ImbalancesThis Pine Script is a trading indicator designed to identify imbalances in the market, specifically on candlestick charts. An imbalance refers to situations where there is a significant difference between buyers and sellers, which can create gaps or areas of inefficiency in the price. These imbalances often act as zones where price may return to "fill" or correct these inefficiencies.
1. Identifying Imbalances
The script analyzes candlestick patterns to detect imbalances based on the relationship between the highs, lows, and closes of consecutive candles. Specifically, it looks for:
Top Imbalances (Bearish): Areas where selling pressure has dominated, causing inefficiencies in the price. These are represented by patterns like multiple consecutive bearish candles or bearish gaps.
Bottom Imbalances (Bullish): Areas where buying pressure has dominated, leading to bullish gaps or inefficiencies.
When an imbalance is detected, the script highlights the area using visual boxes on the chart.
2. Visual Representation
The indicator uses colored boxes to show imbalances directly on the chart:
Top (Bearish) Imbalances: Highlighted using shades of red.
Bottom (Bullish) Imbalances: Highlighted using shades of green.
The boxes are further categorized into three states based on their level of mitigation:
Unmitigated: The imbalance has not been "filled" by price yet.
Partially Mitigated: Price has entered the imbalance zone but not completely filled it.
Fully Mitigated: Price has completely filled the imbalance zone.
3. Mitigation Logic
The concept of mitigation refers to the price revisiting an imbalance zone to correct the inefficiency:
If price fully or partially revisits an imbalance zone, the box's color changes to indicate the mitigation level (e.g., from unmitigated to partially/fully mitigated).
Fully mitigated boxes may be removed or recolored, depending on user preferences.
4. User Customization
The script provides several inputs to customize its behavior:
Enable or disable top and bottom imbalance detection.
Color settings: Users can define different colors for unmitigated, partially mitigated, and fully mitigated imbalances.
Mitigation display options: Users can choose whether to show fully mitigated imbalances on the chart or remove them.
5. Key Calculations
Imbalance Size: The size of the imbalance is calculated as the price difference between a candle's high and low across the relevant pattern.
Pattern Detection: The script checks for specific candlestick patterns (e.g., three consecutive bearish candles) to identify potential imbalances.
6. Practical Use Case
This indicator is useful for traders who:
Rely on supply and demand zones for their trading strategies.
Look for areas where price is likely to return (retesting unmitigated imbalances can signal potential trade setups).
Want to visually track market inefficiencies over time.
In Summary
The "Imbalances" indicator highlights and tracks price inefficiencies on candlestick charts. It marks zones where buying or selling pressure was dominant, and it dynamically updates these zones based on price action to indicate their mitigation status. This tool is particularly helpful for traders who use price action and market structure in their strategies.
波動率
Ultimate Volatility RateUltimate Volatility Rate
This indicator measures the volatility of price movements.
Support and Resistance Identification:
High volatility periods indicate larger price movements, which can be useful in assessing the potential for support and resistance levels to be broken.
Stop Loss (SL) and Take Profit (TP) Calculations:
The average volatility can be used to calculate dynamic Stop Loss (SL) and Take Profit (TP) levels:
SL: Placing it at a certain volatility multiplier below/above the entry price.
TP: Setting it at a certain volatility multiplier below/above the entry price.
For example:
SL: Entry price +/- (UVR × 1.5)
TP: Entry price +/- (UVR × 2)
Market Condition Analysis:
When the indicator value is high, it suggests that the market is volatile (active).
When the value is low, it indicates the market is in consolidation (sideways movement).
This information helps traders decide whether to take trend-following or consolidation-based positions.
Trend Reversal Monitoring:
A sudden increase in volatility often signals the start of a strong trend.
Conversely, a decrease in volatility can signal the slowing down or end of a trend.
Custom ATR with Paranormal Bar FilterCustom ATR with Paranormal Bar Filter
Description:
This indicator calculates a custom ATR (Average True Range) by filtering out bars with unusually large or small price ranges. It helps provide a more accurate measure of market volatility by ignoring outliers.
How it works:
True Range Calculation:
The price range for each bar is calculated.
Bars with ranges much larger or smaller than typical are excluded.
Filtered ATR:
The ATR is calculated using only the bars that pass the filter.
Current Bar Progress:
Measures how much the current bar has moved compared to the filtered ATR, based on the difference between its opening and closing prices.
Display:
A line represents the filtered ATR.
A table shows the filtered ATR, the current bar's range, and its progress relative to the ATR.
Input Settings:
ATR Period: Number of bars used to calculate the ATR.
Filter Window: Number of recent bars used to determine the typical range.
Filter Threshold: Sensitivity of the filter. A higher value allows more bars to pass.
How to Use:
Monitor Volatility:
Use the filtered ATR to understand market volatility while ignoring unusual price movements.
Track Current Bar Progress:
See how much of the ATR the current bar has completed.
Adjust Filter Settings:
Fine-tune the filter to match your trading timeframe and strategy.
This indicator is designed for traders who want to track market volatility without being misled by extreme outlier bars.
Quick scan for signal🙏🏻 Hey TV, this is QSFS, following:
^^ Quick scan for drift (QSFD)
^^ Quick scan for cycles (QSFC)
As mentioned before, ML trading is all about spotting any kind of non-randomness, and this metric (along with 2 previously posted) gonna help ya'll do it fast. This one will show you whether your time series possibly exhibits mean-reverting / consistent / noisy behavior, that can be later confirmed or denied by more sophisticated tools. This metric is O(n) in windowed mode and O(1) if calculated incrementally on each data update, so you can scan Ks of datasets w/o worrying about melting da ice.
^^ windowed mode
Now the post will be divided into several sections, and a couple of things I guess you’ve never seen or thought about in your life:
1) About Efficiency Ratios posted there on TV;
Some of you might say this is the Efficiency Ratio you’ve seen in Perry's book. Firstly, I can assure you that neither me nor Perry, just as X amount of quants all over the world and who knows who else, would say smth like, "I invented it," lol. This is just a thing you R&D when you need it. Secondly, I invite you (and mods & admin as well) to take a lil glimpse at the following screenshot:
^^ not cool...
So basically, all the Efficiency Ratios that were copypasted to our platform suffer the same bug: dudes don’t know how indexing works in Pine Script. I mean, it’s ok, I been doing the same mistakes as well, but loxx, cmon bro, you... If you guys ever read it, the lines 20 and 22 in da code are dedicated to you xD
2) About the metric;
This supports both moving window mode when Length > 0 and all-data expanding window mode when Length < 1, calculating incrementally from the very first data point in the series: O(n) on history, O(1) on live updates.
Now, why do I SQRT transform the result? This is a natural action since the metric (being a ratio in essence) is bounded between 0 and 1, so it can be modeled with a beta distribution. When you SQRT transform it, it still stays beta (think what happens when you apply a square root to 0.01 or 0.99), but it becomes symmetric around its typical value and starts to follow a bell-shaped curve. This can be easily checked with a normality test or by applying a set of percentiles and seeing the distances between them are almost equal.
