BRT Cluster VolumeTitle and Purpose
BRT Cluster Volume is a powerful market analysis tool designed to identify key support and resistance levels, cluster volumes, and breakout signals. This script is highly beneficial for traders who aim to gain deeper insights into market trends and pinpoint zones of interest for buyers and sellers.
Key Features
1. Support and Resistance Levels:
- The script automatically detects chart extremums by analyzing a specified number of bars on the left and right to form levels. This approach effectively identifies local highs and lows.
- The uniqueness of this implementation lies in its dynamic data processing. For each extremum, the "channel width" is calculated, allowing insignificant levels to be filtered out based on a user-defined minimum width. This method eliminates noise and ensures focus on critical levels.
- Extremum lines can be extended to the right (when enabled), allowing traders to track current price movements relative to historical levels.
2. Cluster Volume:
- The cluster analysis is based on lower timeframe data, providing precise identification of key zones of market participant activity. The script dynamically requests close prices and volumes from lower timeframes, calculates the average volume, and identifies levels where volumes exceed a defined threshold.
- The visualization of cluster volumes is unique: volumes exceeding the threshold are displayed as candles with customizable colors and markers. These indicators help traders identify zones of significant interest.
- Cluster volume is only displayed when it interacts with support or resistance levels, ensuring that the visualization remains precise and relevant for market analysis.
3. Breakout Signals:
- The script evaluates "breakout strength" for each breakout of support or resistance levels by comparing the current price with the level. This helps filter false breakouts and focus on significant price movements.
- Traders can select the source for breakout signals (close price or high/low), offering flexibility for various trading styles and strategies.
- By incorporating the concept of "maximum breakout strength," the script highlights only meaningful breakouts, ignoring minor fluctuations.
4. Integration of Trading Sessions:
- Extremum levels for major trading sessions (Asia, Europe, USA) are identified and labeled on the chart. This allows traders to see when significant price levels were formed during the day.
- The script uses timestamps to automatically detect session times, ensuring accuracy and minimizing manual adjustments.
5. Dynamic Data Updates:
- The script dynamically updates support and resistance levels in real time as new data becomes available. This feature is crucial for traders working in fast-moving markets.
- Outdated information (such as obsolete levels) is automatically removed to keep the chart clean and focused on relevant data.
6. Visualization of Activity Zones:
- Trend direction is visualized using color-coded candles based on cluster volumes. For instance, candles with volumes exceeding the average are highlighted with specific colors, helping traders quickly identify areas of heightened activity.
- The unique aspect of this visualization is that cluster volumes appear only in zones where they interact with breakout levels, providing an intuitive and streamlined presentation of critical data.
Usage
- Support and Resistance: Adjust the "Left Bars" and "Right Bars" settings to determine extremums. Use the "Channel Min Width" setting to filter out insignificant levels.
- Cluster Volume: Customize the analysis period and volume threshold to identify high-activity zones. Enable breakout clusters to see how volumes interact with breakouts.
- Session Extremums: Highlight significant levels for Asia, Europe, and US trading sessions to gain insights into market dynamics across different time zones.
- Breakout Signals: Configure the breakout strength and source (close or high/low) for precise signal detection.
Parameter Details
1. Support & Resistance:
- `Left Bars` / `Right Bars`: Number of bars to consider for determining extremums.
- `# of Lines`: Maximum number of support/resistance lines to display.
- `Channel Min Width`: Minimum channel width to filter insignificant levels.
2. Breakout:
- `Show Breakouts`: Toggle breakout signal display.
- `Max breakout strength`: Maximum strength for valid breakouts.
- `Breakout source`: Data source for breakouts (close or high/low).
3. Cluster Volume:
- `Lookback`: Number of bars to analyze for cluster volumes.
- `Threshold`: Volume threshold (percentage above the average).
- `Cluster Volume Timeframe`: Timeframe for cluster volume analysis.
- `Breakout Cluster`: Display cluster volumes only for breakout-related zones.
4. Visual Settings:
- `Extend extremum lines to the right`: Extend support/resistance lines to the right.
- `Show ASIA/EU/US Session Extremums`: Display extremums for trading sessions.
Features and Benefits
- The script provides flexible parameter customization, allowing it to adapt to different trading styles and timeframes.
- The visualization is designed to be clean and intuitive, ensuring users can easily interpret the data.
- Suitable for all timeframes, making it ideal for both intraday and long-term market analysis.
Limitations
- The script is not suitable for analysis on non-standard chart types (e.g., Heikin Ashi, Renko, Kagi).
