Market Structure (Intrabar) [LuxAlgo]The Market Structure (Intrabar) indicator is designed to automatically detect and highlight real-time intrabar market structures, a core component of the Smart Money Concepts methodology.
🔶 USAGE
The proposed indicator gives a detailed picture of the most recent candle lower timeframe trends, highlighting market structures within them.
This can be particularly useful to assess the price dynamic within the most recent candle. For example, we can see how pronounced a trend is by the number of opposite bullish/bearish market structures formed within the candle.
Users can select the intrabar timeframe of interest from the "Intrabar Timeframe" setting, using a timeframe significantly lower than the chart timeframe will return more intrabar candles and potentially more market structures.
🔹 Dashboard
Users have access to a dashboard returning useful statistics such as the number of formed CHoCH's and BOS's from the intrabar prices. These can be indicative of how predominant a trend is within the intrabar data or if there exist multiple trends.
🔶 DETAILS
Market structures allow determining trend continuations as well as trend reversals in the market through two distinct structures:
🔹 Change of Character (CHoCH)
A change of character (CHoCH) refers to a shift in the market behavior of a security that is driven by changes in the underlying supply and demand dynamics. CHoCH's are indicative of confirmed reversals.
🔹 Break of Structure (BoS)
The break of structure (BoS) refers to the point at which a key level of support or resistance is broken. BOS's are indicative of confirmed trend continuations.
🔶 SETTINGS
🔹Inside the Bar Market Structure
Intrabar Timeframe: Lower timeframe setting option, if set to 'Auto' the script will determine the lower timeframe based on the chart timeframe.
Intrabar Market Structure, Length: Toggles the visibility of the break of structures and change of characters. Length defines the detection length of the swing levels.
Intrabar Swing Levels: Toggles the visibility of the swing levels, including a color customization option for highs and lows.
Intrabar Statistics: Toggles the visibility of the dashboard. Some further statistical details are presented in the tooltips of the table cells
🔹 General
Market Structure Colors: Color customization option for the break of structure and change of character lines and labels.
Intrabar Candle Colors: Color customization option for intrabar candles.
Intrabar Candles Horizontal Offset: Adjusting the intrabar candles horizontal position
Dashboard: Dashboard position and size customization option
🔶 LIMITATIONS
Please note that seconds-based intervals are available for premium and professional plan holders, which implies that the seconds-based intervals usage of the indicator may not be available for all users depending on their subscription plan.
🔶 RELATED SCRIPTS
Smart-Money-Concepts
ICT-Concepts
Поиск скриптов по запросу "change"
Momentum Acceleration by DGTItalian physicist Galileo Galilei is usually credited with being the first to measure speed by considering the distance covered and the time it takes. Galileo defined speed as the distance covered during a period of time. In equation form, that is v = Δd / Δt where v is speed, Δd is change in distance, and Δt is change in time. The Greek symbol for delta, a triangle (Δ), means change.
Is the speed getting faster or slower?
Acceleration will be the answer, acceleration is defined as the rate of change of speed over a set period of time, meaning something is getting faster or slower. Mathematically expressed, acceleration denoted as a is a = Δv / Δt , where Δv is the change in speed and Δt is the change in time.
How to apply in trading
Lets think about Momentum, Rate of Return, Rate of Change all are calculated in almost same approach with Speed
Momentum measures change in price over a specified time period,
Rate of Change measures percent change in price over a specified time period,
Rate of Return measures the net gain or loss over a specified time period,
And Speed measures change in distance over a specified time period
So we may state that measuring the change in distance is also measuring the change in price over a specified time period which is length, hence
speed can be calculated as (source – source )/length and acceleration becomes (speed – speed )/length
In this study acceleration is used as signal line and result plotted as arrows demonstrating bull or bear direction where direction changes can be considered as trading setups
Just a little fun, since we deal with speed the short name of the study is named after famous cartoon character Speedy Gonzales
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer: The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
BD RSI & STOCH RSI BAR COLOR CHANGERA simple indicator displaying RSI and STOCHASTIC RSI combined in the one indicator. This indicator also changes the bar colour to yellow when it meets the overbrought conditions of both the RSI and the STOCH RSI and changes the bar colour to black when it meets the oversold conditions of both the RSI and STOCH RSI. The values of these conditions are set as the regular defaults but can be changed in the input settings to suit different time frames and user requirements. This does NOT generate signals but simply shows when both the RSI & STOCH RSI are oversold or overbrought.
EPS QoQ % ChangeThis indicator calculates and displays the quarter-over-quarter (QoQ) percentage change in earnings per share (EPS) directly on your chart, aligned with each earnings event.
It is designed to quickly highlight EPS growth or decline without the need to open an earnings report, providing traders and investors with instant, visual performance context.
Features :
- Automatic Earnings Detection: Identifies earnings bars and calculates QoQ % change.
- Color-Coded Text: Positive changes are shown in your chosen “up” color, declines in your “down” color, and flat results in a neutral color.
- Customizable Appearance: Choose text size and colors to match your chart style.
- Tooltip Support: Optional detailed tooltip showing reported EPS, previous EPS, and calculated QoQ change.
- Compact Layout: Displays in its own pane to avoid cluttering price action.
Use Cases :
- Quickly assess EPS growth trends over time.
- Spot significant earnings beats or misses without reading earnings transcripts.
- Use alongside other technical or fundamental tools for better decision-making.
Rate of Change of OBV with RSI ColorThis indicator combines three popular tools in technical analysis : On-Balance Volume (OBV), Rate of Change (ROC), and Relative Strength Index (RSI). It aims to monitor momentum and potential trend reversals based on volume and price changes.
