
VWAP and Moving Average overlay
Customizable prediction parameters
Real-time updates with each new bar
Technical Components:
Volume-Price Correlation: The indicator analyzes the relationship between price movements and volume, Identifies stronger trends through volume confirmation and uses Volume-Weighted Average Price (VWAP) for price equilibrium
Trend Strength Analysis: Calculates trend direction using exponential moving averages, weights trend strength by relative volume and incorporates momentum for improved accuracy
Prediction Algorithm: combines current price, trend, and volume metrics, projects future price levels using weighted factors and generates confidence bands based on price volatility
Customizable Parameters:
Moving Average Length: Controls the smoothing period for calculations
Volume Weight Factor: Adjusts how much volume influences predictions
Prediction Periods: Number of bars to project into the future
Confidence Band Width: Controls the width of prediction bands
How to use it:
Look for strong volume confirmation with green candles, watch for prediction line slope changes, use confidence bands to gauge potential volatility and compare predictions with key support/resistance levels
Some useful tips:
Start with default settings and adjust gradually
Use wider confidence bands in volatile markets
Consider prediction lines as zones rather than exact levels
Best applications of this indicator:
Trend continuation probability assessment
Potential reversal point identification
Risk management through confidence bands
Volume-based trend confirmation
MACD Cloud with Moving Average and ATR BandsThe algorithm implements a technical analysis indicator that combines the MACD Cloud, Moving Averages (MA), and volatility bands (ATR) to provide signals on market trends and potential reversal points. It is divided into several sections:
🎨 Color Bars:
Activated based on user input.
Controls bar color display according to price relative to ATR levels and moving average (MA).
Logic:
⚫ Black: Potential bearish reversal (price above the upper ATR band).
🔵 Blue: Potential bullish reversal (price below the lower ATR band).
o
🟢 Green: Bullish trend (price between the MA and upper ATR band).
o
🔴 Red: Bearish trend (price between the lower ATR band and MA).
o
📊 MACD Bars:
Description:
The MACD Bars section is activated by default and can be modified based on user input.
🔴 Red: Indicates a bearish trend, shown when the MACD line is below the Signal line (Signal line is a moving average of MACD).
🔵 Blue: Indicates a bullish trend, shown when the MACD line is above the Signal line.
Matching colors between MACD Bars and MACD Cloud visually confirms trend direction.
MACD Cloud Logic: The MACD Cloud is based on Moving Average Convergence Divergence (MACD), a momentum indicator showing the relationship between two moving averages of price.
MACD and Signal Lines: The cloud visualizes the MACD line relative to the Signal line. If the MACD line is above the Signal line, it indicates a potential bullish trend, while below it suggests a potential bearish trend.
☁️ MA Cloud:
The MA Cloud uses three moving averages to analyze price direction:
Moving Average Relationship: Three MAs of different periods are plotted. The cloud turns green when the shorter MA is above the longer MA, indicating an uptrend, and red when below, suggesting a downtrend.
Trend Visualization: This graphical representation shows the trend direction.
📉 ATR Bands:
The ATR bands calculate overbought and oversold limits using a weighted moving average (WMA) and ATR.
Center (matr): Shows general trend; prices above suggest an uptrend, while below indicate a downtrend.
Up ATR 1: Marks the first overbought level, suggesting a potential bearish reversal if the price moves above this band.
Down ATR 1: Marks the first oversold level, suggesting a possible bullish reversal if the price moves below this band.
Up ATR 2: Extends the overbought range to an extreme, reinforcing the possibility of a bearish reversal at this level.
Down ATR 2: Extends the oversold range to an extreme, indicating a stronger bullish reversal possibility if price reaches here.
Español:
El algoritmo implementa un indicador de análisis técnico que combina la nube MACD, promedios móviles (MA) y bandas de volatilidad (ATR) para proporcionar señales sobre tendencias del mercado y posibles puntos de reversión. Se divide en varias secciones:
🎨 Barras de Color:
- Activado según la entrada del usuario.
- Controla la visualización del color de las barras según el precio en relación con los niveles de ATR y el promedio móvil (MA).
- **Lógica:**
- ⚫ **Negro**: Reversión bajista potencial (precio por encima de la banda superior ATR).
- 🔵 **Azul**: Reversión alcista potencial (precio por debajo de la banda inferior ATR).
- 🟢 **Verde**: Tendencia alcista (precio entre el MA y la banda superior ATR).
- 🔴 **Rojo**: Tendencia bajista (precio entre la banda inferior ATR y el MA).
### 📊 Barras MACD:
- **Descripción**:
- La sección de barras MACD se activa por defecto y puede modificarse según la entrada del usuario.
- 🔴 **Rojo**: Indica una tendencia bajista, cuando la línea MACD está por debajo de la línea de señal (la línea de señal es una media móvil de la MACD).
- 🔵 **Azul**: Indica una tendencia alcista, cuando la línea MACD está por encima de la línea de señal.
- La coincidencia de colores entre las barras MACD y la nube MACD confirma visualmente la dirección de la tendencia.
### 🌥️ Nube MACD:
- **Lógica de la Nube MACD**: Basada en el indicador de convergencia-divergencia de medias móviles (MACD), que muestra la relación entre dos medias móviles del precio.
- **Líneas MACD y de Señal**: La nube visualiza la relación entre la línea MACD y la línea de señal. Si la línea MACD está por encima de la de señal, indica una tendencia alcista potencial; si está por debajo, sugiere una tendencia bajista.
### ☁️ Nube MA:
- **Relación entre Medias Móviles**: Se trazan tres medias móviles de diferentes períodos. La nube se vuelve verde cuando la media más corta está por encima de la más larga, indicando una tendencia alcista, y roja cuando está por debajo, sugiriendo una tendencia bajista.
- **Visualización de Tendencias**: Proporciona una representación gráfica de la dirección de la tendencia.
### 📉 Bandas ATR:
- Las bandas ATR calculan límites de sobrecompra y sobreventa usando una media ponderada y el ATR.
- **Centro (matr)**: Muestra la tendencia general; precios por encima indican tendencia alcista y debajo, bajista.
- **Up ATR 1**: Marca el primer nivel de sobrecompra, sugiriendo una reversión bajista potencial si el precio sube por encima de esta banda.
- **Down ATR 1**: Marca el primer nivel de sobreventa, sugiriendo una reversión alcista potencial si el precio baja por debajo de esta banda.
- **Up ATR 2**: Amplía el rango de sobrecompra a un nivel extremo, reforzando la posibilidad de reversión bajista.
- **Down ATR 2**: Extiende el rango de sobreventa a un nivel extremo, sugiriendo una reversión alcista más fuerte si el precio alcanza esta banda.
Third-order moment by TonymontanovThe "Third-order moment" indicator is designed to help traders identify asymmetries and potential turning points in a financial instrument's price distribution over a specified period. By calculating the skewness of the price distribution, this indicator provides insights into the potential future movement direction of the market.
User Parameters:
- Length: This parameter defines the number of bars (or periods) used to compute the mean and third-order moment. A longer length provides a broader historical context, which may smooth out short-term volatility.
- Source: The data input for calculations, defaulting to the closing price of each bar, although users can select alternatives like open, high, low, or any custom value to suit their analysis preferences.
Operational Algorithm:
1. Mean Calculation:
- The indicator begins by calculating the arithmetic mean of the selected data source over the specified period.
2. Third-order Moment Calculation:
- A deviation from the mean is calculated for each data point. These deviations are then cubed to capture any asymmetry in the price distribution.
- The third-order moment is determined by summing these cubed deviations over the specified length and dividing by the number of periods, providing a measure of skewness.
3. Graphical Representation:
- The indicator plots the third-order moment as a column plot. The color of the columns changes based on the sign of the moment: green for positive and red for negative, suggesting bullish and bearish skewness, respectively.
- A zero line is included to help visualize transitions between positive and negative skewness clearly.
- Additionally, the background color shifts depending on whether the third-order moment is above or below zero, further highlighting the prevailing market sentiment.
The "Third-order moment" indicator is a valuable tool for traders looking to gauge the market's skewness, helping identify potential trend continuations or reversals. By understanding the dominance of positive or negative skewness, traders can make more informed decisions.
Asymmetric volatilityThe "Asymmetric Volatility" indicator is designed to visualize the differences in volatility between upward and downward price movements of a selected instrument. It operates on the principle of analyzing price movements over a specified time period, with particular focus on the symmetrical evaluation of both price rises and falls.
User Parameters:
- Length: This parameter specifies the number of bars (candles) used to calculate the average volatility. The larger the value, the longer the time period, and the smoother the volatility data will be.
- Source: This represents the input data for the indicator calculations. By default, the close value of each bar is used, but the user can choose another data source (such as open, high, low, or any custom value).
Operational Algorithm:
1. Movement Calculation:
- UpMoves: Computed as the positive difference between the current bar value and the previous bar value, if it is greater than zero.
- DownMoves: Computed as the positive difference between the previous bar value and the current bar value, if it is greater than zero.
2. Volatility Calculation:
- UpVolatility: This is the arithmetic mean of the UpMoves values over the specified period.
- DownVolatility: This is the arithmetic mean of the DownMoves values over the specified period.