- To ensure accurate performance, realistic data for commission and slippage should be used.
Warnings
- The script relies on historical data for calculations, which may cause discrepancies in real-time conditions.
- Users should fully understand the functionality of cluster analysis and breakout signals before using the script in live trading.
This script combines advanced data processing logic, dynamic level adjustments, and unique visualization approaches, making it an indispensable tool for market analysis and trading decision-making.
Cerca negli script per "session"
Break of High/Low with Volume, MACD, and MAsHow It Works:
Sessions:
The London session is defined between 8:00 and 16:00 UTC.
The New York session is defined between 13:00 and 21:00 UTC.
Previous High/Low:
The script identifies the highest high and lowest low from the previous bar using ta.highest(high, 1) and ta.lowest(low, 1) .
Candle Body Size:
The script calculates the size of the current candle's body and checks if it is at least double the size of the previous candle's body.
Volume Check:
A high volume threshold is set as 1.5 times the 50-period SMA of the volume.
MACD Crossover:
The script calculates the MACD and its signal line and checks for bullish (buy) or bearish (sell) crossovers.
Signals:
A long signal (buy) is generated if the price breaks the previous high with a large body candle, high volume, and a bullish MACD crossover during the specified sessions.
A short signal (sell) is generated if the price breaks the previous low with a large body candle, high volume, and a bearish MACD crossover during the specified sessions.
Plotting:
The 50-period and 200-period moving averages, previous high, and previous low are plotted on the chart.
If a long condition is met, a "BUY" label is displayed below the bar. If a short condition is met, a "SELL" label is displayed above the bar.
Alerts:
Alerts are triggered whenever the conditions for a long or short trade are met.
Customization:
Feel free to adjust the session times, volume threshold, MACD settings, or moving averages based on your trading strategy or the specific asset you are trading.
90 Minute Cycles + MTFCredit goes to LuxAlgo for the inspiration from 'Sessions' which allowed users to analyse specific price movements within a user defined period with tools such as trendline, mean and vwap.
Settings
Sessions
Enable Session: Allows to enable or disable all associated elements with a specific user set session.
Session Time: Opening and closing times of the user set session in the hh:mm format.
Range: Highlights the associated session range on the chart.
Ranges Settings
Range Area colour: Set each range to a specific colour.
Range Label: Shows the session label at the mid-point of the session interval.
Usage
By breaking 24hrs in quarters, starting with an Asian range of 18:00 NY time you can visualise the principles of Accumulation, Manipulation, Distribution and Rebalance. Know as AMD or PO3 (Power of Three), the principle is that the Manipulation phase will break above or below the Accumulation, before moving in an apposing direction and then rebalancing. This only works when there is a higher timeframe PD array or liquidity to support an apposing move.
Further to the daily quarters, each one can then be broken down again into 90min cycles. Again, each represents AMD, allowing the user an opportunity to watch for reversals during the 90min manipulation phase.
Note: Ensure the Asian Cycle always begins at 18:00 NY time.
The example shows that the 90min cycle occurs, followed by an apposing move away in price action
Here is the Daily cycle, highlighting the Manipulation phase.
Enjoy!
OpeningRange (Trading_Tix)Purpose:
The indicator highlights the high, low, and middle (50%) price levels of a specified session's opening range. These levels can serve as key support and resistance zones for trading strategies. The indicator also offers options to extend these levels beyond the session into later timeframes, making it useful for tracking breakout or trend continuation setups.
Key Features:
1. Session Detection:
The indicator identifies a specific session period using the user-defined Session Time. It calculates the start time, high, and low prices during this period:
rangeTime: Defines the session time range (default: 5:00 PM to 2:59 AM).
extendTime: Defines the extended time range where lines/backgrounds can be prolonged.
2. Opening Range Calculation:
High (high_val) and Low (low_val)**:
Tracks the highest and lowest prices during the session.
Middle Line:
A midpoint is calculated by averaging high_val and low_val.
3. Visual Elements:
Horizontal Lines:
Drawn at the high, low, and middle levels.
Customizable in width and color.
Shaded Background Box:
Covers the range between high and low prices.
The box’s color and transparency can be adjusted.
Line and Box Extension:
Optionally extends these elements into the extended time range.
4. Customization:
Users have the flexibility to:
Toggle visibility of lines, middle line, and background box.
Adjust colors, line thickness, and style.
Enable or disable the extension of lines and backgrounds into the extended period.