Calculation:
ROC(OBV) = ((OBV(today) - OBV(today - period)) / OBV(today - period)) * 100
This calculates the percentage change in OBV over a specific period. A positive ROC indicates an upward trend in volume, while a negative ROC suggests a downward trend.
What it Monitors:
OBV: Tracks the volume flow associated with price movements. Rising OBV suggests buying pressure, while falling OBV suggests selling pressure.
ROC of OBV:
Measures the rate of change in the OBV, indicating if the volume flow is accelerating or decelerating.
RSI: Measures the strength of recent price movements, indicating potential overbought or oversold conditions.
How it can be Used:
Identifying Trend Continuation: Rising ROC OBV with a rising RSI might suggest a continuation of an uptrend, especially if the color is lime (RSI above 60).
Identifying Trend Reversal: Falling ROC OBV with a declining RSI might suggest a potential trend reversal, especially if the color approaches blue (RSI below 40).
Confirmation with Threshold: The horizontal line (threshold) can be used as a support or resistance level. Bouncing ROC OBV off the threshold with a color change could suggest a pause in the trend but not necessarily a reversal.
When this Indicator is Useful:
This indicator can be useful for assets with strong volume activity, where tracking volume changes provides additional insights.
It might be helpful during periods of consolidation or trend continuation to identify potential breakouts or confirmations.
Multi-Timeframe EMA Distance & % Change TableDescription of Multi-Timeframe EMA Distance & % Change Table
The Multi-Timeframe EMA Distance & % Change Table indicator is designed to display the distance and percentage change between the current price and the Exponential Moving Averages (EMAs) on multiple timeframes. It creates a table to show these values, with customizable options for decimal precision .
Key Features:
Inputs:
- Timeframes (tf1, tf2, tf3, tf4): User-defined timeframes for EMA calculations (e.g., 1 minute, 15 minutes, daily, etc.).
- EMA Levels (emaLevel, emaLevel2, emaLevel3): User-defined periods for three different EMAs.
EMA Calculations:
- Computes EMAs for the specified levels (50, 100, 200) on each of the user-selected timeframes.
Plotting:
- Plots the EMAs on the chart with distinct colors: Orange, Teal, and Green for different EMAs.
Display Options:
- Checkbox (displayAsPercentage): Allows the user to toggle between displaying distances or percentage changes.
- Decimal Precision:
- decimalPlacesDistance: Specifies the number of decimal places for rounded distance values.
- decimalPlacesPercentage: Specifies the number of decimal places for rounded percentage values.
Table Creation:
- Location: Table is placed in the top-right corner of the chart.
- Headers: Includes columns for each timeframe and EMA distance/percentage.
Distance and Percentage Calculations:
- Distances: Calculated as the difference between the current price and the EMA values for each timeframe.
- Percentages: Calculated as the distance divided by the EMA value, converted to a percentage.
Decimal Rounding:
- Custom Rounding Function: Ensures that distance and percentage values are displayed with the user-specified number of decimal places.
Color Coding:
- Distance Values: Colored green if positive, red if negative.
- Table Entries: Display either the rounded distance or percentage, based on user selection.
Table Update:
- The table is dynamically updated with either distance or percentage values based on the user's choice and rounded to the specified number of decimal places.
This indicator provides a comprehensive overview of EMA distances and percentage changes across multiple timeframes, with detailed control over the precision of the displayed values.
DTFX Algo Zones [LuxAlgo]DTFX Algo Zones are auto-generated Fibonacci Retracements based on market structure shifts.
These retracement levels are intended to be used as support and resistance levels to look for price to bounce off of to confirm direction.
🔶 USAGE
Due to the retracement levels only being generated from identified market structure shifts, the retracements are confined to only draw from areas considered more important due to the technical Break of Structure (BOS) or Change of Character (CHoCH).
The simple action that causes a market structure shift occurs is price breaking above or below a specific swing point. When a market structure shift happens, a retracement is drawn from the point of break to the highest or lowest point since that point. Due to the price action necessary for a market structure shift, these retracements will not always be immediately actionable.
These retracement levels are intended to be used as points to watch for price to retrace to and bounce from, confirming the current direction of price.
In the example below, after the retracement is initiated, by bouncing off of the retracement levels formed from the previous market structure shift it would further confirm the bias of the market structure shift. A break going through these levels would display a weakness from the current market structure shift, implying that it could simply be noise.
🔶 DETAILS
The script uses standard SMC Market structure identification to determine Break of Structures (BOS) and Change of Characters (CHoCH). The specific swing points can be identified by the shapes placed above or below the specific swing high/low candle.
By unchecking the "Display All Zones" setting, users are able to specify the exact number of retracement zones to display using the "Show Last" parameter. This is handy for cleaning up the chart to stay focused on the most recent retracements.
Additionally, when displaying multiple zones, the "Clean-Up Level Overlap" setting may be helpful for decluttering as well. This option optimizes the display of retracement levels to minimize their overlap on other adjacent zones.
The script allows for up to 5 Fib levels to be displayed from each zone, with options for display, value, line style, and color for each of the 5.
The calculation for Fib Levels changes depending on the direction of market structure shifts. When an upwards (Bullish) zone is generated, the retracement is drawn with the bottom of the zone being 0 and the top of the zone being 1. This is reversed for downwards (Bearish) zones.
🔶 SETTINGS
Structure Length: Sets the SMC structure length to use for finding MMS.