3. Graphical Representation:
- The indicator displays two plots: upward and downward volatility, represented by green and red lines, respectively.
- The background color changes based on which volatility is dominant: a green background indicates that upward volatility prevails, while a red background indicates downward volatility.
The indicator allows traders to quickly assess in which direction the market is more volatile at the moment, which can be useful for making trading decisions and evaluating the current market situation.
VATICAN BANK CARTELVATICAN BANK CARTEL - Precision Signal Detection for Buyers.
The VATICAN BANK CARTEL indicator is a highly sophisticated tool designed specifically for buyers, helping them identify key market trends and generate actionable buy signals. Utilizing advanced algorithms, this indicator employs a multi-variable detection mechanism that dynamically adapts to price movements, offering real-time insights to assist in executing profitable buy trades. This indicator is optimized solely for identifying buying opportunities, ensuring that traders are equipped to make well-timed entries and exits, without signals for shorting or selling.
The recommended settings for VATICAN BANK CARTEL indicator is as follows:-
Depth Engine = 20,30,40,50,100.
Deviation Engine = 3,5,7,15,20.
Backstep Engine = 15,17,20,25.
NOTE:- But you can also use this indicator as per your setting, whichever setting gives you best results use that setting.
Key Features:
1.Adaptive Depth, Deviation, and Backstep Inputs:
The core of this indicator is its customizable Depth Engine, Deviation Engine, and Backstep Engine parameters. These inputs allow traders to adjust the sensitivity of the trend detection algorithm based on specific market conditions:
Depth: Defines how deep the indicator scans historical price data for potential trend reversals.
Deviation: Determines the minimum required price fluctuation to confirm a market movement.
Backstep: Sets the retracement level to filter false signals and maintain the accuracy of trend detection.
2. Visual Signal Representation:
The VATICAN BANK CARTEL plots highly visible labels on the chart to mark trend reversals. These labels are customizable in terms of size and transparency, ensuring clarity in various chart environments. Traders can quickly spot buying opportunities with green labels and potential square-off points with red labels, focusing exclusively on buy-side signals.
3.Real-Time Alerts:
The indicator is equipped with real-time alert conditions to notify traders of significant buy or square-off buy signals. These alerts, which are triggered based on the indicator’s internal signal logic, ensure that traders never miss a critical market movement on the buy side.
4.Custom Label Size and Transparency:
To enhance visual flexibility, the indicator allows the user to adjust label size (from small to large) and transparency levels. This feature provides a clean, adaptable view suited for different charting styles and timeframes.
How It Works:
The VATICAN BANK CARTEL analyzes the price action using a sophisticated algorithm that considers historical low and high points, dynamically detecting directional changes. When a change in market direction is detected, the indicator plots a label at the key reversal points, helping traders confirm potential entry points:
- Buy Signal (Green): Indicates potential buying opportunities based on a trend reversal.
- Square-Off Buy Signal (Red): Marks the exit point for open buy positions, allowing traders to take profits or protect capital from potential market reversals.
Note: This indicator is exclusively designed to provide signals for buyers. It does not generate sell or short signals, making it ideal for traders focused solely on identifying optimal buying opportunities in the market.
Customizable Parameters:
- Depth Engine: Fine-tunes the historical data analysis for signal generation.
- Deviation Engine: Adjusts the minimum price change required for detecting trends.
- Backstep Engine: Controls the indicator's sensitivity to retracements, minimizing false signals.
- Labels Transparency: Adjusts the opacity of the labels, ensuring they integrate seamlessly into any chart layout.
- Buy and Sell Colors: Customizable color options for buy and square-off buy labels to match your preferred color scheme.
- Label Size: Select between five different label sizes for optimal chart visibility.
Ideal For:
This indicator is ideal for both beginner and experienced traders looking to enhance their buying strategy with a highly reliable, visual, and alert-driven tool. The VATICAN BANK CARTEL adapts to various timeframes, making it suitable for day traders, swing traders, and long-term investors alike—focused exclusively on buying opportunities.
Benefits and Applications:
1.Intraday Trading: The VATICAN BANK CARTEL indicator is particularly well-suited for intraday trading, as it provides accurate and timely "buy" and "square-off buy" signals based on the current market dynamics.
2.Trend-following Strategies: Traders who employ trend-following strategies can leverage the indicator's ability to identify the overall market direction, allowing them to align their trades with the dominant trend.
3.Swing Trading: The dynamic price tracking and signal generation capabilities of the indicator can be beneficial for swing traders, who aim to capture medium-term price movements.
Security Measures:
1. The code includes a security notice at the beginning, indicating that it is subject to the Mozilla Public License 2.0, which is a reputable open-source license.
2. The code does not appear to contain any obvious security vulnerabilities or malicious content that could compromise user data or accounts.
NOTE:- This indicator is provided under the Mozilla Public License 2.0 and is subject to its terms and conditions.
Disclaimer: The usage of VATICAN BANK CARTEL indicator might or might not contribute to your trading capital(money) profits and losses and the author is not responsible for the same.
IMPORTANT NOTICE:
While the indicator aims to provide reliable "buy" and "square-off buy" signals, it is crucial to understand that the market can be influenced by unpredictable events, such as natural disasters, political unrest, changes in monetary policies, or economic crises. These unforeseen situations may occasionally lead to false signals generated by the VATICAN BANK CARTEL indicator.
Users should exercise caution and diligence when relying on the indicator's signals, as the market's behavior can be unpredictable, and external factors may impact the accuracy of the signals. It is recommended to thoroughly backtest the indicator's performance in various market conditions and to use it as one of the many tools in a comprehensive trading strategy, rather than solely relying on its output.
Ultimately, the success of the VATICAN BANK CARTEL indicator will depend on the user's ability to adapt it to their specific trading style, market conditions, and risk management approach. Continuous monitoring, analysis, and adjustment of the indicator's settings may be necessary to maintain its effectiveness in the ever-evolving financial markets.
DEVELOPER:- yashgode9
PineScript:- version:- 5
This indicator aims to enhance trading decision-making by combining DEPTH, DEVIATION, BACKSTEP with custom signal generation, offering a comprehensive tool for traders seeking clear "buy" and "square-off buy" signals on the TradingView platform.
Stationarity Test: Dickey-Fuller & KPSS [Pinescriptlabs]
📊 Kwiatkowski-Phillips-Schmidt-Shin Model Indicator & Dickey-Fuller Test 📈
This algorithm performs two statistical tests on the price spread between two selected instruments: the first from the current chart and the second determined in the settings. The purpose is to determine if their relationship is stationary. It then uses this information to generate **visual signals** based on how far the current relationship deviates from its historical average.
⚙️ Key Components:
• 🧪 ADF Test (Augmented Dickey-Fuller):** Checks if the spread between the two instruments is stationary.
• 🔬 KPSS Test (Kwiatkowski-Phillips-Schmidt-Shin):** Another test for stationarity, complementing the ADF test.
• 📏 Z-Score Calculation:** Measures how many standard deviations the current spread is from its historical mean.
• 📊 Dynamic Threshold:** Adjusts the trading signal threshold based on recent market volatility.
🔍 What the Values Mean:
The indicator displays several key values in a table:
• 📈 ADF Stationarity:** Shows "Stationary" or "Non-Stationary" based on the ADF test result.
• 📉 KPSS Stationarity:** Shows "Stationary" or "Non-Stationary" based on the KPSS test result.
• 📏 Current Z-Score:** The current Z-score of the spread.
• 🔗 Hedge Ratio:** The relationship coefficient between the two instruments.
• 🌐 Market State:** Describes the current market condition based on the Z-score.
📊 How to Interpret the Chart:
• The main chart displays the Z-score of the spread over time.
• The green and red lines represent the upper and lower thresholds for trading signals.
• The area between the **Z-score** and the thresholds is filled when a trading signal is active.
• Additional charts show the **statistics of the ADF and KPSS tests** and their critical values.
**📉 Practical Example: NVIDIA Corporation (NVDA)**
Looking at the chart for **NVIDIA Corporation (NVDA)**, we can see how the indicator applies in a real case:
1. **Main Chart (Top):**
• Shows the **historical price** of NVIDIA on a weekly scale.
• A general **uptrend** is observed with periods of consolidation.
2. **KPSS & ADF Indicator (Bottom):**
• The lower chart shows the KPSS & ADF Model indicator applied to NVIDIA.
• The **green line** represents the Z-score of the spread.
• The **green shaded areas** indicate periods where the Z-score exceeded the thresholds, generating trading signals.
3. **📋 Current Values in the Table:**
• **ADF Stationarity:** Non-Stationary
• **KPSS Stationarity:** Non-Stationary
• **Current Z-Score:** 3.45
• **Hedge Ratio:** -164.8557
• **Market State:** Moderate Volatility
4. **🔍 Interpretation:**
• A Z-score of **3.45** suggests that NVIDIA’s price is significantly above its historical average relative to **EURUSD**.
• Both the **ADF** and **KPSS** tests indicate **non-stationarity**, suggesting **caution** when using mean reversion signals at this moment.
• The market state "Moderate Volatility" indicates noticeable deviation, but not extreme.