How It Works:
Initialization:
The script initializes variables to store range data (startTime, high_val, low_val) and drawing objects (lines, boxes).
It detects whether the current bar falls within the session (inSession) or extended timeframe (inExtend).
Plotting:
During the session:
Deletes previous lines and boxes from prior sessions.
Draws new lines at the high, low, and middle levels.
Creates a background box covering the range, if enabled.
During the extended period:
Extends the session lines and box, if the user has opted for extensions.
Updates:
Continuously adjusts the high/low values and updates the lines as new price data arrives.
Use Cases:
This indicator can be valuable for traders who:
Use the opening range to identify potential breakout zones.
Trade based on price consolidation within the range.
Want a visual representation of key price levels to plan entries and exits.
Would you like help refining this script further or adjusting its settings to match your trading style?
Number of Bars CheatSheetA regular trading day on the New York Stock Exchange (NYSE) consists of two main sessions: the Opening Auction and the Closing Auction, separated by a continuous trading session. Here's a breakdown of the trading day:
1. **Pre-Opening Session**: This session starts at 4:00 AM Eastern Time (ET) and lasts until 9:30 AM ET. During this time, there is limited trading activity, and orders can be entered and canceled. However, most of the trading activity doesn't occur until the regular trading session begins.
2. **Regular Trading Session**: The regular trading session on the NYSE starts at 9:30 AM ET and lasts until 4:00 PM ET. This is the primary trading session where the majority of price bars are formed.
3. **Closing Auction**: After the regular trading session ends at 4:00 PM ET, there is a closing auction period that typically lasts until 4:10 PM ET. During this time, there is a final price discovery process where orders are matched to determine the closing price for each security.
So, during the regular trading session, which is the main focus for most traders and investors, there are a total of 6.5 hours of trading. Trading occurs continuously during this time, with price bars being formed based on the time frame you're looking at. The most common time frames for price bars are one minute, five minutes, 15 minutes, 30 minutes, and one hour, among others. Therefore, the number of price bars in a regular trading day on the NYSE will depend on the time frame you are using for your analysis. For example, if you are using one-minute bars, there will be 6.5 x 60 = 390 price bars in a regular trading day.
time_filtersLibrary "time_filters"
Collection of filters that related with time like sessions and datetime ranges.
All existing session functions I found in the documentation e.g. not na(time(timeframe.period, sessionTimes))
are not suitable for strategies, since the execution of the entries and the exits are delayed by one bar.
Thus I created this library to overcome this small but very important limitation.
is_in_date_range(fromDate, toDate, srcTimezone, dstTimezone, t)
is_in_date_range - Check if the given time is between the start and end dates
Parameters:
fromDate : - The start date in UNIX time of the valid range
toDate : - The end date in UNIX time of the valid range
srcTimezone : - The timezone of reference for the 'from' and 'to' dates
dstTimezone : - The target timezone to convert the 'from' and 'to' dates
t : - The time to compare in UNIX format
Returns: series of bool whether or not the time is inside the valid range
is_in_session(startTime, endTime, days, srcTimezone, dstTimezone, t)
is_in_session - Check if the given time is inside the session as defined by the input params
Parameters:
startTime : - The sessionTime object with the use flag and the start time
endTime : - The sessionTime object with the use flag and the end time
days : - The sessionDays object with the use flag and marks for each day of the session
srcTimezone : - The timezone of reference for the time ranges
dstTimezone : - The target timezone to convert the time ranges
t : - The current time to compare in UNIX format.
Returns: series of bool whether or not the time is inside the session
sessionTime
Fields:
hourInDay
minuteInHour
sessionDays
Fields:
mon
tue
wed
thu
fri
sat
sun
True Open CalculationsIndicator Description: True Open Calculations
This custom Pine Script indicator calculates and plots key "True Open" levels based on specific time intervals and trading sessions. The True Open levels represent significant price points on the chart, helping traders identify key reference points tied to various market opening times. These levels are important for understanding price action in relation to market sessions and trading cycles. The indicator is designed to plot lines corresponding to different "True Opens" on the chart and display labels with the associated information.
Key Features:
True Year Open:
This represents the opening price on the first Monday of April each year. It serves as a reference point for the yearly price level.
Plot Color: Green.
True Month Open:
This represents the opening price on the second Monday of each month. It helps in identifying monthly trends and provides a key reference for monthly price movements.
Plot Color: Blue.
True Week Open:
This represents the opening price every Monday at 6:00 PM. It gives traders a level to track weekly opening movements and can be useful for weekly trend analysis.