Show Last: Displays this number of retracement zones. (Display All Zones Must be Unchecked)
Display All Zones: Ignores "Show Last" number and displays all historical MMS Retracement Zones.
Zone Display: Choose which zones to display, only bearish, only bullish, or both.
Clean-Up Level Overlap: Minimizes overlap between adjacent zones and levels.
Fib Levels: Settings to display and customize up to 5 Fib levels for each zone.
BDC - Bitcoin (BTC) Dominance Change [Logue]Bitcoin Dominance Change. Interesting things tend to happen when the Bitcoin dominance increases or decreases rapidly. Perhaps because there is overexuberance in the market in either BTC or the alts. In back testing, I found a rapid 13-day change in dominance indicates interesting switches in the BTC trends. Prior to 2019, the indicator doesn't work as well to signal trend shifts (i.e., local tops and bottoms) likely based on very few coins making up the crypto market.
The BTC dominance change is calculated as a percentage change of the daily dominance. You are able to change the upper bound, lower bound, and the period (daily) of the indicator to your own preferences. The indicator going above the upper bound or below the lower bound will trigger a different background color.
Use this indicator at your own risk. I make no claims as to its accuracy in forecasting future trend changes of Bitcoin.
Optimal Length BackTester [YinYangAlgorithms]This Indicator allows for a ‘Optimal Length’ to be inputted within the Settings as a Source. Unlike most Indicators and/or Strategies that rely on either Static Lengths or Internal calculations for the length, this Indicator relies on the Length being derived from an external Indicator in the form of a Source Input.
This may not sound like much, but this application may allows limitless implementations of such an idea. By allowing the input of a Length within a Source Setting you may have an ‘Optimal Length’ that adjusts automatically without the need for manual intervention. This may allow for Traditional and Non-Traditional Indicators and/or Strategies to allow modifications within their settings as well to accommodate the idea of this ‘Optimal Length’ model to create an Indicator and/or Strategy that adjusts its length based on the top performing Length within the current Market Conditions.
This specific Indicator aims to allow backtesting with an ‘Optimal Length’ inputted as a ‘Source’ within the Settings.
This ‘Optimal Length’ may be used to display and potentially optimize multiple different Traditional Indicators within this BackTester. The following Traditional Indicators are included and available to be backtested with an ‘Optimal Length’ inputted as a Source in the Settings:
Moving Average; expressed as either a: Simple Moving Average, Exponential Moving Average or Volume Weighted Moving Average
Bollinger Bands; expressed based on the Moving Average Type
Donchian Channels; expressed based on the Moving Average Type
Envelopes; expressed based on the Moving Average Type
Envelopes Adjusted; expressed based on the Moving Average Type
All of these Traditional Indicators likewise may be displayed with multiple ‘Optimal Lengths’. They have the ability for multiple different ‘Optimal Lengths’ to be inputted and displayed, such as:
Fast Optimal Length
Slow Optimal Length
Neutral Optimal Length
By allowing for the input of multiple different ‘Optimal Lengths’ we may express the ‘Optimal Movement’ of such an expressed Indicator based on different Time Frames and potentially also movement based on Fast, Slow and Neutral (Inclusive) Lengths.
This in general is a simple Indicator that simply allows for the input of multiple different varieties of ‘Optimal Lengths’ to be displayed in different ways using Tradition Indicators. However, the idea and model of accepting a Length as a Source is unique and may be adopted in many different forms and endless ideas.
Tutorial:
You may add an ‘Optimal Length’ within the Settings as a ‘Source’ as followed in the example above. This Indicator allows for the input of a:
Neutral ‘Optimal Length’
Fast ‘Optimal Length’
Slow ‘Optimal Length’
It is important to account for all three as they generally encompass different min/max length values and therefore result in varying ‘Optimal Length’s’.
For instance, say you’re calculating the ‘Optimal Length’ and you use:
Min: 1
Max: 400
This would therefore be scanning for 400 (inclusive) lengths.
As a general way of calculating you may assume the following for which lengths are being used within an ‘Optimal Length’ calculation:
Fast: 1 - 199
Slow: 200 - 400
Neutral: 1 - 400
This allows for the calculation of a Fast and Slow length within the predetermined lengths allotted. However, it likewise allows for a Neutral length which is inclusive to all lengths alloted and may be deemed the ‘Most Accurate’ for these reasons. However, just because the Neutral is inclusive to all lengths, doesn’t mean the Fast and Slow lengths are irrelevant. The Fast and Slow length inputs may be useful for seeing how specifically zoned lengths may fair, and likewise when they cross over and/or under the Neutral ‘Optimal Length’.
This Indicator features the ability to display multiple different types of Traditional Indicators within the ‘Display Type’.
We will go over all of the different ‘Display Types’ with examples on how using a Fast, Slow and Neutral length would impact it:
Simple Moving Average:
In this example above have the Fast, Slow and Neutral Optimal Length formatted as a Slow Moving Average. The first example is on the 15 minute Time Frame and the second is on the 1 Day Time Frame, demonstrating how the length changes based on the Time Frame and the effects it may have.
Here we can see that by inputting ‘Optimal Lengths’ as a Simple Moving Average we may see moving averages that change over time with their ‘Optimal Lengths’. These lengths may help identify Support and/or Resistance locations. By using an 'Optimal Length' rather than a static length, we may create a Moving Average which may be more accurate as it attempts to be adaptive to current Market Conditions.