---
**💡 Usage:**
• **When Both Tests Show Stationarity:**
• **🔼 If Z-score > Upper Threshold:** Consider **buying the first instrument** and **selling the second**.
• **🔽 If Z-score < Lower Threshold:** Consider **selling the first instrument** and **buying the second**.
• **When Either Test Shows Non-Stationarity:**
• Wait for the relationship to become **stationary** before trading.
• **Market State:**
• Use this information to evaluate **general market conditions** and adjust your trading strategy accordingly.
**Mirror Comparison of the Same as Symbol 2 🔄📊**
**📊 Table Values:**
• **Extreme Volatility Threshold:** This value is displayed when the **Z-score** exceeds **100%**, indicating **extreme deviation**. It signals a potential **trading opportunity**, as the spread has reached unusually high or low levels, suggesting a **reversion or correction** in the market.
• **Mean Reversion Threshold:** Appears when the **Z-score** begins returning towards the mean after a period of **high or extreme volatility**. It indicates that the spread between the assets is returning to normal levels, suggesting a phase of **stabilization**.
• **Neutral Zone:** Displayed when the **Z-score** is near **zero**, signaling that the spread between assets is within expected limits. This indicates a **balanced market** with no significant volatility or clear trading opportunities.
• **Low Volatility Threshold:** Appears when the **Z-score** is below **70%** of the dynamic threshold, reflecting a period of **low volatility** and market stability, indicating fewer trading opportunities.
Español:
📊 Indicador del Modelo Kwiatkowski-Phillips-Schmidt-Shin & Prueba de Dickey-Fuller 📈
Este algoritmo realiza dos pruebas estadísticas sobre la diferencia de precios (spread) entre dos instrumentos seleccionados: el primero en el gráfico actual y el segundo determinado en la configuración. El objetivo es determinar si su relación es estacionaria. Luego utiliza esta información para generar señales visuales basadas en cuánto se desvía la relación actual de su promedio histórico.
⚙️ Componentes Clave:
• 🧪 Prueba ADF (Dickey-Fuller Aumentada): Verifica si el spread entre los dos instrumentos es estacionario.
• 🔬 Prueba KPSS (Kwiatkowski-Phillips-Schmidt-Shin): Otra prueba para la estacionariedad, complementando la prueba ADF.
• 📏 Cálculo del Z-Score: Mide cuántas desviaciones estándar se encuentra el spread actual de su media histórica.
• 📊 Umbral Dinámico: Ajusta el umbral de la señal de trading en función de la volatilidad reciente del mercado.
🔍 Qué Significan los Valores:
El indicador muestra varios valores clave en una tabla:
• 📈 Estacionariedad ADF: Muestra "Estacionario" o "No Estacionario" basado en el resultado de la prueba ADF.
• 📉 Estacionariedad KPSS: Muestra "Estacionario" o "No Estacionario" basado en el resultado de la prueba KPSS.
• 📏 Z-Score Actual: El Z-score actual del spread.
• 🔗 Ratio de Cobertura: El coeficiente de relación entre los dos instrumentos.
• 🌐 Estado del Mercado: Describe la condición actual del mercado basado en el Z-score.
📊 Cómo Interpretar el Gráfico:
• El gráfico principal muestra el Z-score del spread a lo largo del tiempo.
• Las líneas verdes y rojas representan los umbrales superior e inferior para las señales de trading.
• El área entre el Z-score y los umbrales se llena cuando una señal de trading está activa.
• Los gráficos adicionales muestran las estadísticas de las pruebas ADF y KPSS y sus valores críticos.
📉 Ejemplo Práctico: NVIDIA Corporation (NVDA)
Observando el gráfico para NVIDIA Corporation (NVDA), podemos ver cómo se aplica el indicador en un caso real:
Gráfico Principal (Superior): • Muestra el precio histórico de NVIDIA en escala semanal. • Se observa una tendencia alcista general con períodos de consolidación.
Indicador KPSS & ADF (Inferior): • El gráfico inferior muestra el indicador Modelo KPSS & ADF aplicado a NVIDIA. • La línea verde representa el Z-score del spread. • Las áreas sombreadas en verde indican períodos donde el Z-score superó los umbrales, generando señales de trading.
📋 Valores Actuales en la Tabla: • Estacionariedad ADF: No Estacionario • Estacionariedad KPSS: No Estacionario • Z-Score Actual: 3.45 • Ratio de Cobertura: -164.8557 • Estado del Mercado: Volatilidad Moderada
🔍 Interpretación: • Un Z-score de 3.45 sugiere que el precio de NVIDIA está significativamente por encima de su promedio histórico en relación con EURUSD. • Tanto la prueba ADF como la KPSS indican no estacionariedad, lo que sugiere precaución al usar señales de reversión a la media en este momento. • El estado del mercado "Volatilidad Moderada" indica una desviación notable, pero no extrema.
💡 Uso:
• Cuando Ambas Pruebas Muestran Estacionariedad:
• 🔼 Si Z-score > Umbral Superior: Considera comprar el primer instrumento y vender el segundo.
• 🔽 Si Z-score < Umbral Inferior: Considera vender el primer instrumento y comprar el segundo.
• Cuando Alguna Prueba Muestra No Estacionariedad:
• Espera a que la relación se vuelva estacionaria antes de operar.
• Estado del Mercado:
• Usa esta información para evaluar las condiciones generales del mercado y ajustar tu estrategia de trading en consecuencia.
Comparativo en Espejo del Mismo Como Símbolo 2 🔄📊
📊 Valores de la Tabla:
• Umbral de Volatilidad Extrema: Este valor se muestra cuando el Z-score supera el 100%, indicando desviación extrema. Señala una posible oportunidad de trading, ya que el spread entre los activos ha alcanzado niveles inusualmente altos o bajos, lo que podría indicar una reversión o corrección en el mercado.
• Umbral de Reversión a la Media: Aparece cuando el Z-score comienza a volver hacia la media tras un período de alta o extrema volatilidad. Indica que el spread entre los activos está regresando a niveles normales, sugiriendo una fase de estabilización.
• Zona Neutral: Se muestra cuando el Z-score está cerca de cero, señalando que el spread entre activos está dentro de lo esperado. Esto indica un mercado equilibrado con ninguna volatilidad significativa ni oportunidades claras de trading.
• Umbral de Baja Volatilidad: Aparece cuando el Z-score está por debajo del 70% del umbral dinámico, reflejando un período de baja volatilidad y estabilidad del mercado, indicando menos oportunidades de trading.
[DarkTrader] Harmonic SNRThe Harmonic SNR indicator identifies key price levels (pivots) based on harmonic swings and highlights these levels as potential support and resistance zones. It works by analyzing price swings on two different timeframes simultaneously and compares the resulting pivot points to find matching levels between the timeframes.
Once the matching levels are identified, the script filters out the ones that are too close to each other based on a user-defined minimum distance. This helps in displaying only the most relevant levels on the chart. The valid levels are then sorted and plotted as lines on the chart to provide visual reference points for potential support and resistance areas. These harmonic levels can help traders identify key price zones where the market may react or reverse.
The difference between Harmonic SNR algorithm and traditional Classic Support and Resistance (SNR) lies in the methodology of identifying key price levels, the comparison of timeframes, and the way the levels are filtered and plotted.
1. Method of Calculation
Classic SNR :
Support and resistance levels are often identified based on historical price highs and lows, psychological round numbers, or areas where price has reversed multiple times in the past.
This approach is more static and often relies on manual identification or simple horizontal lines that mark historical levels.
Harmonic SNR :
This indicator uses pivot highs and lows from harmonic swings based on a defined swing period. It calculates swing points programmatically (using pivot calculations) and identifies key price levels algorithmically.
It compares pivot points across two different timeframes (intraday and a higher timeframe) to filter out important price levels, providing a more dynamic and multi-timeframe perspective.
2. Multi-Timeframe Comparison
Classic SNR :
Classic SNR typically focuses on one timeframe and doesn’t involve comparing key levels across different timeframes.
It marks levels purely based on historical price behavior within the single timeframe of analysis.
Harmonic SNR :
This algorithm compares price swings from two different timeframes (e.g., intraday and daily or higher timeframes). Only levels that appear in both timeframes are considered valid.
This makes the harmonic SNR more selective, filtering out weaker levels and highlighting only those that are significant on both timeframes.
3. Dynamic Filtering and Distance Control
Classic SNR :
Traditional SNR does not typically involve filtering based on the distance between levels. It can plot multiple levels even if they are very close to each other, which can clutter the chart.
Harmonic SNR :
This script introduces a filtering mechanism based on a user-defined minimum distance between two levels. If two levels are too close to each other (within a specified threshold), one is excluded to avoid redundancy.
This distance control adds an additional layer of precision to your SNR levels, making them more reliable by avoiding over-clustered levels.
Indicator In Use :
By using harmonic swing points, this indicator indirectly reflects harmonic price movement, which is rooted in the natural oscillation of the market. This gives your SNR levels a dynamic, harmonic-based foundation.
FloWave Oscillator [StabTrading]The FloWave Oscillator is a powerful trading tool designed to identify market trends and reversals by analysing reversal zones based on momentum and fear algorithms.