Then I noticed that on different moving window sizes, the typical value of the metric seems to slide: higher window sizes lead to lower typical values across the moving windows. Turned out this can be modeled the same way confidence intervals are made. Lines 34 and 35 explain it all, I guess. You can see smth alike on an autocorrelogram. These two match the mean & mean + 1 stdev applied to the metric. This way, we’ve just magically received data to estimate alpha and beta parameters of the beta distribution using the method of moments. Having alpha and beta, we can now estimate everything further. Btw, there’s an alternative parameterization for beta distributions based on data length.
Now what you’ll see next is... u guys actually have no idea how deep and unrealistically minimalistic the underlying math principles are here.
I’m sure I’m not the only one in the universe who figured it out, but the thing is, it’s nowhere online or offline. By calculating higher-order moments & combining them, you can find natural adaptive thresholds that can later be used for anomaly detection/control applications for any data. No hardcoded thresholds, purely data-driven. Imma come back to this in one of the next drops, but the truest ones can already see it in this code. This way we get dem thresholds.
Your main thresholds are: basis, upper, and lower deviations. You can follow the common logic I’ve described in my previous scripts on how to use them. You just register an event when the metric goes higher/lower than a certain threshold based on what you’re looking for. Then you take the time series and confirm a certain behavior you were looking for by using an appropriate stat test. Or just run a certain strategy.
To avoid numerous triggers when the metric jitters around a threshold, you can follow this logic: forget about one threshold if touched, until another threshold is touched.
In general, when the metric gets higher than certain thresholds, like upper deviation, it means the signal is stronger than noise. You confirm it with a more sophisticated tool & run momentum strategies if drift is in place, or volatility strategies if there’s no drift in place. Otherwise, you confirm & run ~ mean-reverting strategies, regardless of whether there’s drift or not. Just don’t operate against the trend—hedge otherwise.
3) Flex;
Extension and limit thresholds based on distribution moments gonna be discussed properly later, but now you can see this:
^^ magic
Look at the thresholds—adaptive and dynamic. Do you see any optimizations? No ML, no DL, closed-form solution, but how? Just a formula based on a couple of variables? Maybe it’s just how the Universe works, but how can you know if you don’t understand how fundamentally numbers 3 and 15 are related to the normal distribution? Hm, why do they always say 3 sigmas but can’t say why? Maybe you can be different and say why?
This is the primordial power of statistical modeling.
4) Thanks;
I really wanna dedicate this to Charlotte de Witte & Marion Di Napoli, and their new track "Sanctum." It really gets you connected to the Source—I had it in my soul when I was doing all this ∞
RS Cycles [QuantVue]The RS Cycles indicator is a technical analysis tool that expands upon traditional relative strength (RS) by incorporating Beta-based adjustments to provide deeper insights into a stock's performance relative to a benchmark index. It identifies and visualizes positive and negative performance cycles, helping traders analyze trends and make informed decisions.
Key Concepts:
Traditional Relative Strength (RS):
Definition: A popular method to compare the performance of a stock against a benchmark index (e.g., S&P 500).
Calculation: The traditional RS line is derived as the ratio of the stock's closing price to the benchmark's closing price.
RS=Stock Price/Benchmark Price
Usage: This straightforward comparison helps traders spot periods of outperformance or underperformance relative to the market or a specific sector.
Beta-Adjusted Relative Strength (Beta RS):
Concept: Traditional RS assumes equal volatility between the stock and benchmark, but Beta RS accounts for the stock's sensitivity to market movements.
Calculation:
Beta measures the stock's return relative to the benchmark's return, adjusted by their respective volatilities.
Alpha is then computed to reflect the stock's performance above or below what Beta predicts:
Alpha=Stock Return−(Benchmark Return×β)
Significance: Beta RS highlights whether a stock outperforms the benchmark beyond what its Beta would suggest, providing a more nuanced view of relative strength.
RS Cycles:
The indicator identifies positive cycles when conditions suggest sustained outperformance:
Short-term EMA (3) > Mid-term EMA (10) > Long-term EMA (50).
The EMAs are rising, indicating positive momentum.
RS line shows upward movement over a 3-period window.
EMA(21) > 0 confirms a broader uptrend.
Negative cycles are marked when the opposite conditions are met:
Short-term EMA (3) < Mid-term EMA (10) < Long-term EMA (50).
The EMAs are falling, indicating negative momentum.
RS line shows downward movement over a 3-period window.
EMA(21) < 0 confirms a broader downtrend.
This indicator combines the simplicity of traditional RS with the analytical depth of Beta RS, making highlighting true relative strength and weakness cycles.
IV Rank/Percentile with Williams VIX FixDisplay IV Rank / IV Percentile
This indicator is based on William's VixFix, which replicates the VIX—a measure of the implied volatility of the S&P 500 Index (SPX). The key advantage of the VixFix is that it can be applied to any security, not just the SPX.
IV Rank is calculated by identifying the highest and lowest implied volatility (IV) values over a selected number of past periods. It then determines where the current IV lies as a percentage between these two extremes. For example, if over the past five periods the highest IV was 30%, the lowest was 10%, and the current IV is 20%, the IV Rank would be 50%, since 20% is halfway between 10% and 30%.
IV Percentile, on the other hand, considers all past IV values—not just the highest and lowest—and calculates the percentage of these values that are below the current IV. For instance, if the past five IV values were 30%, 10%, 11%, 15%, and 17%, and the current IV is 20%, the IV Rank remains at 50%. However, the IV Percentile is 80% because 4 out of the 5 past values (80%) are below the current IV of 20%.
Real-Time Custom Candle Range Color Indicator
The script allows the user to input a custom range value (default set to 100 points) through the userDefinedRange variable. This value determines the minimum range required for a candle to change color.
Calculating Candle Range:
The script calculates the range of each candle by subtracting the low from the high price.
Determining Bullish or Bearish Candles:
It checks whether the close price is higher than the open price to determine if a candle is bullish (isBullish variable).
Coloring Candles:
Based on the custom range input, the script changes the color of the candles:
If the candle's range is greater than or equal to the custom range and it is bullish, the candle color is set to blue (bullishColor).
If the range condition is met and the candle is bearish, the color is set to orange (bearishColor).
If the range condition is not met, the color is set to na (not applicable).
Plotting Colored Candles:
The plotcandle function is used to plot candles with colors based on the custom range and bullish/bearish conditions. The candles will have a higher z-order to be displayed in front of default candles.
Displaying High and Low Price Points:
Triangular shapes are plotted at the high and low price levels using the plotshape function, with colors representing bullish (blue) and bearish (orange) conditions.
In trading, this indicator can help traders visually identify candles that meet a specific range criteria, potentially signaling strength or weakness in price movements. By customizing the range parameter, traders can adapt the indicator to different market conditions and trading strategies. It can be used in conjunction with other technical analysis tools to make informed trading decisions based on candlestick patterns and price movements.
Simplified Momentum ScoreIndicator Name: Simplified Momentum Score
Description:
The Simplified Momentum Score indicator calculates the normalized price momentum of an asset over a user-defined period (e.g., 30 days). It provides a single actionable score between 0 and 1, making it easy to compare the relative strength of different tokens or assets:
1: Strongest momentum (best performer).
0: Weakest momentum (worst performer).
How to Use:
Apply this indicator to any chart in TradingView.
Use the normalized score to rank tokens or assets:
Closer to 1: Indicates strong recent price performance.