Bollinger Bands:
Bollinger Bands are a way to see a Simple Moving Average (SMA) that then uses Standard Deviation to identify how much deviation has occurred. This Deviation is then Added and Subtracted from the SMA to create the Bollinger Bands which help Identify possible movement zones that are ‘within range’. This may mean that the price may face Support / Resistance when it reaches the Outer / Inner bounds of the Bollinger Bands. Likewise, it may mean the Price is ‘Overbought’ when outside and above or ‘Underbought’ when outside and below the Bollinger Bands.
By applying All 3 different types of Optimal Lengths towards a Traditional Bollinger Band calculation we may hope to see different ranges of Bollinger Bands and how different lookback lengths may imply possible movement ranges on both a Short Term, Long Term and Neutral perspective. By seeing these possible ranges you may have the ability to identify more levels of Support and Resistance over different lengths and Trading Styles.
Donchian Channels:
Above you’ll see two examples of Machine Learning: Optimal Length applied to Donchian Channels. These are displayed with both the 15 Minute Time Frame and the 1 Day Time Frame.
Donchian Channels are a way of seeing potential Support and Resistance within a given lookback length. They are a way of withholding the High’s and Low’s of a specific lookback length and looking for deviation within this length. By applying a Fast, Slow and Neutral Machine Learning: Optimal Length to these Donchian Channels way may hope to achieve a viable range of High’s and Low’s that one may use to Identify Support and Resistance locations for different ranges of Optimal Lengths and likewise potentially different Trading Strategies.
Envelopes / Envelopes Adjusted:
Envelopes are an interesting one in the sense that they both may be perceived as useful; however we deem that with the use of an ‘Optimal Length’ that the ‘Envelopes Adjusted’ may work best. We will start with examples of the Traditional Envelope then showcase the Adjusted version.
Envelopes:
As you may see, a Traditional form of Envelopes even produced with a Machine Learning: Optimal Length may not produce optimal results. Unfortunately this may occur with some Traditional Indicators and they may need some adjustments as you’ll notice with the ‘Envelopes Adjusted’ version. However, even without the adjustments, these Envelopes may be useful for seeing ‘Overbought’ and ‘Oversold’ locations within a Machine Learning: Optimal Length standpoint.
Envelopes Adjusted:
By adding an adjustment to these Envelopes, we may hope to better reflect our Optimal Length within it. This is caused by adding a ratio reflection towards the current length of the Optimal Length and the max Length used. This allows for the Fast and Neutral (and potentially Slow if Neutral is greater) to achieve a potentially more accurate result.
Envelopes, much like Bollinger Bands are a way of seeing potential movement zones along with potential Support and Resistance. However, unlike Bollinger Bands which are based on Standard Deviation, Envelopes are based on percentages +/- from the Simple Moving Average.
We will conclude our Tutorial here. Hopefully this has given you some insight into how useful adding a ‘Optimal Length’ within an external (secondary) Indicator as a Source within the Settings may be. Likewise, how useful it may be for automation sake in the sense that when the ‘Optimal Length’ changes, it doesn’t rely on an alert where you need to manually update it yourself; instead it will update Automatically and you may reap the benefits of such with little manual input needed (aside from the initial setup).
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Inflation Rate of ChangeInflation and the Fed interest rate impacts all corners of the economy. Today I am releasing to the community an indicator that measures the rate of change of inflation with historical data back to ~1950. I built this to study the historical market impacts of inflation and changes to the Fed rate (see separate indicator I published for Fed Funds Rate here ).
What this indicator does:
This indicator pulls in Consumer Price Index data and applies a rate of change formula to it. The output is measured as a percentage. I.e. 7 would mean a 7% rate of change over the look-back period.
Options in the indicator:
You can change the amount of bars back it uses to calculate rate of change. By default it is set to 253, which would be looking 1 year back on a normal stock market day chart. If you are on a month chart, you would input 12 there to look 1 year back, etc.
There are also different versions of the CPI that you can select with a drop-down input to pull in different inflation measures:
FRED:CPIAUCSL = Urban Consumers, All Items (this is the default data it pulls, and is a common way to measure inflation)
FRED:CPIUFDNS = Food
FRED:CPIHOSNS = Housing
FRED:CPIENGSL = Energy
Disclaimer: Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
True Adaptive-Lookback Phase Change Index [Loxx]Previously I posted a Phase Change Index using Ehlers Autocorrelation Periodogram Algorithm to tease out the adaptive periods. You can find the previous version here: . This new version is also adaptive but uses a different method to derive the adaptive length inputs. This adaptive method derives period inputs by counting pivots from past candles. This version also relies on Jurik Smoothing to generate the final signal. I named this one "true" because I should have specified in the previous PCI's title that it's powered by Ehlers Autocorrelation Periodogram. Additionally, you'll notice the ALB algorithm has changed from other indicators, This is restrict the range of possible ALB period outputs to a specific range so the indicator is usable.
And remember, this is an inverse indicator. This means that small values on the oscillator indicate bullish sentiment and higher values on the oscillator indicate bearish sentiment.
What is the Phase Change Index?
Based on the M.H. Pee's TASC article "Phase Change Index".
Prices at any time can be up, down, or unchanged. A period where market prices remain relatively unchanged is referred to as a consolidation. A period that witnesses relatively higher prices is referred to as an uptrend, while a period of relatively lower prices is called a downtrend.
The Phase Change Index ( PCI ) is an indicator designed specifically to detect changes in market phases.
This indicator is made as he describes it with one deviation: if we follow his formula to the letter then the "trend" is inverted to the actual market trend. Because of that an option to display inverted (and more logical) values is added.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
Included:
Bar coloring
2 signal variations w/ alerts
Year-over-Year % Change for PCEPILFEHello, traders!