Serving as the first stage in a comprehensive trading system, it is intentionally straightforward, allowing traders to clearly see potential entry points across all charts and timeframes.
By inputting their own market sentiment, traders can customize the algorithm to align with their trading style. This flexibility helps traders navigate complex market environments with greater precision, whether they are seeking to capitalize on short-term opportunities or ride longer-term trends.
💡 Features
Reversal Zones - The FloWave Oscillator identifies key reversal zones driven by momentum and fear dynamics. Lighter green zones signal the initial stages of a potential reversal, while darker green zones indicate that a trend flip is imminent.
Trading Style Customization - The indicator allows traders to adjust their trading style with sensitivity settings ranging from Very Aggressive to Very Conservative. This flexibility lets traders tailor the indicator to their preferred time horizon—whether they seek to scalp short-term opportunities or capture long-term reversals.
🔥 Sensitivity Settings
Very Aggressive/Aggressive - These settings increase the indicator's sensitivity, generating more frequent signals, ideal for traders focused on short-term gains or those navigating choppy markets.
Neutral - Offers a balanced approach, combining both aggressive and conservative elements. It's a starting point for traders to evaluate performance before adjusting to more specific styles.
Conservative/Very Conservative - These settings reduce signal frequency, focusing on stronger, more reliable reversals. Best suited for long-term traders aiming to minimize risk and avoid premature market entries or exits.
🛠️ Usage/Practice
In the above example we’ll analysis how the indicator accurately predicts both the tops and bottoms of a market cycle.
Top of the Bull Market - The trendline initially shows two light red reversal zones, signalling a potential weakening in the upward momentum. As the trend progresses, a dark red zone emerges, confirming that a more substantial trend reversal to the downside is likely. This sequence provides an early warning, allowing traders to prepare for a possible market shift.
First Bull Signal - In the following phase, the indicator mirrors the previous action but in the opposite direction, identifying a reversal towards the upside. This behaviour demonstrates the indicator's ability to adapt to changing market conditions.
Bottom of the Bear Market - As the market continues its downward trajectory, the indicator presents two dark green reversal zones, highlighting areas where the selling pressure may be easing. These dark green zones offer three distinct opportunities to dollar-cost average (DCA) into the asset, allowing traders to build or enhance their positions during the end of the bear cycle. The indicator’s sensitivity in this phase ensures that traders can navigate the bearish market with confidence.
Continuation of Bull Cycle - In this segment, the indicator does not display any dark green reversal zones, implying that the uptrend remains robust. The absence of these zones suggests that the upward momentum is likely to continue, providing traders with another opportunity to add to their long positions. This scenario underscores the indicator’s capacity to identify when a trend is strong enough to warrant additional investment.
Potential Correction in an Uptrend - A light red zone appears, signalling a possible correction within the ongoing uptrend. However, the absence of a dark red zone indicates that the correction may be minor and that the overall trend is still upward. Traders might view this as a conservative point to take some profits off the table, managing risk while staying aligned with the broader bull market.
Bearish Signal - Eventually, a dark red reversal zone emerges, indicating that the trend has lost its upward momentum. This signal serves as a strong indicator that the uptrend may be concluding, prompting traders to consider exiting their positions or taking a more defensive stance. As the market enters a sideways phase, the trader can switch to a more aggressive trading style, seeking opportunities to scalp within the range while navigating the flat market conditions.
In this example, we demonstrate how to identify scalp trading opportunities by combining the Very Conservative and Very Aggressive settings. The key strategy is to use the Very Conservative trend to confirm the validity of reversal zones identified by the Very Aggressive setting.
The VC trend doesn’t indicate a buy reversal zone, but it shows an upward divergence. This suggests that the reversal buy zone on the VA chart is a potential entry point due to the supportive VC trend.
Multiple sell zones appear on the VA chart, but the VC trend shows a strong and steady uptrend. This suggests that we should wait for confirmation from the VC trend before considering a sell position, as the market is still moving upward strongly.
The VA chart shows several buy zones, but the VC trend indicates a strong downtrend, and no buy zone appears on the conservative setting. This suggests waiting for the next VA buy zone, confirmed by an upward divergence on the VC trend, before entering a trade.
Similar to Point 3 but in the opposite direction, the VA chart shows sell zones, but the VC trend indicates caution. The strategy would be to wait for confirmation from the VC trend before making a move.
🔶Conclusion
When used in conjunction with other indicators like the MeanRevert Matrix, the FloWave Oscillator becomes an integral part of a comprehensive trading system. It helps traders make informed decisions by providing clear signals that are aligned with the current market sentiment and broader economic trends. By following the implementation guidelines and adjusting the indicator settings as market conditions change, traders can effectively enhance their trading performance.
Smoothed SuperTrend with VWAP Confirmation [CHE] Smoothed SuperTrend with Automated Optimization and VWAP Confirmation
Overview
The "Smoothed SuperTrend with VWAP Confirmation" is an advanced technical analysis indicator designed for precise trend identification and trading signal generation. This script integrates a smoothed version of the popular SuperTrend indicator with an additional layer of confirmation using the Volume-Weighted Average Price (VWAP). The combination of these two elements offers traders a powerful tool for identifying optimal entry and exit points in the market.
Key Features
1. Smoothed SuperTrend
- Super Smoother Algorithm: The SuperTrend in this script is not just a regular one; it is enhanced by the Super Smoother filter, which reduces market noise and provides more reliable trend signals.
- Customizable Parameters: Traders can adjust three different sets of SuperTrend parameters (factor and ATR length), allowing them to tailor the indicator to their specific trading strategies.
- Automatic Optimization: The script automatically evaluates the performance of each SuperTrend parameter set and selects the one with the best cumulative performance. This selection process can be set to pick either the best or the worst performing parameter set, depending on the trader's preference.
2. VWAP Confirmation
- Precise Trend Confirmation: Once the best-performing SuperTrend is identified, the script further refines the signals by using VWAP as a confirmation tool. VWAP is a highly respected indicator in the trading community, often used to assess the true average price of an asset.
- Long and Short Signal Generation: The script generates Long and Short signals only when the price action is confirmed by both the SuperTrend and VWAP. For a Long signal, the price must be above the VWAP, and for a Short signal, it must be below the VWAP. This dual confirmation ensures higher accuracy and reduces the likelihood of false signals.
3. Visual and Informative Labels
- Signal Labels: Upon confirmation of a trend reversal by both the SuperTrend and VWAP, the script plots clear labels on the chart, indicating confirmed Long or Short signals. These labels are customizable in terms of color, text, and size, ensuring they fit seamlessly into any chart setup.
- Best Parameters Display: At the close of the most recent bar, the script displays a label that provides detailed information about the best-performing SuperTrend parameters and their cumulative performance. This feature keeps traders informed about which settings are currently most effective.
Input Customization Options
1. Super Smoother Length
- Traders can define the length of the Super Smoother filter, which is used to smooth both price data and ATR (Average True Range) values. This input allows traders to control the sensitivity of the indicator, with shorter lengths providing faster responses and longer lengths offering smoother trends.
2. SuperTrend Parameters
- Factor: For each of the three SuperTrends, traders can set a unique factor that determines the distance of the SuperTrend bands from the average price. A higher factor results in wider bands and fewer signals, while a lower factor results in narrower bands and more signals.
- ATR Length: Traders can also specify the length of the ATR used in each SuperTrend calculation. A longer ATR period captures broader market volatility, while a shorter period focuses on more immediate price movements.
3. Label Settings
- Label Colors: The script allows full customization of label colors for Long and Short signals, ensuring that they match the trader’s chart aesthetics.
- Label Text Colors and Sizes: Traders can adjust the text color and size of the labels for Long, Short, and information labels, allowing them to prioritize visibility and readability on their charts.
4. Performance Selection Mode
- Best or Worst Performer: This input allows traders to select whether the script should optimize for the best or worst performing SuperTrend parameter set. This flexibility is useful in different market conditions, where a trader might want to analyze either the strongest trend or focus on a contrarian strategy.
5. VWAP Calculation
- The script automatically recalculates the VWAP based on trend changes, ensuring that the confirmation signals are as accurate and relevant as possible to the current market context.
Important Note
This script is designed to provide more accurate trend signals and confirmations, but like all technical indicators, it should not be used in isolation. It is recommended to use this tool as part of a broader trading strategy, including proper risk management and consideration of fundamental market conditions.
Conclusion
The "Smoothed SuperTrend with VWAP Confirmation" script is an innovative trading tool that combines the strengths of the SuperTrend and VWAP indicators. By integrating smoothing techniques and automatic parameter optimization, this indicator provides traders with more accurate and reliable trend signals. The added confirmation by VWAP further enhances the precision of the entry and exit points, making it an excellent choice for traders looking to improve their technical analysis and trading outcomes. This tool is especially valuable for those who prefer customizable inputs and a systematic approach to trading, ensuring that the indicator adapts to various market conditions and individual trading styles.
Best regards
Chervolino
Price Action Smart Money Concepts [BigBeluga]THE SMART MONEY CONCEPTS Toolkit
The Smart Money Concepts [ BigBeluga ] is a comprehensive toolkit built around the principles of "smart money" behavior, which refers to the actions and strategies of institutional investors.