Closer to 0: Indicates weak recent price performance.
Customize the momentum period to match your trading strategy.
This tool is ideal for quick comparative analysis of multiple tokens to identify top-performing assets. Keep it simple, actionable, and effective! 🚀
Relative Momentum StrengthThe Relative Momentum Strength (RMS) indicator is designed to help traders and investors identify tokens with the strongest momentum over two customizable timeframes. It calculates and plots the percentage price change over 30-day and 90-day periods (or user-defined periods) to evaluate a token's relative performance.
30-Day Momentum (Green Line): Short-term price momentum, highlighting recent trends and movements.
90-Day Momentum (Blue Line): Medium-term price momentum, providing insights into broader trends.
This tool is ideal for comparing multiple tokens or assets to identify those showing consistent strength or weakness. Use it to spot outperformers and potential reversals in a competitive universe of assets.
How to Use:
Apply this indicator to your TradingView chart for any token or asset.
Look for tokens with consistently high positive momentum for potential strength.
Use the plotted values to compare relative performance across your watchlist.
Customization:
Adjust the momentum periods to suit your trading strategy.
Overlay it with other indicators like RSI or volume for deeper analysis.
Candlestick Strength and Volatility ReadoutDisplays a readout on the top right corner of the screen displaying a two basic calculations (volatility and strength; i.e. candlestick size and how close to the highs or lows it closed) for more convenient candlestick (price action) analysis.
Due to restrictions with Pine Script (or my knowledge thereof) only the current and previous candlestick data is shown, rather than the one currently hovered over.
The data is derived via two simple calculations; volatility being division between the range of the candlestick's high and low by the ATR; 'strength' (what I like to call it) being the range of the body by the range of the open to high or low, depending on the facing direction (positive or negative candlestick). These are expressed as percentages and will turn green depending on the set threshold.
Using this, one can effectively automate calculations you'd have to do by hand otherwise. I personally use these as entry filters in my trading, so it helps to not have to measure, remeasure, and divide before each potential entry.
Settings are implemented to change certain variables to your liking.
MadTrend [InvestorUnknown]The MadTrend indicator is an experimental tool that combines the Median and Median Absolute Deviation (MAD) to generate signals, much like the popular Supertrend indicator. In addition to identifying Long and Short positions, MadTrend introduces RISK-ON and RISK-OFF states for each trade direction, providing traders with nuanced insights into market conditions.
Core Concepts
Median and Median Absolute Deviation (MAD)
Median: The middle value in a sorted list of numbers, offering a robust measure of central tendency less affected by outliers.
Median Absolute Deviation (MAD): Measures the average distance between each data point and the median, providing a robust estimation of volatility.
Supertrend-like Functionality
MadTrend utilizes the median and MAD in a manner similar to how Supertrend uses averages and volatility measures to determine trend direction and potential reversal points.
RISK-ON and RISK-OFF States
RISK-ON: Indicates favorable conditions for entering or holding a position in the current trend direction.
RISK-OFF: Suggests caution, signaling RISK-ON end and potential trend weakening or reversal.
Calculating MAD
The mad function calculates the median of the absolute deviations from the median, providing a robust measure of volatility.
// Function to calculate the Median Absolute Deviation (MAD)
mad(series float src, simple int length) =>
med = ta.median(src, length) // Calculate median
abs_deviations = math.abs(src - med) // Calculate absolute deviations from median
ta.median(abs_deviations, length) // Return the median of the absolute deviations
MADTrend Function
The MADTrend function calculates the median and MAD-based upper (med_p) and lower (med_m) bands. It determines the trend direction based on price crossing these bands.
MADTrend(series float src, simple int length, simple float mad_mult) =>
// Calculate MAD (volatility measure)
mad_value = mad(close, length)
// Calculate the MAD-based moving average by scaling the price data with MAD
median = ta.median(close, length)
med_p = median + (mad_value * mad_mult)
med_m = median - (mad_value * mad_mult)
var direction = 0
if ta.crossover(src, med_p)
direction := 1
else if ta.crossunder(src, med_m)
direction := -1
Trend Direction and Signals
Long Position (direction = 1): When the price crosses above the upper MAD band (med_p).
Short Position (direction = -1): When the price crosses below the lower MAD band (med_m).
RISK-ON: When the price moves further in the direction of the trend (beyond median +- MAD) after the initial signal.
RISK-OFF: When the price retraces towards the median, signaling potential weakening of the trend.
RISK-ON and RISK-OFF States
RISK-ON LONG: Price moves above the upper band after a Long signal, indicating strengthening bullish momentum.
RISK-OFF LONG: Price falls back below the upper band, suggesting potential weakness in the bullish trend.
RISK-ON SHORT: Price moves below the lower band after a Short signal, indicating strengthening bearish momentum.
RISK-OFF SHORT: Price rises back above the lower band, suggesting potential weakness in the bearish trend.
Picture below show example RISK-ON periods which can be identified by “cloud”
Note: Highlighted areas on the chart indicating RISK-ON and RISK-OFF periods for both Long and Short positions.
Implementation Details
Inputs and Parameters:
Source (input_src): The price data used for calculations (e.g., close, open, high, low).
Median Length (length): The number of periods over which the median and MAD are calculated.
MAD Multiplier (mad_mult): Determines the distance of the upper and lower bands from the median.
Calculations:
Median and MAD are recalculated each period based on the specified length.
Upper (med_p) and Lower (med_m) Bands are computed by adding and subtracting the scaled MAD from the median.
Visual representation of the indicator on a price chart:
Backtesting and Performance Metrics
The MadTrend indicator includes a Backtesting Mode with a performance metrics table to evaluate its effectiveness compared to a simple buy-and-hold strategy.
Equity Calculation:
Calculates the equity curve based on the signals generated by the indicator.
Performance Metrics:
Metrics such as Mean Returns, Standard Deviation, Sharpe Ratio, Sortino Ratio, and Omega Ratio are computed.
The metrics are displayed in a table for both the strategy and the buy-and-hold approach.
Note: Due to the use of labels and plot shapes, automatic chart scaling may not function ideally in Backtest Mode.
Alerts and Notifications
MadTrend provides alert conditions to notify traders of significant events:
Trend Change Alerts
RISK-ON and RISK-OFF Alerts - Provides real-time notifications about the RISK-ON and RISK-OFF states for proactive trade management.
Customization and Calibration
Default Settings: The provided default settings are experimental and not optimized. They serve as a starting point for users.
Parameter Adjustment: Traders are encouraged to calibrate the indicator's parameters (e.g., length, mad_mult) to suit their specific trading style and the characteristics of the asset being analyzed.
Source Input: The indicator allows for different price inputs (open, high, low, close, etc.), offering flexibility in how the median and MAD are calculated.
Important Notes
Market Conditions: The effectiveness of the MadTrend indicator can vary across different market conditions. Regular calibration is recommended.
Backtest Limitations: Backtesting results are historical and do not guarantee future performance.
Risk Management: Always apply sound risk management practices when using any trading indicator.
HMA Gaussian Volatility AdjustedOverview
The "HMA Gaussian Volatility Adjusted" indicator introduces a unique combination of HMA smoothing with a Gaussian filter and two components to measure volatility (Average True Range (ATR) and Standard Deviation (SD)). This tool provides traders with a stable and accurate measure of price trends by integrating a Gaussian Filter smoothed using HMA with a customized calculation of volatility. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise.