This indicator is specifically for FRED:PCEPILFE , which is a 'Personal Consumption Expenditures (PCE) Index excluding food and energy.'
What this indicator does is compare the monthly data to that of the same month last year to see how it has changed over the year. This comparison method is widely known as YoY(Year-over-Year).
While I made this indicator to use for FRED:PCEPILFE , you may use it for different charts as long as they show monthly data.
FRED:PCEPILFE is one of the main measures of inflation the Federal Reserve uses.
You can see the YoY % change of the PCE Index excluding food and energy in the official website for the Bureau of Labor Statistics, but unfortunately, I couldn't find one in TradingView.
So instead, I decided to make my own indicator showing the changes using FRED:PCEPILFE .
The code is very simple: it compares the data to the data 12 points ago because 12 points would mean 12 months in this chart. We then multiply the result by 100 for percentage.
Doing so, we compare the current month to the same month of the previous year.
Because I am only interested in the YoY % Change of the index, I pulled the indicator all the way up, covering the original chart data entirely. (Or you could achieve the same by simply moving your indicator to the pane above. But this way, the original chart data is also visible.)
I hope this indicator helps you with your analysis. Feel free to ask questions if have any!
God bless!
UM EMA SMA WMA HMA with Directional Color ChangeUM EMA SMA WMA HMA with Directional Color Change
Description:
This is a Swiss Army knife type of Moving Average tool. Select your favorite Moving Average type, EMA - Exponential Moving Average, SMA - Simple Moving Average, WMA - Weighted Moving Average, or HMA - Hull Moving Average. Then selection your number of periods. The MA line is green when trending higher and red when trending lower. The fill between price and the MA line matches the red/green of the direction.
Defaults and Configuration:
The default setting is 65 period and EMA. Line colors and optional fill colors are user-configurable.
Alerts:
An alert can be set on the MA for directional color changes (red to green, or green to red) Right click the indicator and select Add Alert. Then select Bullish or Bearish color change.
Suggested Uses:
Add this to any timeframe chart with your favorite Moving averages. A strategy I use frequently is to "stretch" the Moving average. For example if you like the 8 day moving average on the daily chart, try the 52 period Moving average on the hourly chart. (6.5 market hours per day * 8) By looking at smaller time frames with longer MAs you get smoother color transitions on the Moving average. Add multiple instances of the MA. I prefer to use a smaller quick MA with a longer MA that represents a longer time frame.
Another use case I also like is the color transition over a Moving Average crossover. While I do like the daily 2/6 and 8/3 moving average crossovers, red-to-green and green-to-red color transitions seem to work with less lag than the crossovers.
Suggested Settings:
Daily charts: 8 EMA
Hourly charts: 55 EMA
30 minute charts: 65 WMA. (I like this one for inverse ETFs)
3 minutes charts: 178 EMA and 233 EMA
I also like to round MA settings up or down to the nearest fibonacci number: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, etc.
RedK_Relative (Dual) Rate Of Change v1 - RROC v1Quick Summary
==============
The Relative Rate of Change (RRoC) is an expanded version of the classic Rate of Change (RoC) indicator - we apply couple of changes to bring additional insights and signals from that classic Technical Analysis concept - which can help us better visualize the "relative speed of change" of a stock (or whatever we trade), and can work specifically as a "breakout finder" .. please read on if this can be valuable to your trading.
First, a quick review of what is the classic Rate of Change (RoC) - The below part is from Investopedia definition of RoC
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www.investopedia.com
What is Rate of Change (ROC)
The rate of change (ROC) is the speed at which a variable changes over a specific period of time.
ROC is often used when speaking about momentum, and it can generally be expressed as a ratio between a change in one variable relative to a corresponding change in another; graphically, the rate of change is represented by the slope of a line.
Understanding Rate of Change (ROC)
Rate of change is used to mathematically describe the percentage change in value over a defined period of time, and it represents the momentum of a variable .
The calculation for ROC is simple in that it takes the current value of a stock or index and divides it by the value from an earlier period.
Subtract one and multiply the resulting number by 100 to give it a percentage representation.
ROC = (current value / previous value - 1) * 100
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What changes did we make to the RoC?
====================================
(1) - Per the official definition, the original RoC should provide a "rate of change" - i.e., we should say "the 5-bar average price change for AAPL is x% per bar" - now norice that the formula doesn't divide by the number of bars (length) -- so the reality is, the results is more of "the 5-bar price change for apple is x% for the full 5 bar length"
- what is wrong with that ? nothing really, but it's harder to use that number to set my trade target or exit. i need the indicator to give me a number that represents the "average change per bar" so i can use it to "design my trade target and my exit loss" -- so in the RRoC, we divide the change by the number of bars used in the settings
The updated formula would be : RoC = (current value / previous value -1 ) * 100 / length
(2) - Dual Length: we make the RoC relative, by adding a longer (or slow) RoC
- the idea here is simple - imagine you're driving your car beside a moving train, your car will not "breakout" from the train until your speed (= distance gain per unit of time) is faster than the train - so in reality, your baseline is not 0 speed, it's the speed of that train your racing against -- makes sense?