The Smart Money Concepts Toolkit brings together a suite of advanced indicators that are all interconnected and built around a unified concept: understanding and trading like institutional investors, or "smart money." These indicators are not just randomly chosen tools; they are features of a single overarching framework, which is why having them all in one place creates such a powerful system.
This all-in-one toolkit provides the user with a unique experience by automating most of the basic and advanced concepts on the chart, saving them time and improving their trading ideas.
Real-time market structure analysis simplifies complex trends by pinpointing key support, resistance, and breakout levels.
Advanced order block analysis leverages detailed volume data to pinpoint high-demand zones, revealing internal market sentiment and predicting potential reversals. This analysis utilizes bid/ask zones to provide supply/demand insights, empowering informed trading decisions.
Imbalance Concepts (FVG and Breakers) allows traders to identify potential market weaknesses and areas where price might be attracted to fill the gap, creating opportunities for entry and exit.
Swing failure patterns help traders identify potential entry points and rejection zones based on price swings.
Liquidity Concepts, our advanced liquidity algorithm, pinpoints high-impact events, allowing you to predict market shifts, strong price reactions, and potential stop-loss hunting zones. This gives traders an edge to make informed trading decisions based on liquidity dynamics.
🔵 FEATURES
The indicator has quite a lot of features that are provided below:
Swing market structure
Internal market structure
Mapping structure
Adjustable market structure
Strong/Weak H&L
Sweep
Volumetric Order block / Breakers
Fair Value Gaps / Breakers (multi-timeframe)
Swing Failure Patterns (multi-timeframe)
Deviation area
Equal H&L
Liquidity Prints
Buyside & Sellside
Sweep Area
Highs and Lows (multi-timeframe)
🔵 BASIC DEMONSTRATION OF ALL FEATURES
1. MARKET STRUCTURE
The preceding image illustrates the market structure functionality within the Smart Money Concepts indicator.
➤ Solid lines: These represent the core indicator's internal structure, forming the foundation for most other components. They visually depict the overall market direction and identify major reversal points marked by significant price movements (denoted as 'x').
➤ Internal Structure: These represent an alternative internal structure with the potential to drive more rapid market shifts. This is particularly relevant when a significant gap exists in the established swing structure, specifically between the Break of Structure (BOS) and the most recent Change of High/Low (CHoCH). Identifying these formations can offer opportunities for quicker entries and potential short-term reversals.
➤ Sweeps (x): These signify potential turning points in the market where liquidity is removed from the structure. This suggests a possible trend reversal and presents crucial entry opportunities. Sweeps are identified within both swing and internal structures, providing valuable insights for informed trading decisions.
➤ Mapping structure: A tool that automatically identifies and connects significant price highs and lows, creating a zig-zag pattern. It visualizes market structure, highlights trends, support/resistance levels, and potential breakouts. Helps traders quickly grasp price action patterns and make informed decisions.
➤ Color-coded candles based on market structure: These colors visually represent the underlying market structure, making it easier for traders to quickly identify trends.
➤ Extreme H&L: It visualizes market structure with extreme high and lows, which gives perspective for macro Market Structure.
2. VOLUMETRIC ORDER BLOCKS
Order blocks are specific areas on a financial chart where significant buying or selling activity has occurred. These are not just simple zones; they contain valuable information about market dynamics. Within each of these order blocks, volume bars represent the actual buying and selling activity that took place. These volume bars offer deeper insights into the strength of the order block by showing how much buying or selling power is concentrated in that specific zone.
Additionally, these order blocks can be transformed into Breaker Blocks. When an order block fails—meaning the price breaks through this zone without reversing—it becomes a breaker block. Breaker blocks are particularly useful for trading breakouts, as they signal that the market has shifted beyond a previously established zone, offering opportunities for traders to enter in the direction of the breakout.
Here's a breakdown:
➤ Bear Order Blocks (Red): These are zones where a lot of selling happened. Traders see these areas as places where sellers were strong, pushing the price down. When the price returns to these zones, it might face resistance and drop again.
➤ Bull Order Blocks (Green): These are zones where a lot of buying happened. Traders see these areas as places where buyers were strong, pushing the price up. When the price returns to these zones, it might find support and rise again.
These Order Blocks help traders identify potential areas for entering or exiting trades based on past market activity. The volume bars inside blocks show the amount of trading activity that occurred in these blocks, giving an idea of the strength of buying or selling pressure.
➤ Breaker Block: When an order block fails, meaning the price breaks through this zone without reversing, it becomes a breaker block. This indicates a significant shift in market liquidity and structure.
➤ A bearish breaker block occurs after a bullish order block fails. This typically happens when there's an upward trend, and a certain level that was expected to support the market's rise instead gives way, leading to a sharp decline. This decline indicates that sellers have overcome the buyers, absorbing liquidity and shifting the sentiment from bullish to bearish.
Conversely, a bullish breaker block is formed from the failure of a bearish order block. In a downtrend, when a level that was expected to act as resistance is breached, and the price shoots up, it signifies that buyers have taken control, overpowering the sellers.
3. FAIR VALUE GAPS:
A fair value gap (FVG), also referred to as an imbalance, is an essential concept in Smart Money trading. It highlights the supply and demand dynamics. This gap arises when there's a notable difference between the volume of buy and sell orders. FVGs can be found across various asset classes, including forex, commodities, stocks, and cryptocurrencies.
FVGs in this toolkit have the ability to detect raids of FVG which helps to identify potential price reversals.
Mitigation option helps to change from what source FVGs will be identified: Close, Wicks or AVG.
4. SWING FAILURE PATTERN (SFP):
The Swing Failure Pattern is a liquidity engineering pattern, generally used to fill large orders. This means, the SFP generally occurs when larger players push the price into liquidity pockets with the sole objective of filling their own positions.
SFP is a technical analysis tool designed to identify potential market reversals. It works by detecting instances where the price briefly breaks a previous high or low but fails to maintain that breakout, quickly reversing direction.
How it works:
Pattern Detection: The indicator scans for price movements that breach recent highs or lows.
Reversal Confirmation: If the price quickly reverses after breaching these levels, it's identified as an SFP.
➤ SFP Display:
Bullish SFP: Marked with a green symbol when price drops below a recent low before reversing upwards.
Bearish SFP: Marked with a red symbol when price rises above a recent high before reversing downwards.
➤ Deviation Levels: After detecting an SFP, the indicator projects white lines showing potential price deviation:
For bullish SFPs, the deviation line appears above the current price.
For bearish SFPs, the deviation line appears below the current price.
These deviation levels can serve as a potential trading opportunity or areas where the reversal might lose momentum.
With Volume Threshold and Filtering of SFP traders can adjust their trading style:
Volume Threshold: This setting allows traders to filter SFPs based on the volume of the reversal candle. By setting a higher volume threshold, traders can focus on potentially more significant reversals that are backed by higher trading activity.
SFP Filtering: This feature enables traders to filter SFP detection. It includes parameters such as:
5. LIQUIDITY CONCEPTS:
➤ Equal Lows (EQL) and Equal Highs (EQH) are important concepts in liquidity-based trading.
EQL: A series of two or more swing lows that occur at approximately the same price level.
EQH: A series of two or more swing highs that occur at approximately the same price level.
EQLs and EQHs are seen as potential liquidity pools where a large number of stop loss orders or limit orders may be clustered. They can be used as potential reverse points for trades.
This multi-period feature allows traders to select less and more significant EQL and EQH:
➤ Liquidity wicks:
Liquidity wicks are a minor representation of a stop-loss hunt during the retracement of a pivot point:
➤ Buy and Sell side liquidity:
The buy side liquidity represents a concentration of potential buy orders below the current price level. When price moves into this area, it can lead to increased buying pressure due to the execution of these orders.
The sell side liquidity indicates a pool of potential sell orders below the current price level. Price movement into this area can result in increased selling pressure as these orders are executed.
➤ Sweep Liquidation Zones:
Sweep Liquidation Zones are crucial for understanding market structure and potential future price movements. They provide insights into areas where significant market participants have been forced out of their positions, potentially setting up new trading opportunities.
🔵 USAGE & EXAMPLES
The core principle behind the success of this toolkit lies in identifying "confluence." This refers to the convergence of multiple trading indicators all signaling the same information at a specific point or area. By seeking such alignment, traders can significantly enhance the likelihood of successful trades.
MS + OBs
The chart illustrates a highly bullish setup where the price is rejecting from a bullish order block (POC), while simultaneously forming a bullish Swing Failure Pattern (SFP). This occurs after an internal structure change, marked by a bullish Change of Character (CHoCH). The price broke through a bearish order block, transforming it into a breaker block, further confirming the bullish momentum.
The combination of these elements—bullish order blocks, SFP, and CHoCH—creates a powerful bullish signal, reinforcing the potential for upward movement in the market.
SFP + Bear OB
This chart above displays a bearish setup with a high probability of a price move lower. The price is currently rejecting from a bear order block, which represents a key resistance area where significant selling pressure has previously occurred. A Swing Failure Pattern (SFP) has also formed near this bear order block, indicating that the price briefly attempted to break above a recent high but failed to sustain that upward movement. This failure suggests that buyers are losing momentum, and the market could be preparing for a move to the downside.