Technical Composition and Calculation
The "HMA Gaussian Volatility Adjusted" indicator incorporates HMA smoothing and dynamic standard deviation calculations to build upon traditional volatility measures.
HMA & Gaussian Smoothing:
HMA Calculation (HMA_Length): The script applies a Hull Moving Average (HMA) to smooth the price data over a user-defined period, reducing noise and helping focus on broader market trends.
Gaussian Filter Calculation (Length_Gaussian): The smoothed HMA data is further refined by putting it into a Gaussian filter to incorporate a normal distribution.
Volatility Measurement:
ATR Calculation (ATR_Length, ATR_Factor): The indicator incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the Gaussian, providing a dynamic measure of potential price movement based on recent volatility.
Standard Deviation Calculation (SD_Length): The script calculates the standard deviation of the price over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (SDD, SDU) act as additional indicators of price extremes.
Momentum Calculation & Scoring
When the indicator signals SHORT:
Diff = Price - Upper Boundary of the Standard Deviation (calculated on a Gaussian filter).
When the indicator signals LONG:
Diff = Price - Upper Boundary of the ATR (calculated on a Gaussian filter).
The calculated Diff signals how close the indicator is to changing trends. An EMA is applied to the Diff to smooth the data. Positive momentum occurs when the Diff is above the EMA, and negative momentum occurs when the Diff is below the EMA.
Trend Detection
Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands, combined with positive/negative momentum, signals potential uptrends or downtrends, offering traders a clear view of market direction.
Features and User Inputs
The "HMA Gaussian Volatility Adjusted" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions:
HMA Length: Allows traders to adjust the sensitivity of the HMA smoothing to control the amount of noise filtered from the price data.
Gaussian Length: Users can define the length at which the Gaussian filter is applied.
ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands to adjust for price volatility.
Standard Deviation Length: Controls how the standard deviation is calculated, allowing further customization in detecting price volatility.
EMA Confluence: This input lets traders determine the length of the EMA used to calculate price momentum.
Type of Plot Setting: Allows users to determine how the indicator signal is plotted on the chart (Background color, Trend Lines, BOTH (backgroung color and Trend Lines)).
Transparency: Provides users with customization of the background color's transparency.
Color Long/Short: Offers users the option to choose their preferred colors for both long and short signals.
Summary and Usage Tips
The "HMA Gaussian Volatility Adjusted" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of HMA smoothing, Gaussian filtering, and standard deviation analysis provides a nuanced view of market movements by incorporating various metrics to determine direction, momentum, and volatility. This helps traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs.
ATR-based TP/SL with Dynamic RREnglish
This indicator combines the power of the Average True Range (ATR) with dynamic calculations for Take Profit (TP) and Stop Loss (SL) levels, offering a clear visualization of trading opportunities and their respective Risk-Reward Ratios (RRR).
Features:
Dynamic TP/SL Calculation:
TP and SL levels are derived using user-defined ATR multipliers for precise positioning.
Multipliers are flexible, allowing traders to adjust according to their strategies.
Risk-Reward Ratio (RRR):
Automatically calculates and displays the RRR for each trade signal.
Helps traders quickly assess if a trade aligns with their risk management plan.
Entry Conditions:
Buy signals occur when the closing price crosses above the 20-period Simple Moving Average (SMA).
Sell signals occur when the closing price crosses below the 20-period SMA.
Visual Aids:
Red and green lines indicate Stop Loss and Take Profit levels.
Blue and orange labels show the RRR for long and short trades, respectively.
How It Works:
The indicator uses the ATR to calculate TP and SL levels:
TP: Adjusted based on the desired Risk-Reward Ratio (RR).
SL: Proportional to the ATR multiplier.
Entry signals are plotted with "BUY" or "SELL" markers, while the respective TP/SL levels are drawn as horizontal lines.
Why Use This Indicator?
Perfect for traders who value precise risk management.
Helps identify trades with favorable RRR (e.g., greater than 1.5 or 2.0).
Ideal for swing traders, day traders, and scalpers looking to automate their decision-making process.
Customization:
ATR Length: Control the sensitivity of ATR-based calculations.
ATR Multipliers: Set the TP and SL distances relative to the ATR.
Desired RRR: Define the risk/reward ratio you aim to achieve.
Important Notes:
The indicator does not place trades automatically; it is for visual and analytical purposes.
Always backtest and combine it with additional analysis for best results.
French
Cet indicateur combine la puissance de l’Average True Range (ATR) avec des calculs dynamiques pour les niveaux de Take Profit (TP) et de Stop Loss (SL), tout en offrant une visualisation claire des opportunités de trading et de leurs Ratios Risque/Rendement (RRR).
Fonctionnalités :
Calcul Dynamique des TP/SL :
Les niveaux de TP et SL sont calculés à l'aide de multiplicateurs ATR définis par l’utilisateur pour une position précise.
Les multiplicateurs sont personnalisables pour s'adapter à votre stratégie de trading.
Ratio Risque/Rendement (RRR) :
Calcule et affiche automatiquement le ratio RRR pour chaque signal de trade.
Permet aux traders d’évaluer rapidement si un trade correspond à leur plan de gestion des risques.
Conditions d'Entrée :
Les signaux d'achat apparaissent lorsque le prix de clôture traverse au-dessus de la moyenne mobile simple (SMA) à 20 périodes.
Les signaux de vente apparaissent lorsque le prix de clôture traverse en dessous de la SMA à 20 périodes.
Aides Visuelles :
Lignes rouges et vertes pour indiquer les niveaux de Stop Loss et de Take Profit.
Étiquettes bleues et orange pour afficher le RRR des trades longs et courts, respectivement.
Comment Cela Fonctionne :
L'indicateur utilise l’ATR pour calculer les niveaux TP et SL :
TP : Calculé dynamiquement en fonction du ratio risque/rendement souhaité (RRR).
SL : Proportionnel au multiplicateur ATR défini par l’utilisateur.
Les signaux d’entrée sont représentés par des étiquettes "BUY" ou "SELL", tandis que les niveaux de TP/SL sont tracés sous forme de lignes horizontales.
Pourquoi Utiliser Cet Indicateur ?
Idéal pour les traders soucieux d’une gestion rigoureuse des risques.
Identifie les opportunités de trades avec des RRR favorables (par exemple, supérieurs à 1.5 ou 2.0).
Convient aux swing traders, day traders et scalpeurs souhaitant automatiser leur processus de décision.
Personnalisation :
Longueur de l’ATR : Contrôlez la sensibilité des calculs basés sur l’ATR.
Multiplicateurs ATR : Ajustez les distances TP et SL par rapport à l’ATR.
Ratio RRR souhaité : Définissez le ratio risque/rendement que vous visez.
Remarques Importantes :
Cet indicateur n’exécute pas de trades automatiquement ; il est destiné à un usage visuel et analytique uniquement.
Toujours backtester et combiner avec une analyse supplémentaire pour de meilleurs résultats.
parametre par type de trading:
1. Pour les Scalpers :
Style de trading : Trades rapides sur de petites variations de prix, souvent sur des unités de temps courtes (1 min, 5 min).