Plot Color: Orange.
True Day Open:
This represents the opening price at 12:00 AM (midnight) each day. It serves as a daily benchmark for price action at the start of the trading day.
Plot Color: Red.
True New York Session Open:
This represents the opening price at 7:30 AM (New York session start time). This level is crucial for traders focused on the New York trading session.
Plot Color: Purple.
Additional Features:
Labels: The indicator displays labels to the right of each plotted line to describe which "True Open" it represents (e.g., "True Year Open," "True Month Open," etc.).
Dynamic Plotting: The lines are only plotted on the current candle, and the lines are dynamically updated for each time period based on the corresponding "True Open."
Visual Cues: The colors of the plotted lines (green, blue, orange, red, purple) help quickly distinguish between different "True Open" levels, making it easy for traders to track price action and make informed decisions.
Use Cases:
Yearly, Monthly, Weekly, Daily, and Session Benchmarking: This indicator provides traders with important price levels to use as benchmarks for the current year, month, week, and day, helping to identify trends and potential reversals.
Session Awareness: It is particularly useful for traders who want to track key market sessions, such as the New York session, and their impact on price movement.
Long-term Analysis: By including the yearly open, this indicator helps traders gain a broader perspective on market trends and provides context for analyzing shorter-term price movements.
Benefits:
Helps identify important reference points for longer-term trends (yearly, monthly) as well as shorter-term moves (daily, weekly, and session).
Visually intuitive with color-coded lines and labels, allowing quick and easy identification of key market open levels.
Dynamic and real-time: The indicator plots and updates the True Open levels dynamically as the market progresses.
DCSessionStatsOHLC_v1.0DCSessionStatsOHLC_v1.0
© dc_77 | Pine Script™ v6 | Licensed under Mozilla Public License 2.0
This indicator overlays customizable session-based OHLC (Open, High, Low, Close) statistics on your TradingView chart. It tracks price action within user-defined sessions, calculates average manipulation and distribution levels based on historical data, and visually projects these levels with lines and labels. Additionally, it provides a session count table to monitor bullish and bearish sessions.
Key Features:
Session Customization: Define session time (e.g., "0000-1600") and time zone (e.g., UTC, America/New_York). Analyze up to 20 historical sessions.
Anchor Line: Displays a vertical line at session start with customizable style, color, and optional label.
Session Open Line: Plots a horizontal line at the session’s opening price with adjustable appearance and label.
Manipulation Levels: Calculates and projects average price extensions (high/low relative to open) for manipulative moves, shown as horizontal lines with labels.
Distribution Levels: Displays average price ranges (high/low beyond open) for distribution phases, with customizable lines and labels.
Visual Flexibility: Adjust line styles (solid, dashed, dotted), colors, widths, label sizes, and projection offsets (bars beyond session start).
Session Stats Table: Optional table showing counts of bullish (close > open) and bearish (close < open) sessions, with configurable position and size.
How It Works:
Tracks OHLC data within each session and identifies session start/end based on the specified time range.
Computes averages for manipulation (e.g., low below open in bullish sessions) and distribution (e.g., high above open) levels from past sessions.
Projects these levels forward as horizontal lines, extending them by a user-defined offset for easy reference.
Updates a table with real-time bullish/bearish session counts.
Use Case:
Ideal for traders analyzing intraday or custom session behavior, identifying key price levels, and gauging market sentiment over time.
Toggle individual elements on/off and fine-tune visuals to suit your trading style.
chrono_utilsLibrary "chrono_utils"
Collection of objects and common functions that are related to datetime windows session days and time
ranges. The main purpose of this library is to handle time-related functionality and make it easy to reason about a
future bar and see if it is part of a predefined user session and/or inside a datetime window. All existing session
functions I found in the documentation e.g. "not na(time(timeframe, session, timezone))" are not suitable for
strategies, since the execution of the orders is delayed by one bar due to the execution happening at the bar close.
So a prediction for the next bar is necessary. Moreover, a history operator with a negative value is not allowed e.g.