Additionally, we can toggle on the Deviation Area in the SFP section to highlight potential levels where price deviation might occur. These deviation areas represent zones where the price is likely to react after the Swing Failure Pattern:
BUY – SELL sides + EQL
The chart showcases a bullish setup with a high probability of price breaking out of the current sell-side resistance level. The market structure indicates a formation of Equal Lows (EQL), which often suggests a build-up of liquidity that could drive the price higher.
The presence of strong buy-side pressure (69%), indicated by the green zone at the bottom, reinforces this bullish outlook. This area represents a key support zone where buyers are outpacing sellers, providing the foundation for a potential upward breakout.
EQL + Bull ChoCh
This chart illustrates a potential bullish setup, driven by the formation of Equal Lows (EQL) followed by a bullish Change of Character (CHoCH). The presence of Equal Lows often signals a liquidity build-up, which can lead to a reversal when combined with additional bullish signals.
Liquidity grab + Bull ChoCh + FVGs
This chart demonstrates a strong bullish scenario, where several important market dynamics are at play. The price begins its upward momentum from Liquidity grab following a bullish Change of Character (CHoCH), signaling the transition from a bearish phase to a bullish one.
As the price progresses, it performs liquidity grabs, which serve to gather the necessary fuel for further movement. These liquidity grabs often occur before significant price surges, as large market participants exploit these areas to accumulate positions before pushing the price higher.
The chart also highlights a market imbalance area, showing strong momentum as the price moves swiftly through this zone.
In this examples, we see how the combination of multiple “smart money” tools helps identify a potential trade opportunities. This is just one of the many scenarios that traders can spot using this toolkit. Other combinations—such as order blocks, liquidity grabs, fair value gaps, and Swing Failure Patterns (SFPs)—can also be layered on top of these concepts to further refine your trading strategy.
🔵 SETTINGS
Window: limit calculation period
Swing: limit drawing function
Mapping structure: show structural points
Algorithmic Logic: (Extreme-Adjusted) Use max high/low or pivot point calculation
Algorithmic loopback: pivot point look back
Show Last: Amount of Order block to display
Hide Overlap: hide overlapping order blocks
Construction: Size of the order blocks
Fair value gaps: Choose between normal FVG or Breaker FVG
Mitigation: (close - wick - avg) point to mitigate the order block/imbalance
SFP lookback: find a higher / lower point to improve accuracy
Threshold: remove less relevant SFP
Equal H&L: (short-mid-long term) display longer term
Liquidity Prints: Shows wicks of candles where liquidity was grabbed
Sweep Area: Identify Sweep Liquidation areas
By combining these indicators in one toolkit, traders are equipped with a comprehensive suite of tools that address every angle of the Smart Money Concept. Instead of relying on disparate tools spread across various platforms, having them integrated into a single, cohesive system allows traders to easily see confluence and make more informed trading decisions.
Trend Strength | Flux Charts💎 GENERAL OVERVIEW
Introducing the new Trend Strength indicator! Latest trends and their strengths play an important role for traders. This indicator aims to make trend and strength detection much easier by coloring candlesticks based on the current strength of trend. More info about the process in the "How Does It Work" section.
Features of the new Trend Strength Indicator :
3 Trend Detection Algorithms Combined (RSI, Supertrend & EMA Cross)
Fully Customizable Algorithm
Strength Labels
Customizable Colors For Bullish, Neutral & Bearish Trends
📌 HOW DOES IT WORK ?
This indicator uses three different methods of trend detection and combines them all into one value. First, the RSI is calculated. The RSI outputs a value between 0 & 100, which this indicator maps into -100 <-> 100. Let this value be named RSI. Then, the Supertrend is calculated. Let SPR be -1 if the calculated Supertrend is bearish, and 1 if it's bullish. After that, latest EMA Cross is calculated. This is done by checking the distance between the two EMA's adjusted by the user. Let EMADiff = EMA1 - EMA2. Then EMADiff is mapped from -ATR * 2 <-> ATR * 2 to -100 <-> 100.
Then a Total Strength (TS) is calculated by given formula : RSI * 0.5 + SPR * 0.2 + EMADiff * 0.3
The TS value is between -100 <-> 100, -100 being fully bearish, 0 being true neutral and 100 being fully bullish.
Then the Total Strength is converted into a color adjusted by the user. The candlesticks in the chart will be presented with the calculated color.
If the Labels setting is enabled, each time the trend changes direction a label will appear indicating the new direction. The latest candlestick will always show the current trend with a label.
EMA = Exponential Moving Average
RSI = Relative Strength Index
ATR = Average True Range
🚩 UNIQUENESS
The main point that differentiates this indicator from others is it's simplicity and customization options. The indicator interprets trend and strength detection in it's own way, combining 3 different well-known trend detection methods: RSI, Supertrend & EMA Cross into one simple method. The algorithm is fully customizable and all styling options are adjustable for the user's liking.
⚙️ SETTINGS
1. General Configuration
Detection Length -> This setting determines the amount of candlesticks the indicator will look for trend detection. Higher settings may help the indicator find longer trends, while lower settings will help with finding smaller trends.
Smoothing -> Higher settings will result in longer periods of time required for trend to change direction from bullish to bearish and vice versa.
EMA Lengths -> You can enter two EMA Lengths here, the second one must be longer than the first one. When the shorter one crosses under the longer one, this will be a bearish sign, and if it crosses above it will be a bullish sign for the indicator.
Labels -> Enables / Disables trend strength labels.
Gaussian Weighted Moving Average with Forecast [CHE]Presentation for TradingView: Gaussian Weighted Moving Average with Forecast
Introduction
Welcome to our presentation on the "Gaussian Weighted Moving Average with Forecast" (GWMA). This script, written in Pine Script™, offers an enhanced method for analyzing and predicting price movements on TradingView. The script combines Gaussian Weighted Moving Averages and polynomial regression to provide accurate and customizable forecasts.
Overview
Title: Gaussian Weighted Moving Average with Forecast
Author: chervolino
License: Mozilla Public License 2.0
Main Features
1. Gaussian Weighted Moving Average (GWMA):
- Calculates a weighted moving average using a Gaussian weighting function.
- Parameters for length and standard deviation allow fine-tuning of the smoothing effect.
2. Polynomial Regression with Forecast:
- Creates a model to predict future price movements.
- Adjustable length and degree of polynomial regression.
- Option to extrapolate predictions and visualize them.
3. Visual Representation:
- Uses lines and colors to depict trend changes.
- Customizable colors for upward and downward trends.
Input Parameters
Length: Length of the moving average (default: 50)
Standard Deviation: Standard deviation for Gaussian weighting (default: 10.0)
Width: Width of the plotted lines (default: 1)
Colors: Customizable colors for upward and downward trends
Forecast Length: Length of the forecast period (default: 20)
Extrapolate Length: Length of the extrapolation (default: 50)
Polynomial Degree: Degree of the polynomial regression (default: 3)
Lock Forecast: Option to lock and stabilize the forecast
Core Algorithms
1. Gaussian Weight Calculation:
gaussian_weight(x, std_dev) =>
1 / (std_dev * math.sqrt(2 * math.pi)) * math.exp(-0.5 * math.pow(x / std_dev, 2))
2. GWMA Calculation:
calculate_gwma(length, std_dev) =>
// Algorithm to calculate the weighted moving average
3. Initialize Lines for Polynomial Regression:
initialize_lines_array(extrapolate, length) =>
// Initialize array lines
4. Create Design Matrix for Polynomial Regression:
get_design_matrix(length, degree) =>
// Create the design matrix
5. Calculate and Plot Polynomial Regression:
calculate_polynomial_regression(src, length, degree, extrapolate, lines_arr, lock, width, upward_color, downward_color) =>
// Algorithm to calculate polynomial regression and plot the forecast
Combining Indicators: Originality and Usefulness
The combination of Gaussian Weighted Moving Average and polynomial regression provides traders with a robust tool for trend analysis and prediction. The GWMA smooths out price data while emphasizing recent prices, making it sensitive to short-term trends. Polynomial regression, on the other hand, offers a mathematical approach to model and forecast future prices based on historical data. By integrating these two methodologies, traders can achieve a more comprehensive view of market trends and potential future movements, making the tool highly valuable for decision-making.
Explanation for Users
Most TradingView users are not familiar with Pine Script, so a clear description is essential for understanding how to use the script.
Gaussian Weighted Moving Average (GWMA): This indicator calculates a moving average using Gaussian weights, which gives more importance to recent prices. The length and standard deviation parameters allow users to control the sensitivity and smoothness of the average.
Polynomial Regression with Forecast: This feature uses polynomial regression to model the price trend and predict future movements. Users can adjust the length of the historical data used, the degree of the polynomial, and the length of the forecast. The script plots these predictions, making it easier for traders to visualize potential future price paths.
Visualization of Results
1. GWMA Plotting:
plot(gaussian_ma_result, title="GWMA", color=line_color, linewidth=width_input)
2. Forecast Extrapolation:
plot(forecast_val, 'Extrapolation', offset=extrapolate_setting, linewidth=width_input, style=plot.style_circles)
Conclusion
The "Gaussian Weighted Moving Average with Forecast" script provides a powerful tool for analyzing and predicting price movements on TradingView. By combining Gaussian weighting and polynomial regression, it offers a precise and customizable method for trend analysis and forecasting.