Recommandations de paramètres :
ATR Length : 7 (plus court pour réagir rapidement à la volatilité).
Multiplicateur SL : 1.0 (Stop Loss proche pour limiter les pertes).
RR souhaité : 1.5 à 2.0 (bon équilibre entre risque et récompense).
Résultat attendu : Des trades fréquents, avec une probabilité raisonnable de toucher le TP tout en limitant les pertes.
2. Pour les Day Traders :
Style de trading : Trades qui durent plusieurs heures dans la journée, souvent sur des unités de temps moyennes (15 min, 1h).
Recommandations de paramètres :
ATR Length : 14 (standard pour capturer une volatilité modérée).
Multiplicateur SL : 1.5 (Stop Loss à distance raisonnable pour supporter les fluctuations intrajournalières).
RR souhaité : 2.0 à 3.0 (ciblez une bonne récompense par rapport au risque).
Résultat attendu : Moins de trades, mais un RR élevé pour compenser les pertes potentielles.
3. Pour les Swing Traders :
Style de trading : Trades qui durent plusieurs jours, souvent sur des unités de temps longues (4h, 1 jour).
Recommandations de paramètres :
ATR Length : 20 (pour capturer des mouvements de volatilité plus larges).
Multiplicateur SL : 2.0 (Stop Loss large pour supporter des fluctuations importantes).
RR souhaité : 3.0 ou plus (ciblez de gros mouvements de prix).
Résultat attendu : Des trades moins fréquents mais potentiellement très lucratifs.
4. Pour les Actifs Volatils (Crypto, Commodités) :
Problème spécifique : Les actifs volatils ont souvent des mouvements brusques.
Recommandations de paramètres :
ATR Length : 7 ou 10 (plus court pour suivre rapidement les variations).
Multiplicateur SL : 1.5 à 2.0 (assez large pour ne pas être déclenché prématurément).
RR souhaité : 1.5 à 2.0 (favorisez des récompenses réalistes sur des mouvements volatils).
Résultat attendu : Trades qui s’adaptent à la volatilité sans sortir trop tôt.
5. Pour les Marchés Stables (Indices, Actions Blue Chip) :
Problème spécifique : Les mouvements sont souvent lents et prévisibles.
Recommandations de paramètres :
ATR Length : 14 ou 20 (capture une volatilité modérée).
Multiplicateur SL : 1.0 à 1.5 (Stop Loss serré pour maximiser l’efficacité).
RR souhaité : 2.0 à 3.0 (ciblez des ratios plus élevés sur des mouvements moins fréquents).
Résultat attendu : Maximisation des profits sur des tendances claires.
Recommandation Générale :
Si vous ne savez pas par où commencer, utilisez ces paramètres par défaut :
ATR Length : 14
Multiplicateur SL : 1.5
RR souhaité : 2.0
MACD, ADX & RSI -> for altcoins# MACD + ADX + RSI Combined Indicator
## Overview
This advanced technical analysis tool combines three powerful indicators (MACD, ADX, and RSI) into a single view, providing a comprehensive analysis of trend, momentum, and divergence signals. The indicator is designed to help traders identify potential trading opportunities by analyzing multiple aspects of price action simultaneously.
## Components
### 1. MACD (Moving Average Convergence Divergence)
- **Purpose**: Identifies trend direction and momentum
- **Components**:
- Fast EMA (default: 12 periods)
- Slow EMA (default: 26 periods)
- Signal Line (default: 9 periods)
- Histogram showing the difference between MACD and Signal line
- **Visual**:
- Blue line: MACD line
- Orange line: Signal line
- Green/Red histogram: MACD histogram
- **Interpretation**:
- Histogram color changes indicate potential trend shifts
- Crossovers between MACD and Signal lines suggest entry/exit points
### 2. ADX (Average Directional Index)
- **Purpose**: Measures trend strength and direction
- **Components**:
- ADX line (default threshold: 20)
- DI+ (Positive Directional Indicator)
- DI- (Negative Directional Indicator)
- **Visual**:
- Navy blue line: ADX
- Green line: DI+
- Red line: DI-
- **Interpretation**:
- ADX > 20 indicates a strong trend
- DI+ crossing above DI- suggests bullish momentum
- DI- crossing above DI+ suggests bearish momentum
### 3. RSI (Relative Strength Index)
- **Purpose**: Identifies overbought/oversold conditions and divergences
- **Components**:
- RSI line (default: 14 periods)
- Divergence detection
- **Visual**:
- Purple line: RSI
- Horizontal lines at 70 (overbought) and 30 (oversold)
- Divergence labels ("Bull" and "Bear")
- **Interpretation**:
- RSI > 70: Potentially overbought
- RSI < 30: Potentially oversold
- Bullish/Bearish divergences indicate potential trend reversals
## Alert System
The indicator includes several automated alerts:
1. **MACD Alerts**:
- Rising to falling histogram transitions
- Falling to rising histogram transitions
2. **RSI Divergence Alerts**:
- Bullish divergence formations
- Bearish divergence formations
3. **ADX Trend Alerts**:
- Strong trend development (ADX crossing threshold)
- DI+ crossing above DI- (bullish)
- DI- crossing above DI+ (bearish)
## Settings Customization
All components can be fine-tuned through the settings panel:
### MACD Settings
- Fast Length
- Slow Length
- Signal Smoothing
- Source
- MA Type options (SMA/EMA)
### ADX Settings
- Length
- Threshold level
### RSI Settings
- RSI Length
- Source
- Divergence calculation toggle
## Usage Guidelines
### Entry Signals
Strong entry signals typically occur when multiple components align:
1. MACD histogram color change
2. ADX showing strong trend (>20)
3. RSI showing divergence or leaving oversold/overbought zones
### Exit Signals
Consider exits when:
1. MACD crosses signal line in opposite direction
2. ADX shows weakening trend
3. RSI reaches extreme levels with divergence
### Risk Management
- Use the indicator as part of a complete trading strategy
- Combine with price action and support/resistance levels
- Consider multiple timeframe analysis for confirmation
- Don't rely solely on any single component
## Technical Notes
- Built for TradingView using Pine Script v5
- Compatible with all timeframes
- Optimized for real-time calculation
- Includes proper error handling and NA value management
- Memory-efficient calculations for smooth performance
## Installation
1. Copy the provided Pine Script code
2. Open TradingView Chart
3. Create New Indicator -> Pine Editor
4. Paste the code and click "Add to Chart"
5. Adjust settings as needed through the indicator settings panel
## Version Information
- Version: 2.0
- Last Updated: November 2024
- Platform: TradingView
- Language: Pine Script v5
USDT.D Volatility TrackerUSDT.D Volatility Tracker
Description:
This script is designed to track the volatility of USDT.D (US Dollar in cryptocurrency) on the TradingView platform. It uses a moving average and deviation from it to generate buy and sell signals, helping traders visualize changes in volatility and make informed decisions.
Input Parameters:
maPeriod: The period of the moving average (default 120). This parameter allows users to adjust the length of the period used to calculate the moving average.
devThreshold: The deviation threshold (default 0.6). This parameter defines the level of deviation that will trigger buy or sell signals.