- so we add a second length that can act as a baseline - when the Fast RoC exceeds the Slow RoC (your car is faster than the train), a breakout would possibly occur - that breakout may fail (if something interrupts it - my car may breakdown if it can't handle the faster speed :) ) or it can fully materialize if the "context" is favorable.
as we can see on the above chart, we can use the RRoC to identify an incoming possible breakout using that simple "relative speed" concept - and that setup happened not once but twice in our example
the interpretation of this for AAPL would be (for example): "AAPL has been making an average change of 0.22% in the past 20 days, but for the last 5 days, the average change was 0.35% - so it looks like AAPL is gaining short term momentum and may break-out soon"
(3) this is another strong feature: Use for broader context:
- we can set the RRoC for a resolution of - for example - a day, while we look at the 1 hour chart - giving us the ability to trade on a smaller timeframe in the context of a larger timeframe .. this is more of an advanced feature but i hope some will be able to leverage it.
Here's a side-by-side comparison of RRoC vs the classic (built-in) RoC indicator
Conclusion:
============
- The (Relative Rate of Change) RRoC expands on the concepts presented by the classic Rate of Change (RoC) indicator and enables additional insights - especially around the discovery of potential price breakout
- leverage the RRoC indicator settings to tweak it to how your trade (fast length, slow length, resolution, smoothing). the defaults should work for any instrument but may not necessarily be the optimal settings
- use in conjunction with other indicators that can show trend and prevailing sentiment / context - to ensure you get proper confirmation and please get very familiar with how the RRoC works before you use it for live trading.
Comments are welcome - Best of luck
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Multi-Period % Change Bands (Extreme Dots)Multiple Period Percentage Change Extreme Dots
This indicator visualizes percentage changes across three different timeframes (8, 13, and 21 days), highlighting extreme movements that break out of a user-defined band. It's designed to identify which timeframe is showing the most significant percentage change when prices make notable moves.
Features:
- Tracks percentage changes for 8-day, 13-day, and 21-day periods
- Customizable upper and lower bands to define significant moves
- Shows dots only for the most extreme moves (highest above band or lowest below band)
- Color-coded for easy identification:
- Blue: 8-day changes
- Green: 13-day changes
- Red: 21-day changes
- Includes current values display for all timeframes
Usage Tips:
- Shorter timeframes (8-day) are more sensitive to price changes and should use narrower bands (e.g., ±3%)
- Medium timeframes (13-day) work well with moderate bands (e.g., ±5%)
- Longer timeframes (21-day) can use wider bands (e.g., ±8%)
- Dots appear only when a timeframe shows the most extreme move above/below bands
- Use the gray zone between bands to identify normal price action ranges
The indicator helps identify which lookback period is showing the strongest momentum in either direction, while filtering out normal market noise within the bands.
Note: This is particularly useful for:
- Identifying trend strength across different timeframes
- Spotting which duration is showing the most extreme moves
- Filtering out minor fluctuations through the band system
- Comparing relative strength of moves across different periods
Percentage Change IndicatorPercentage Change Indicator
This indicator calculates and displays the percentage change between the current close price and the previous close price. It provides a clear visual representation of price movements, helping traders quickly identify significant changes in the market.
## Formula
The percentage change is calculated using the following formula:
```
Percentage Change = (Current Close - Previous Close) * 100 / Current Close
```
## Features
- Displays percentage change as a bar chart
- Green bars indicate positive changes
- Red bars indicate negative changes
- A horizontal line at 0% helps distinguish between positive and negative movements
## How to Use
1. Add the indicator to your chart
2. Observe the bar chart below your main price chart
3. Green bars above the 0% line indicate upward price movements
4. Red bars below the 0% line indicate downward price movements
5. The height of each bar represents the magnitude of the percentage change
This indicator can be particularly useful for:
- Identifying sudden price spikes or drops
- Analyzing the volatility of an asset
- Comparing price movements across different timeframes
- Spotting potential entry or exit points based on percentage changes
Customize the indicator's appearance in the settings to suit your charting preferences.
Note: This indicator works on all timeframes, adapting its calculations to the selected chart period.
Marcos Ruiz :Price Change Speed Descripción:
Este indicador en Pine Script está diseñado para analizar y visualizar dinámicamente la velocidad de los cambios de precio en un gráfico de TradingView. El indicador permite a los usuarios seleccionar diferentes tipos de medias móviles y fuentes de precios para calcular y mostrar el cambio porcentual en el precio durante un período especificado
Características:
Selección de Fuente de Precio: Elige entre cierre, apertura, alto, o bajo para los cálculos de precios
Tipos de Media Móvil: Selecciona entre SMA, WMA, EMA, HMA, o VWMA para determinar la media móvil utilizada en el cálculo de la velocidad promedio
Coloreado Dinámico: El color de la línea de la media móvil cambia según la velocidad de cambio de precio
Aumento de Velocidad: Cuando la velocidad del cambio de precio está aumentando, la media móvil se colorea según upColor definido por el usuario
Disminución de Velocidad: Cuando la velocidad está disminuyendo, la media móvil se colorea según downColor definido por el usuario
Posición Neutral: Coloreado adicional para escenarios donde el precio está por encima o por debajo de la media móvil, pero no cumple con las condiciones de aumento/disminución
Factor de Refuerzo: Ajusta la sensibilidad del cálculo del cambio de velocidad
Uso:
Parámetros de Entrada:
Define el Período para establecer la ventana de retroceso para calcular la velocidad
Elige la Fuente de Precio para determinar qué datos de precios usar
Selecciona el Tipo de Media Móvil y ajusta la Longitud de EMA para la comparación
Interpretación:
El indicador traza la media móvil seleccionada con colores dinámicos basados en la velocidad calculada del cambio de precio