Thank you for your attention! For any questions or further information, please feel free to reach out.
Harmonic Patterns [WinWorld]PREFACE
This indicator was made with the help of our team's fellow friend and harmonic patterns expert, whose support we deeply appreciate — @Muneer_Gove
DESCRIPTION
Harmonic patterns are one the most recognizable and popular trading concepts in the word of trading.
They are distinct formations, found in the financial markets, that predict potential price movements based on Fibonacci ratios. These patterns, which include the Gartley, Bat, Alt Bat, Butterfly and etc., identify specific and repetitive price structures that can forecast future price reversals. By incorporating these patterns into trading process, one does gain an opportunity to profit from repetetitve price movements.
The whole thing about harmonic pattern is the process of finding them. The basic step-by-step guide to build a harmonic pattern is this:
Locate significant highs and lows on the chart, which form the basis of the pattern. The best tools to use for this purple is zigzag, because zigzag indicator draw lines, which will be helpful quite helpful in the process and will save you a lot of time;
Use Fibonacci tools to measure the retracement and extension levels between legs of pattern — distances between pair of points . Each harmonic pattern has specific Fibonacci ratios that define its structure;
Draw lines connecting the pivot points according to the pattern's structure. For example, a Gartley pattern connects five points (X, A, B, C, D) in a specific sequence and ratio;
Ensure that the identified structure adheres to the harmonic pattern’s Fibonacci requirements. If the points align within the acceptable ranges, the pattern is valid.
In order to better understand this process let's see an example of the pattern from our indicator right away:
This is a Butterfly pattern. Its set of retracememt ratios is as follows:
AB/XA = 0.756 to 0.816
BC/AB = 0.382 to 0.990
CD/BC = 1.618 to 2.618
AD/XA = 1.27
Below you can see that each ratio of the pattern is successfully met:
* Note : white lines — ratio range, yellow line — point 's price level in between ranges.
AB/XA Ratio
BC/AB Ratio
CD/BC Ratio
AD/XA Ratio
SETTINGS
Main Settings
Failed Patterns — shows/hides patterns, which meet one of these conditions:
— Price crossed level of point C before reaching PRZ;
— New pattern appeared and PRZ of previous pattern was not reached;
Completed Patterns — shosw/hides patterns, whose PRZ was reached;
Dashboard — shows/hides dashboard, which displays active patterns (patterns, which can be used to trade).
Alert Settings
PRZ — enables/disables alert of event, when price reaches PRZ.
ZigZag Settings
Depth #1-9 — shows/hides patterns of the chosen zigzag copy. Here you can choose customize depth number.
Pattern Visual Controls
Bullish Patterns — shows/hides bullish patterns;
Bearish Patterns — shows/hides bearish patterns;
Pending Patterns — shows/hides patterns, whose PRZ has not been reached yet;
list of pattern names — hides/shows chosen pattern.
Colours
Bullish — colour of bullish patterns;
Bearish — colour of bearish patterns.
IMPORTANT CONCEPTS
PRZ — entry target level.
If its text near the line level is purple, it means that PRZ has NOT been reached yet.
If it is white, it means that PRZ has been reached.
In order for SL or TP to be counted when price reaches, price has to reach PRZ first with its high/low.
SL — stop-loss.
If its near the line level is red, it means that SL has NOT been reached yet.
If it is white, it means that SL has been reached.
If it is gray, it means that SL has been invalidated — price crossed with high/low the level of point C before reaching PRZ.
If SL is reached and price reaches TP targets, they will be counted.
SL of each pattern are built by individual ratio. For example, in Butterfly pattern SL ratio is 1.414 and it is calculated as (SL - A)/XA.
IMPORTANT NOTE : SL is reached when price crosses SL level with candle's close (!)
TP — take-profit.
If its near the line level is green, it means that TP has NOT been reached yet.
If it is white, it means that TP has been reached.
If one of the TP targets is reached and price reached SL, it will not be counted.
IMPORTANT NOTE : TP is reached when price crosses TP level with candle's high/low(!)
TP of each pattern are built by same the ratios for all patterns, but it is calculated by individual algorithm. For example, in the same Butterfly pattern TP ratio will be 0.382, 0.500 and 0.618 and they will be placed as Fibonacci retracement grid from point A to point D ( same for formula for all other patterns, excluding the ones listed next ), BUT on Shark , Muner and AB=CD pattern the same TP will be placed as Fibonacci retracement grid from point C to point D
WHY USE THIS INDICATOR?
Our Harmic Patterns indicator uses zigzag, which is based on depth mechanic. In order to identify the maximum possible amount of patterns this indicator runs 9 copies of the same zigzags with different depth values. Each copy of zigzag can be turned off in the settings individually.
At the moment of publishing, this indicator can autmatically identify 10 patterns:
Crab
Deep Crab
Gartley
Deep Gartley
Bat
Alt Bat
Muner
Butterfly
Shark
AB=CD
Things, that make this indicator different from other harmonic pattern indicator, are:
Advanced pattern recognition and validation process. We have implemeted special logic, which allows the indicator to draw fully accurate patterns, which satisfy industry standards.
For example, let's say we have a bearish pattern. We take points X an A. If there is a price's high, that is above X point's high, such pattern should be automatically invalidated. We have found even one indicator that does perform such validation process, and our indicator does that. . And this is just one example, we have much of such mechanics implemeted thanks to Mr. Muner's knowledge.
Advanced pattern extension mechanics . Right this mechanic applies to only one pattern — Shark. Its classic CD/BC ratio is 0.886, but when price moves in a way so this ratio now equals to 1.13, this signal the indicator to redraw the pattern, based on this new CD/BC ratio. We haven't found any indicator on the market that has such mechanic implemented.
Dashboard for displaying active patterns . On this dashboard you can find patterns, whose SL and TP have not been touched yet. If price touches the SL or TP of the pattern, this pattern is removed from the dashboard, because it is considered finished.
At the moment of publishing this dashboard only shows the patterns from the current timeframe.
Informative alert when price reaches PRZ of the pattern . Many other indicator do not provide details of this event, which requires trader to waste his time on opening up the chart and searching for this event. Our indicator allows trader to see the PRZ price right when alert happens and open up the trade much fastr.
Alert message is made by this template:
, : PRZ was reached at on
Example:
BTCUSDT, long Bat: PRZ was reached at 70,000 on 15m.
ALERTS
At the moment of publishing this indicator offers one alert, which happens when price reaches PRZ level.
HOW CAN I GET THE MOST OUT OF THIS INDICATOR?
This indicator can act as the standalone tool, because PRZ, TP and SL are assigned to each pattern and tracked during the pattern's life period.
You can this indicator with any other strategy or indicator, because this indicator is basically a tool that shows the trader repetitive price formations, after which price tends to go a certaion direction in the most cases, allowing trader to profit from it.
You can try combining Harmonic Patterns indicator with Smart Money tools, made by our team, because Smart Money strategies basically show the most liquid price zones and levels, which can be used to find an entry opportunity and Harmonic Patterns indicator can be added to make a final decision on the entry.
If you are interested in trying these two strategies together, feel free to learn Smart Money trading strategy by reading our Advanced SMC guide, which is available in our eductional materials.
SUMMARY
Harmonic Patterns indicator is an advanced tool of technical analysis, which automatically finds 10 most used harmonic patterns on the chart, assign PRZ, TP and SL targets to them and tracks them during each pattern 'life period'.
While searching for these patterns, this indicator performs series of validation techniques, that allow trader to see only the most valid patterns, which have a higher changes to succeed.
This indicator can be used both as a standalone tool and as 'team player' for any stategy by being the tool, which can be used for making a final decision on an entry target.
AFTERWORD
This indicator has been developed for more than 2 weeks, which consisted of everyday discussions, bug fixes and special additons to the algorithm in order to making patterns more valid, so we really hope you will find a great use of this indicator and it will help you recude time on the analysis and boost your profits :)
We want to express our gratitude to @Muneer_Gove once again, because he has done huge job helping us fine-tuning the algorithm, building complex pattern validatiom and extension logic and fixing bugs. Thank you!
Best of luck , traders!
— with love, WinWorld Team
Day trading volume based levels by VhatkarThis script identifies dynamic support and resistance levels based on volume and price action analysis. It uses a unique algorithm that combines volume force calculations with pivot points to determine key levels where price is likely to react.
Originality and Usefulness :
Innovative Volume Force Calculation : The script calculates upforce and downforce based on volume and price movement, providing a novel insight into buying and selling pressure. Unlike traditional volume indicators, this approach offers a more nuanced understanding of market dynamics.
Dynamic Pivot Points : Pivot points are dynamically adjusted based on volume force and highest high calculations, unlike conventional static pivot points. This makes the levels more responsive to real-time market conditions, offering traders a competitive edge.
Adaptive Target Levels : The script sets target and stop prices for both long and short positions, with adjustable percentages based on the chosen timeframe. This feature is particularly useful for day traders looking for precise entry and exit points.