Data Request:
The script requests closing data for USDT.D using the request.security function, allowing it to retrieve up-to-date data on the selected timeframe.
Moving Average and Deviation Calculation:
An exponential moving average (EMA) is used to calculate the deviation from the moving average, enabling the identification of current volatility.
Deviation Line Display:
The deviation rate line is displayed on the chart, allowing users to visually track changes in volatility.
Signal Generation:
If the deviation exceeds the set threshold (devThreshold), a buy signal is generated (green background).
If the deviation falls below the negative threshold (-devThreshold), a sell signal is generated (red background).
Visual Signals:
Buy signals are displayed on the chart as green triangles, while sell signals are displayed as red triangles. This helps traders quickly identify potential entry and exit points.
Truly Iterative Gaussian ChannelOVERVIEW
The Truly Iterative Gaussian Channel is a robust channeling system that integrates a Gaussian smoothing kernel with a rolling standard deviation to create dynamically adaptive upper and lower boundaries around price. This indicator provides a smooth, yet responsive representation of price movements while minimizing lag and dynamically adjusting channel width to reflect real-time market volatility. Its versatility makes it effective across various timeframes and trading styles, offering significant potential for experimentation and integration into advanced trading systems.
TRADING USES
The Gaussian indicator can be used for multiple trading strategies. Trend following relies on the middle Gaussian line to gauge trend direction: prices above this line indicate bullish momentum, while prices below signal bearish momentum. The upper and lower boundaries act as dynamic support and resistance levels, offering breakout or pullback entry opportunities. Mean reversion focuses on identifying reversal setups when price approaches or breaches the outer boundaries, aiming for a return to the Gaussian centerline. Volatility filtering helps assess market conditions, with narrow channels indicating low volatility or consolidation and suggesting fewer trading opportunities or an impending breakout. Adaptive risk management uses channel width to adjust for market volatility, with wider channels signaling higher risk and tighter channels indicating lower volatility and potentially safer entry points.
THEORY
Gaussian kernel smoothing, derived from the Gaussian normal distribution, is a cornerstone of probability and statistics, valued for its ability to reduce noise while preserving critical signal features. In this indicator, it ensures price movements are smoothed with precision, minimizing distortion while maintaining responsiveness to market dynamics.
The rolling standard deviation complements this by dynamically measuring price dispersion from the mean, enabling the channel to adapt in real time to changing market conditions. This combination leverages the mathematical correctness of both tools to balance smoothness and adaptability.
An iterative framework processes data efficiently, bar by bar, without recalculating historical value to ensure reliability and preventing repainting to create a mathematically grounded channel system suitable for a wide range of market environments.
The Gaussian channel excels at filtering noise while remaining responsive to price action, providing traders with a dependable tool for identifying trends, reversals, and volatility shifts with consistency and precision.
CALIBRATION
Calibration of the Gaussian channel involves adjusting its length to modify sensitivity and adaptability based on trading style. Shorter lengths (e.g., 50-100) are ideal for intraday traders seeking quick responses to price fluctuations. Medium lengths (e.g., 150-200) cater to swing traders aiming to capture broader market trends. Longer lengths (e.g., 250-400+) are better suited for positional traders focusing on long-term price movements and stability.
MARKET USAGE
Stock, Forex, Crypto, Commodities, and Indices.
Bull Bear Candles with Volume ProfileUser Guide for Bull Bear Candles Indicator with Keltner Channels
Author: NellyN
Introduction
This indicator helps identify potential bullish and bearish trends in the market by analyzing buying and selling volume over two configurable timeframes. It calculates the percentage of buying and selling volume and displays the current market condition based on two moving averages for 2 periods.
Key Features
• Volume Analysis : Calculates Buy and Sell Volume for two configurable timeframes (e.g., 5 min, 15 min, 15 min. and 1 hour, etc.) and displays them as percentages.
• Moving Averages : Uses one Moving Average (MA) for two different time periods to identify trends (uptrend when shorter-term MA is above longer-term MA). You can also choose other Moving Average types like SMA, EMA, WMA, RMA, VWMA, or HMA.
• Colored Candles : Candles are colored green for bullish conditions, red for bearish conditions, and gray for neutral conditions.
• Market Condition Labels : Displays labels in table-view indicating the current market condition based on Buy and Sell Volume (Very Bullish, Very Bearish, Bullish/Bearish Retracement, Chop).
• Alerts: Generates alerts for potential buy and sell signals based on indicator conditions (Note: Enable alerts in the indicator settings).
• Visual Signals: Provides visual signals through colored candles and market condition labels in addition to alerts.
Input Parameters
• Source: Close price (default) or Heikin Ashi
• Timeframe: Select the timeframe for price and volume data used in the indicator (e.g., Daily, Hourly).
• Colored Candles On: Enable (True) or disable (False) coloring candles based on market conditions.
• Enable Alerts: Enable (True) or disable (False) alerts for buy/sell signals.
• Length of MA: Sets the length for the MAs used in trend identification (minimum 1).
• Lookback Period Vol. 1 & 2: Define the timeframes used to calculate buying and selling volume and the MA calculation (e.g., 5 min, 15 min).
Understanding the Outputs
• Cloud Fill: The area between two MAs is filled with a color that reflects the trend (green for uptrend, red for downtrend).
• Table: Shows Buy Volume, Sell Volume, Buy Percentage, Sell Percentage, and the current Market Condition Labels. (If you decide to see them uncomment them from the code simply removing the // in front of the code)
• Colored Candles and Market Condition Labels: Look for green candles and bullish labels for potential buying opportunities, and vice versa for red candles and bearish labels.
Bullish green label appears when short-term MA is above long-term MA AND Buy Volume percentage is greater than 50%.
Red cross for exiting long entry appears when we have bearish volume OR bearish crossover of the MA for the 2 periods.
Bearish red label appears when short-term MA is below long-term MA AND Buy Volume percentage is less than 50%.
Green cross for exiting short entry appears when we have bullish volume OR bullish crossover of the MA for the 2 periods.
• Bullish/Bearish Retracement: The moving averages indicate a potential trend reversal, while the Buy Volume percentage suggests a continuation of the prior trend. The candle color may be green, red, or gray depending on the current price position relative to the moving averages.
• Chop (Gray Candle): The moving averages are flat and the Buy Volume percentage is not significantly above or below 50%.
• Buy/Sell Alerts: The indicator generates alerts based on specific conditions, but these should be used in conjunction with other trading strategies and careful risk management.
Important Notes
• This indicator is for informational purposes only and should not be considered financial advice. Back-test the indicator with historical data to understand its performance before using it for live trading.
• Combine this indicator with other technical analysis tools.
ORB Screener with Trailing SLThis is an extension to our already published script ORB with ATR Trailing SL indicator
Many people requested to add screener to the existing indicator but since it's slowing down the performance heavily, we decided to add this as a separate screener.
Note: This screener does NOT plot the chart and so you want to have both plotting and screener, use both scripts together.
Overview:
The ORB Screener is a TradingView indicator designed to assist traders in identifying breakout opportunities based on the Opening Range Breakout (ORB) strategy. It features multi-symbol screening, customizable session timeframes, and a detailed table for quick visual reference and stock scanning.