Los cambios positivos y negativos en la velocidad se indican con diferentes colores, proporcionando una representación visual del momento y la fuerza de la tendencia del precio
Nota: Este script es el resultado de un desarrollo y pruebas extensivas. Se agradecen mucho sus comentarios y contribuciones
Description:
This Pine Script indicator is designed to dynamically analyze and visualize the speed of price changes on a TradingView chart. The indicator allows users to select different moving average types and price sources to compute and display the percentage change in price over a specified period
Features:
Price Source Selection: Choose from close, open, high, or low for price calculations
Moving Average Types: Select from SMA, WMA, EMA, HMA, or VWMA to determine the moving average used for computing average speed
Dynamic Coloring: The moving average line's color changes based on the speed of price change
Increasing Speed: When the price change speed is increasing, the moving average is colored according to the user-defined upColor
Decreasing Speed: When the speed is decreasing, the moving average is colored according to the user-defined downColor
Neutral Position: Additional coloring for scenarios where the price is above or below the moving average but not meeting the increase/decrease conditions
Reinforcement Factor: Adjusts the sensitivity of the speed change calculation
Usage:
Input Parameters:
Set the Period to define the lookback window for calculating speed
Choose the Price Source to determine which price data to use
Select the Moving Average Type and adjust the EMA Length for comparison
Interpretation:
The indicator plots the selected moving average with dynamic colors based on the calculated speed of price change
Positive and negative changes in speed are indicated by different colors, providing a visual representation of price momentum and trend strength
Note: This script is the result of extensive development and testing. Your feedback and contributions are highly appreciated
Adaptive Look-back/Volatility Phase Change Index on Jurik [Loxx]Adaptive Look-back, Adaptive Volatility Phase Change Index on Jurik is a Phase Change Index but with adaptive length and volatility inputs to reduce phase change noise and better identify trends. This is an invese indicator which means that small values on the oscillator indicate bullish sentiment and higher values on the oscillator indicate bearish sentiment
What is the Phase Change Index?
Based on the M.H. Pee's TASC article "Phase Change Index".
Prices at any time can be up, down, or unchanged. A period where market prices remain relatively unchanged is referred to as a consolidation. A period that witnesses relatively higher prices is referred to as an uptrend, while a period of relatively lower prices is called a downtrend.
The Phase Change Index (PCI) is an indicator designed specifically to detect changes in market phases.
This indicator is made as he describes it with one deviation: if we follow his formula to the letter then the "trend" is inverted to the actual market trend. Because of that an option to display inverted (and more logical) values is added.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers, 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average (KAMA) and Tushar Chande’s variable index dynamic average (VIDYA) adapt to changes in volatility. By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic, relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
-Your choice of length input calculation, either fixed or adaptive cycle
-Invert the signal to match the trend
-Bar coloring to paint the trend
Happy trading!
Gann Swing Chart [One-Bar]"Gann used three types of swings chart.
One-Bar Swing Chart (1-Bar Swing Chart): The One-Bar Swing Chart, or Minor Trend Chart, follows the one-bar movements of the market. From a low price, each time the market makes a higher-high than the previous bar, a One-Bar trend line moves up from the recent low to the new high. This action makes the previous low price a One-Bar bottom. From a high price each time the market makes a lower-low than the previous bar, a One-Bar swing line moves down from the recent high to the new low. This action makes the previous high price a One-Bar top.
The combination of One-Bar tops and bottoms forms the One-Bar trend indicator chart. The crossing of a One-Bar swing top changes the One-Bar trend to up. The penetration of a One-Bar swing bottom changes the One-Bar trend to down."
This Indicator only show Gann Swing Chart use One-Bar type.
Rate Of Change [SIDD]This Oscillator is helping identify rate of change in Price.
Basic Definition :-
The Rate of Change ( ROC ) is a momentum technical indicator.
It measures the percentage change in price between the current price and the price a certain number of periods ago.
This indicator is plotted against zero, with the indicator moving upwards into positive territory if price changes are to the upside, and moving into negative territory if price changes are to the downside.
Customization of inbuilt ROC:- I have created EMA of ROC with 9 days exponential moving average and Coloring the plot of 9 EMA of ROC Green and RED. Green line indicates that Price change rate is positive in last 9 time period on selected resolution (time frame) and Red line indicated that negative price change rate.
I have identified the zone like +5 and -5 line area in study where some resistance or support is there for 9 EMA ROC line. and if 9 EMA ROC crosses those line then intensity of previous trend get increased.
I have drawn here breakout trendline from lower high candle with hand mark up and same time ROC is above 5 marked with hand up. Similarly I have drawn hand mark down where breakdown trendline is drawn for higher low candle breakdown.
You can see clearly ROC 9 EMA is sync correctly with breakout and breakdown candle when ROC 9 EMA
is above 5 and below 5.
I able to observed that ROC 9 EMA is helping in finding correct breakout and breakdown candles with proper trendline breakout and breakdown.
above all my observation is with daily time frame and 1 Hr time frame candles mostly. If you are changing time frame then see the difference and post same in comment so I can watch those changes as well,
You can modify this study and lets create better than this as well. As I think nothing is perfect in this world always there is scope of improvement.
This study to see how the price are getting changing and what is the rate of change .
This study doesn't give any buy and sell recommendation.
I have other indicator which is given in my signature below that you can check.
TF7 Option vs Index Change RatioOverview
This indicator helps traders visualise the strength and direction of an option's price movement compared to its underlying index (NIFTY or SENSEX).