Unique Timeframe Adjustments : The script includes specific adjustments for different timeframes (e.g., 15m, 30m, 60m), optimizing the support and resistance levels for day trading strategies. This adaptability is not commonly found in existing open-source scripts.
Volume-Weighted Adjustments : The integration of VWAP (Volume-Weighted Average Price) into the volume force calculation adds an extra layer of accuracy, helping traders make more informed decisions.
Comprehensive Visual Representation : The script offers clear visual plots of entry, target, and stop levels, along with color-coded fill areas that indicate different target zones. This visual clarity enhances user experience and decision-making.
Unique Features Compared to Open-Source Scripts :
Advanced Volume Force Algorithm : While many open-source scripts rely solely on price action or basic volume indicators, this script integrates a sophisticated volume force algorithm. This unique approach allows traders to identify more accurate support and resistance levels based on real market activity.
Dynamic and Adaptive Pivot Points : Unlike traditional open-source scripts that use static pivot points, this script dynamically adjusts pivot points based on the highest high and volume force. This dynamic adjustment provides a more precise and adaptable analysis suitable for various market conditions.
Integrated VWAP Calculation : Incorporating VWAP into volume force calculations adds an extra dimension of accuracy, allowing for more reliable trading signals. This feature differentiates the script from simpler open-source alternatives that may not include such advanced calculations.
How to Use :
Apply the Script : Add the "Vhatkar Dynamic S/R Levels" script to your chart. Make sure your chart has volume data as the script relies on volume calculations.
Select Timeframe : The script is designed for day trading timeframes such as 5m, 15m, and 30m. Ensure you are using one of these timeframes for optimal performance.
Adjust Parameters :
Target Lines : Set the number of target lines using the SLRange input. Increase the count if fewer lines are visible or decrease if too many lines are cluttering the chart.
Interpreting Signals :
Long Entries : When the close price is above the pivot point, the script plots potential long entry points and target levels (TP1, TP2, TP3) as well as a stop-loss level.
Short Entries : When the close price is below the pivot point, the script plots potential short entry points and target levels (TP1, TP2, TP3) as well as a stop-loss level.
Visual Aids : Use the color-coded fill areas to quickly identify target zones and stop levels.
Trade Management : Utilize the plotted entry, target, and stop levels to manage your trades. Adjust your trading strategy based on the levels provided by the script.
Usage :
Designed for day trading on timeframes such as 5m, 15m, and 30m.
Provides clear visual plots of entry, target, and stop levels.
Offers flexibility with adjustable parameters to suit different trading styles.
SMC Community [algoat] — Smart Money ConceptsEmpower your trading with the core principles of the Smart Money Concepts through interactive features and highly customizable settings.
The indicator's strength lies in the unique SMC Core algorithm, a calculation based on real price action data, capturing every tick from small intraday fluctuations to significant high timeframe movements.
algoat SMC Core is our continually evolving, specialized structure mapping algorithm, serving as the backbone of our price action related publications.
⭐ Key Features
Swing Market Structure: Change of Character, Break of Structure
Recognize and visualize real-time market structures with swing elements. Identify and mark key structural changes in the market to visually highlight shifts in market trends and patterns. This feature is designed to alert you to significant changes in the market's behavior, signaling a potential shift from accumulation to distribution phases, or vice versa. It helps traders adapt their strategies based on evolving market dynamics.
Order Flow: Structure Fractal
Connect the successive structural high and low levels, visualizing the intricate flow of market movements. This feature highlights fractal structures within the market, enabling traders to detect significant price action patterns.
Structure Range: Determine Discount, Premium, and Equilibrium Zones
This feature provides a unique way of visualizing price areas where a security could be overbought or oversold (premium or discount zones) and where the price is expected to be fair and balanced (equilibrium zone). Distance from the current price is displayed in percentage terms, which can assist traders with crucial data for risk management and strategic planning. The Range function helps you identify the most favorable price zones for entries and set your stop-loss and take-profit levels more accurately.
Liquidity Grabs: Reveal Hidden Manipulation Attempts
Identify uncovered market areas where high liquidity trading may take place. Liquidity Grabs help track "smart money" footprints by identifying levels where large institutional traders may have induced liquidity traps. Understanding these traps can aid in avoiding false market moves and optimizing trade entries.
Institutional Interest Zones: Order Blocks and Fair Value Gaps
Uncover areas where bigger orders may be lined up. Reveal zones of interest ordered by volume strength. Receive warnings about market price imbalances.
▸ Order Blocks pinpoint crucial zones where large institutional investors ("smart money") have shown strong buying or selling interest recently. These blocks can serve as a tool for identifying key areas for potential trade entries or exits.
▸ Fair Value Gaps detect discrepancies between the perceived market value and the actual market price, revealing potential areas for price correction. With its mitigation settings, you can fine-tune the FVG detection according to the magnitude of value misalignment you consider significant.
Mitigation types dictate how price interacts with a zone, with order blocks requiring a close through (indicating stronger price movement) and fair value gaps requiring a wick through (hinting at weak rejection).
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⭐ Why SMC?
In the ever-evolving trading landscape, mainstream methods and strategies can quickly become outdated as they are widely adopted. Liquidity is constantly sought after, and the best source for this is exploring and exploiting trading strategies that are widely accepted and applied. Currently, one of these strategies is the SMC (Supply, Demand, and Price Action).
It's no coincidence that our educational materials incorporate concepts such as liquidity grabs (LG) and Smart Money Traps (SMT). As the application of SMC gains popularity among retail traders, trading with this approach becomes more challenging. Therefore, the recent focus has been on reforming the SMC methodology, as it is the only method that relies on real price movements and will always work when applied correctly.
The indicator reflects our personal use and deep comprehension of Smart Money Concepts. It provides streamlined tools for tracking algorithmic trends with modern visualizations, without unnecessary clutter.
▸ What does the proper application of SMC entail?
Many SMC traders associate their key areas of interest with the market structure, which is generally considered acceptable. However, depending solely on a single foundation can lead to significant deviations, which may cause notable impacts on trading results. Moreover, if the basis for the market structure calculation is inaccurate, the consequences can be even more severe. It's akin to risking money on a lottery ticket, believing it will be a winner.
Our methodology is different, and it may ensure longevity in the financial markets. The structure remains crucial, but it is not the sole foundation of everything; instead, it serves as a validation tool. Each calculation, such as order blocks (OB), Fair Value Gaps (FVG), liquidity grabs (LG), range analysis, and more, is independent and unique, separate from the structure. However, validation must ultimately come from the structure itself.
We employ individual and high-quality filters: before a function calculation is validated by the structure, it must undergo rigorous testing based on its own set of validation conditions. This approach aims to enhance robustness and accuracy, providing traders with a reliable framework for making informed trading decisions.
▸ An example of structure validation: Order Block with "Swing Sensitivity"
These order blocks will only be displayed and utilized by the script if there is a swing structure validation with a valid break. In other words, the presence of a confirmed swing Change of Character (ChoCh) or Break of Structure (BoS) is essential for the Order Block to be considered valid and relevant.
This approach ensures that the order blocks are aligned with the overall market structure and are not based on isolated or unreliable price movements. Whether it's Fair Value Gaps (FVG), Liquidity Grabs (LG), Range calculations, or other functionalities, the same underlying principle holds true. The background structure calculation serves as a validation mechanism for the data and insights generated by these functions, ensuring they adhere to the specific criteria and rules established within our methodology. By incorporating this robust validation process, traders can have confidence in the reliability and accuracy of the information provided by the indicator, allowing them to make informed trading decisions based on validated data and analysis.
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👉 Usage - the general approach
Determine your trading style and build your basic strategy:
The indicator helps you understand your trading style, whether it's swing trading, scalping or another approach. By analyzing the SMC indicator, you gain valuable information about potential market trends, entry and exit points, and overall market sentiment.
Steps:
Identify Trading Style: Determine whether you are a swing trader, scalper, or long-term investor. This will influence how you use the indicator.
Analyze Market Trends: Use the SMC indicator to observe market trends and identify potential entry and exit points.
Adapt Strategies: Adjust your strategies based on the market dynamics revealed by the SMC indicator, such as changes in order flow or market structure.
👉 Example of usage
In the following chart, you'll notice how we've utilized the indicator to formulate a strategic trading approach. We've employed Order Blocks equipped with volume parameters to identify crucial market zones. Simultaneously, we've leveraged swing/internal market structures to gain insights into potential long- and short-term market turnarounds. Lastly, we've examined trend line liquidity zones to pinpoint probable impulses and breakouts within ongoing trends.
Now we can see how the price descended to the order block with the highest volume, which we had previously marked as our point of interest for an entry. As the price closed below the median Order Block, we noted its mitigation. After an internal CHoCH, it's directing us towards the main Order Block as a target.
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🧠 General advice
Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives.
Confirming signals with other indicators
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators
Integrate this indicator with other technical indicators to develop a comprehensive trading strategy and provide additional confirmation.
Conduct Thorough Research and Backtesting
Ensure a solid understanding of the indicator and its behavior through thorough research and backtesting before making trading decisions. Consider incorporating fundamental analysis and market sentiment into your trading approach.
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⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era.
Risk Notice
Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