The ORB Screener utilizes the ORB strategy to calculate breakout levels for multiple symbols. It identifies the high and low during a specified session (e.g., first 5 minutes after market open) and provides insights on whether the price is above the high (bullish), below the low (bearish), or between the range (neutral).
Additionally, the script calculates and displays the RSI values for each symbol, aiding traders in assessing momentum alongside breakout status.
Note: One can add up to 40 symbols for screening the stocks.
Key Features and Inputs:
ORB Session Time: Define a specific timeframe (e.g., "0915-0920") during which the ORB high and low are calculated. This serves as the foundation for identifying breakouts.
Multi-Symbol Screening: Screen up to 40 symbols at once, enabling you to monitor multiple opportunities without switching charts.
Breakout Validation:
Select from two methods for confirming a breakout: Close (based on closing prices) or Touch (based on intraday highs/lows).
Breakout Status Indicators:
Above High: Indicates a current bullish breakout when the price exceeds the ORB high.
Below Low: Indicates a current bearish breakout when the price falls below the ORB low.
Between Range: Indicates no breakout (price remains within the range).
RSI Integration : Calculates the RSI for each symbol to help traders evaluate momentum alongside breakout signals.
Customizable Table Display:
Position: Place the data table at the top, middle, or bottom of the chart and align it left, center, or right.
Size: Choose from multiple table size options for optimal visibility (Auto, Huge, Large, Normal, Small, Tiny).
Visual Feedback:
Green Background: Indicates a breakout happened at least once above the ORB high.
Red Background: Indicates a breakout happened at least once below the ORB low.
Gray Background: Indicates price is within the ORB range.
Bayesian Price Projection Model [Pinescriptlabs]📊 Dynamic Price Projection Algorithm 📈
This algorithm combines **statistical calculations**, **technical analysis**, and **Bayesian theory** to forecast a future price while providing **uncertainty ranges** that represent upper and lower bounds. The calculations are designed to adjust projections by considering market **trends**, **volatility**, and the historical probabilities of reaching new highs or lows.
Here’s how it works:
🚀 Future Price Projection
A dynamic calculation estimates the future price based on three key elements:
1. **Trend**: Defines whether the market is predisposed to move up or down.
2. **Volatility**: Quantifies the magnitude of the expected change based on historical fluctuations.
3. **Time Factor**: Uses the logarithm of the projected period (`proyeccion_dias`) to adjust how time impacts the estimate.
🧠 **Bayesian Probabilistic Adjustment**
- Conditional probabilities are calculated using **Bayes' formula**:
\
This models future events using conditional information:
- **Probability of reaching a new all-time high** if the price is trending upward.
- **Probability of reaching a new all-time low** if the price is trending downward.
- These probabilities refine the future price estimate by considering:
- **Higher volatility** increases the likelihood of hitting extreme levels (highs/lows).
- **Market trends** influence the expected price movement direction.
🌟 **Volatility Calculation**
- Volatility is measured using the **ATR (Average True Range)** indicator with a 14-period window. This reflects the average amplitude of price fluctuations.
- To express volatility as a percentage, the ATR is normalized by dividing it by the closing price and multiplying it by 200.
- Volatility is then categorized into descriptive levels (e.g., **Very Low**, **Low**, **Moderate**, etc.) for better interpretation.
---
🎯 **Deviation Limits (Upper and Lower)**
- The upper and lower limits form a **projected range** around the estimated future price, providing a framework for uncertainty.
- These limits are calculated by adjusting the ATR using:
- A user-defined **multiplier** (`factor_desviacion`).
- **Bayesian probabilities** calculated earlier.
- The **square root of the projected period** (`proyeccion_dias`), incorporating the principle that uncertainty grows over time.
🔍 **Interpreting the Model**
This can be seen as a **dynamic probabilistic model** that:
- Combines **technical analysis** (trends and ATR).
- Refines probabilities using **Bayesian theory**.
- Provides a **visual projection range** to help you understand potential future price movements and associated uncertainties.
⚡ Whether you're analyzing **volatile markets** or confirming **bullish/bearish scenarios**, this tool equips you with a robust, data-driven approach! 🚀
Español :
📊 Algoritmo de Proyección de Precio Dinámico 📈
Este algoritmo combina **cálculos estadísticos**, **análisis técnico** y **la teoría de Bayes** para proyectar un precio futuro, junto con rangos de **incertidumbre** que representan los límites superior e inferior. Los cálculos están diseñados para ajustar las proyecciones considerando la **tendencia del mercado**, **volatilidad** y las probabilidades históricas de alcanzar nuevos máximos o mínimos.
Aquí se explica su funcionamiento:
🚀 **Proyección de Precio Futuro**
Se realiza un cálculo dinámico del precio futuro estimado basado en tres elementos clave:
1. **Tendencia**: Define si el mercado tiene predisposición a subir o bajar.
2. **Volatilidad**: Determina la magnitud del cambio esperado en función de las fluctuaciones históricas.
3. **Factor de Tiempo**: Usa el logaritmo del período proyectado (`proyeccion_dias`) para ajustar cómo el tiempo afecta la estimación.
🧠 **Ajuste Probabilístico con la Teoría de Bayes**
- Se calculan probabilidades condicionales mediante la fórmula de **Bayes**:
\
Esto permite modelar eventos futuros considerando información condicional:
- **Probabilidad de alcanzar un nuevo máximo histórico** si el precio sube.
- **Probabilidad de alcanzar un nuevo mínimo histórico** si el precio baja.
- Estas probabilidades ajustan la estimación del precio futuro considerando:
- **Mayor volatilidad** aumenta la probabilidad de alcanzar niveles extremos (máximos/mínimos).
- **La tendencia del mercado** afecta la dirección esperada del movimiento del precio.
🌟 **Cálculo de Volatilidad**
- La volatilidad se mide usando el indicador **ATR (Average True Range)** con un período de 14 velas. Este indicador refleja la amplitud promedio de las fluctuaciones del precio.
- Para obtener un valor porcentual, el ATR se normaliza dividiéndolo por el precio de cierre y multiplicándolo por 200.
- Además, se clasifica esta volatilidad en categorías descriptivas (e.g., **Muy Baja**, **Baja**, **Moderada**, etc.) para facilitar su interpretación.
🎯 **Límites de Desviación (Superior e Inferior)**
- Los límites superior e inferior representan un **rango proyectado** en torno al precio futuro estimado, proporcionando un marco para la incertidumbre.
- Estos límites se calculan ajustando el ATR según:
- Un **multiplicador** definido por el usuario (`factor_desviacion`).
- Las **probabilidades condicionales** calculadas previamente.
- La **raíz cuadrada del período proyectado** (`proyeccion_dias`), lo que incorpora el principio de que la incertidumbre aumenta con el tiempo.
---
🔍 **Interpretación del Modelo**
Este modelo se puede interpretar como un **modelo probabilístico dinámico** que:
- Integra **análisis técnico** (tendencias y ATR).
- Ajusta probabilidades utilizando **la teoría de Bayes**.
- Proporciona un **rango de proyección visual** para ayudarte a entender los posibles movimientos futuros del precio y su incertidumbre.