It calculates a Change Ratio, which is the percentage move in the option compared to the index movement during the same bar. This is especially useful for intraday traders looking for signs of momentum, divergence, or unusual strength/weakness in option pricing.
How It Works
The ratio is calculated as:
(Option LTP − Option Open) / (Index Close − Index Open)
The value is capped between −10 and +10 to filter out extreme or invalid spikes.
The ratio is displayed as a color-coded column chart:
🟩 Green bars: Option is moving in the same direction as the index.
🟥 Red bars: Option is underperforming or moving opposite to the index.
A compact table shows the last 5 bars of:
Option price change (with +/− sign)
Index price change
Calculated ratio (also color-coded)
You can toggle the table visibility in the settings.
Inputs & Features
Select underlying index: NIFTY or SENSEX
Toggle the data table display
Clean formatting with signed values and conditional color highlights
⚠️ Disclaimer
This is a visual analysis tool, not a buy/sell signal. Always validate with your trading strategy and risk management
#OptionsTrading, #NIFTY, #SENSEX, #ChangeRatio, #IndexAnalysis, #Momentum, #Divergence, #Intraday
Market Structure ICT Screener [TradingFinder] BoS ChoCh🔵 Introduction
Market Structure is the foundation of every Smart Money and ICT based trading model. It describes how price moves through a sequence of highs and lows, forming clear phases of expansion, retracement and reversal. Understanding this structure allows traders to read institutional order flow and align their positions with the true direction of liquidity.
Two of the most critical components in Market Structure are the Break of Structure (BOS) and Change of Character (CHOCH). A BOS represents trend continuation, confirming strength within the current direction. In contrast, CHOCH also known as a Market Structure Shift (MSS) signals the first sign of a trend reversal or liquidity shift where order flow begins to change from bullish to bearish or vice versa.
Because the market is fractal, structure can exist at multiple levels known as Major (External) and Minor (Internal). Major structure defines the overall trend on higher timeframes while minor or internal structure reveals short term swings and early reversals within that larger move.
🔵 How to Use
Understanding Market Structure starts with identifying how price interacts with previous swing highs and swing lows. Every trend in the market, whether bullish or bearish, is built from a sequence of impulsive and corrective moves. Impulsive legs show strong displacement in the direction of liquidity flow, while corrective legs represent temporary pullbacks as the market rebalances before the next expansion. Recognizing these sequences is essential for reading the story of price and anticipating what may happen next.
A Break of Structure (BOS) occurs when price decisively moves beyond a previous structural point by breaking above the last high in an uptrend or falling below the last low in a downtrend. This event confirms that the current trend remains intact and that liquidity has been successfully taken from one side of the market. A BOS acts as confirmation of continuation and reflects strength within the existing directional bias.
A Change of Character (CHOCH) appears when price violates structure in the opposite direction of the prevailing trend. This is the first signal that market sentiment and order flow may be shifting. For example, during a downtrend if price breaks above a previous high, it indicates that sellers are losing control and a potential bullish reversal may be developing. In an uptrend, when price drops below a recent low, it suggests a possible bearish transition.
Because the market is fractal, structure exists across multiple layers. Major structure reflects the dominant movement visible on higher timeframes and defines the broader directional bias. Minor or internal structure represents smaller swings within that move and helps identify early transitions before they appear on the higher timeframe. When internal and external structures align, they offer a high probability signal for trend continuation or reversal.
By observing BOS and CHOCH across both internal and external structures, traders can clearly visualize when the market is expanding, contracting or preparing to shift direction. This structured understanding of price movement forms the foundation for precise trend analysis and high quality decision making in any Smart Money or ICT based trading approach.
🔵 Settings
🟣 Display Settings
Table on Chart : Allows users to choose the position of the signal dashboard either directly on the chart or below it, depending on their layout preference.
Number of Symbols : Enables users to control how many symbols are displayed in the screener table, from 10 to 20, adjustable in increments of 2 symbols for flexible screening depth.
Table Mode : This setting offers two layout styles for the signal table :
Basic : Mode displays symbols in a single column, using more vertical space.
Extended : Mode arranges symbols in pairs side-by-side, optimizing screen space with a more compact view.
Table Size : Lets you adjust the table’s visual size with options such as: auto, tiny, small, normal, large, huge.
Table Position : Sets the screen location of the table. Choose from 9 possible positions, combining vertical (top, middle, bottom) and horizontal (left, center, right) alignments.
🟣 Symbol Settings
Each of the 20 symbol slots comes with a full set of customizable parameters :
Symbol : Define or select the asset (e.g., XAUUSD, BTCUSD, EURUSD, etc.).
Timeframe : Set your desired timeframe for each symbol (e.g., 15, 60, 240, 1D).
Pivot Period : Set the length used to detect swing highs and lows. Shorter values increase sensitivity, longer ones focus on major structures.
🔵 Conclusion
Mastering Market Structure and understanding the relationship between BOS and CHOCH allows traders to see the market with greater clarity and confidence. These two elements reveal how liquidity moves through different phases of expansion and retracement and how institutional order flow shifts between accumulation and distribution.
By analyzing both internal and external structures, traders can align short term and long term perspectives and anticipate where price is most likely to react. The ability to read these structural shifts helps identify continuation points, reversals and areas where liquidity is engineered or collected.
Incorporating Market Structure into a consistent trading process transforms the way a trader views the chart. Instead of reacting to random movements, each swing, break and shift becomes part of a logical framework that reflects the true behavior of the market. Understanding BOS and CHOCH is not just a concept but a complete language of price that guides every professional decision in Smart Money and ICT based trading.