⚡ Ya sea que estés analizando **mercados volátiles** o confirmando **escenarios alcistas/bajistas**, ¡esta herramienta te ofrece un enfoque robusto y basado en datos! 🚀
Power Of 3 ICT 01 [TradingFinder] AMD ICT & SMC Accumulations🔵 Introduction
The ICT Power of 3 (PO3) strategy, developed by Michael J. Huddleston, known as the Inner Circle Trader, is a structured approach to analyzing daily market activity. This strategy divides the trading day into three distinct phases: Accumulation, Manipulation, and Distribution.
Each phase represents a unique market behavior influenced by institutional traders, offering a clear framework for retail traders to align their strategies with market movements.
Accumulation (19:00 - 01:00 EST) takes place during low-volatility hours, as institutional traders accumulate orders. Manipulation (01:00 - 07:00 EST) involves false breakouts and liquidity traps designed to mislead retail traders. Finally, Distribution (07:00 - 13:00 EST) represents the active phase where significant market movements occur as institutions distribute their positions in line with the broader trend.
This indicator is built upon the Power of 3 principles to provide traders with a practical and visual tool for identifying these key phases. By using clear color coding and precise time zones, the indicator highlights critical price levels, such as highs and lows, helping traders to better understand market dynamics and make more informed trading decisions.
Incorporating the ICT AMD setup into daily analysis enables traders to anticipate market behavior, spot high-probability trade setups, and gain deeper insights into institutional trading strategies. With its focus on time-based price action, this indicator simplifies complex market structures, offering an effective tool for traders of all levels.
🔵 How to Use
The ICT Power of 3 (PO3) indicator is designed to help traders analyze daily market movements by visually identifying the three key phases: Accumulation, Manipulation, and Distribution.
Here's how traders can effectively use the indicator :
🟣 Accumulation Phase (19:00 - 01:00 EST)
Purpose : Identify the range-bound activity where institutional players accumulate orders.
Trading Insight : Avoid placing trades during this phase, as price movements are typically limited. Instead, use this time to prepare for the potential direction of the market in the next phases.
🟣 Manipulation Phase (01:00 - 07:00 EST)
Purpose : Spot false breakouts and liquidity traps that mislead retail traders.
Trading Insight : Observe the market for price spikes beyond key support or resistance levels. These moves often reverse quickly, offering high-probability entry points in the opposite direction of the initial breakout.
🟣 Distribution Phase (07:00 - 13:00 EST)
Purpose : Detect the main price movement of the day, driven by institutional distribution.
Trading Insight : Enter trades in the direction of the trend established during this phase. Look for confirmations such as breakouts or strong directional moves that align with broader market sentiment
🔵 Settings
Show or Hide Phases :mDecide whether to display Accumulation, Manipulation, or Distribution.
Adjust the session times for each phase :
Accumulation: 1900-0100 EST
Manipulation: 0100-0700 EST
Distribution: 0700-1300 EST
Modify Visualization : Customize how the indicator looks by changing settings like colors and transparency.
🔵 Conclusion
The ICT Power of 3 (PO3) indicator is a powerful tool for traders seeking to understand and leverage market structure based on time and price dynamics. By visually highlighting the three key phases—Accumulation, Manipulation, and Distribution—this indicator simplifies the complex movements of institutional trading strategies.
With its customizable settings and clear representation of market behavior, the indicator is suitable for traders at all levels, helping them anticipate market trends and make more informed decisions.
Whether you're identifying entry points in the Accumulation phase, navigating false moves during Manipulation, or capitalizing on trends in the Distribution phase, this tool provides valuable insights to enhance your trading performance.
By integrating this indicator into your analysis, you can better align your strategies with institutional movements and improve your overall trading outcomes.
Naji's Price Change DetectorThis indicator detects when the price goes up or down by a customizable % and time. This allows the user to detect large changes in the market in order to try to catch the reversal.
This does not detect the reversal, you need to decide when to enter the trade yourself.
Key Features:
Customizable Settings:
Percent Change Threshold: You can change this in the settings panel (default = 4%).
Number of Bars to Check: Adjustable between 1 and any desired number of bars (default = 5).
Dynamic Calculation:
The script calculates the price change for every bar within the specified range.
Alerts:
Alerts are customized to reflect the chosen settings and will trigger only once per bar close.
Background Highlights:
Green: A price increase exceeding the threshold was detected.
Red: A price decrease exceeding the threshold was detected.
Advanced Pivot Manipulation SuperTrend - Consolidation ZoneHere’s the description translated into English for your TradingView publication:
---
Advanced Pivot Manipulation SuperTrend - Consolidation Zone
Description :
This advanced indicator combines multiple technical tools to provide a comprehensive analysis of trends, key levels, and consolidation zones. Ideal for traders seeking to spot opportunities while avoiding the traps of flat markets, it helps you better understand market dynamics and improve your trading decisions.
Key Features:
1.
Dynamic SuperTrend with Pivot Points:
- An enhanced SuperTrend algorithm based on pivot points for more precise trend tracking.
- Thresholds (Up/Dn) are dynamically adjusted using ATR (Average True Range) for improved volatility adaptation.
2. Consolidation Zones:
- Automatically identifies periods when the market moves within a narrow range (1% by default).
- Consolidation zones are visually highlighted to help avoid risky trades.
3. Dynamic Support and Resistance:
- Automatically calculates support and resistance levels based on a rolling period (configurable).
- These levels serve as key references for potential breakouts or trend reversals.
4. Advanced Detection Tools:
- Includes a volume multiplier and shadow-to-body ratio to signal unusual or potentially manipulated moves (e.g., spoofing).
5. Intuitive Visuals:
- SuperTrend lines are color-coded to indicate bullish (green) or bearish (red) trends.
- Semi-transparent lines mark support and resistance levels, and red backgrounds indicate consolidation zones.
Customizable Parameters:
- Pivot Point Period: Adjust the period for detecting pivot highs and lows.
- ATR Factor and Period: Control the sensitivity of the SuperTrend indicator.
- Lookback Period for S/R: Define the duration for calculating support and resistance levels.
- Volume Multiplier and Shadow/Body Ratio: Configure thresholds for detecting high volumes or anomalies in candlestick patterns.
How to Use:
- Easily identify dominant trends using the SuperTrend.
- Spot consolidation zones to avoid inefficient trades or prepare breakout strategies.
- Use support and resistance levels as reference points for placing orders or adjusting risk management.
Target Audience:
- Intraday and swing traders.
- Anyone looking for a comprehensive and customizable indicator to effectively analyze volatile markets.
---
Notes:
The indicator is fully customizable to suit your needs and strategies. Feel free to experiment with the parameters to maximize its effectiveness according to your trading style.
Keywords: SuperTrend, Support and Resistance, Consolidation, Pivot Points, Trends, ATR, Advanced Trading.
---
This description highlights the indicator’s strengths and is designed to appeal to the TradingView community.
Volatility % (Standard Deviation of Returns)This script takes closing prices of candles to measure the Standard Deviation (σ) which is then used to calculate the volatility by taking the stdev of the last 30 candles and multiplying it by the root of the trading days in a year, month and week. It then multiplies that number by 100 to show a percentage.
Default settings are annual volatility (252 candles, red), monthly volatility (30 candles, blue) and weekly volatility (5 candles, green) if you use daily candles. It is open source so you can increase the number of candles with which the stdev is calculated, and change the number of the root that multiplies the stdev.