`not na(time(timeframe, session, timezone) )` expression is not valid. Thus, I created this library to overcome
this small but very important limitation. In the meantime, I added useful functionality to handle session-based
behavior. An interesting utility that emerged from this development is data anomaly detection where a comparison
between the prediction and the actual value is happening. If those two values are different then a data inconsistency
happens between the prediction bar and the actual bar (probably due to a holiday or half session day etc..)
exTimezone(timezone)
exTimezone - Convert extended timezone to timezone string
Parameters:
timezone (simple string) : - The timezone or a special string
Returns: string representing the timezone
nameOfDay(day)
nameOfDay - Convert the day id into a short nameOfDay
Parameters:
day (int) : - The day id to convert
Returns: - The short name of the day
today()
today - Get the day id of this day
Returns: - The day id
nthDayAfter(day, n)
nthDayAfter - Get the day id of n days after the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days after the reference day
nextDayAfter(day)
nextDayAfter - Get the day id of next day after the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the next day after the reference day
nthDayBefore(day, n)
nthDayBefore - Get the day id of n days before the given day
Parameters:
day (int) : - The day id of the reference day
n (int) : - The number of days to go forward
Returns: - The day id of the day that is n days before the reference day
prevDayBefore(day)
prevDayBefore - Get the day id of previous day before the given day
Parameters:
day (int) : - The day id of the reference day
Returns: - The day id of the previous day before the reference day
tomorrow()
tomorrow - Get the day id of the next day
Returns: - The next day day id
normalize(num, min, max)
normalizeHour - Check if number is inthe range of
Parameters:
num (int)
min (int)
max (int)
Returns: - The normalized number
normalizeHour(hourInDay)
normalizeHour - Check if hour is valid and return a noralized hour range from
Parameters:
hourInDay (int)
Returns: - The normalized hour
normalizeMinute(minuteInHour)
normalizeMinute - Check if minute is valid and return a noralized minute from
Parameters:
minuteInHour (int)
Returns: - The normalized minute
monthInMilliseconds(mon)
monthInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Parameters:
mon (int) : - The month of reference to get the miliseconds
Returns: - The number of milliseconds of the month
barInMilliseconds()
barInMilliseconds - Calculate the miliseconds in one bar of the timeframe
Returns: - The number of milliseconds in one bar
method init(this, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, refTimezone, chTimezone, fromDateTime, toDateTime)
init - Initialize the time window object from boolean values of each session day
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object that will hold the from and to datetimes
refTimezone (simple string) : - The timezone of reference of the 'from' and 'to' dates
chTimezone (simple string) : - The target timezone to convert the 'from' and 'to' dates
fromDateTime (int) : - The starting datetime of the time window
toDateTime (int) : - The ending datetime of the time window
Returns: - The time window object
method init(this, sun, mon, tue, wed, thu, fri, sat)
init - Initialize the session days object from boolean values of each session day
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sun (bool) : - Is Sunday a trading day?
mon (bool) : - Is Monday a trading day?
tue (bool) : - Is Tuesday a trading day?
wed (bool) : - Is Wednesday a trading day?
thu (bool) : - Is Thursday a trading day?
fri (bool) : - Is Friday a trading day?
sat (bool) : - Is Saturday a trading day?
Returns: - The session days objectfrom_chart
method init(this, unixTime)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
unixTime (int) : - The unix time
Returns: - The session time object
method init(this, hourInDay, minuteInHour)
init - Initialize the object from the hour and minute of the session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
Returns: - The session time object
method init(this, hourInDay, minuteInHour, refTimezone)
init - Initialize the object from the hour and minute of the session time
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
hourInDay (int) : - The hour of the time
minuteInHour (int) : - The minute of the time
refTimezone (string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method init(this, startTime, endTime)
init - Initialize the object from the start and end session time in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTime (SessionTime) : - The time the session begins
endTime (SessionTime) : - The time the session ends
Returns: - The session time range object
method init(this, startTimeHour, startTimeMinute, endTimeHour, endTimeMinute, refTimezone)
init - Initialize the object from the start and end session time
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
startTimeHour (int) : - The time hour the session begins
startTimeMinute (int) : - The time minute the session begins
endTimeHour (int) : - The time hour the session ends
endTimeMinute (int) : - The time minute the session ends
refTimezone (string)
Returns: - The session time range object
method init(this, days, timeRanges)
init - Initialize the user session object from session days and time range
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
days (SessionDays) : - The session days object that defines the days the session is happening
timeRanges (SessionTimeRange ) : - The array of all the session time ranges during a session day
Returns: - The user session object
method to_string(this)
to_string - Formats the time window into a human-readable string
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The string of the time window
method to_string(this)
to_string - Formats the session days into a human-readable string with short day names
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The string of the session day short names
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_string(this)
to_string - Formats the session time into a human-readable string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_string(this)
to_string - Formats the user session into a human-readable string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - The string of the user session
method to_string(this)
to_string - Formats the bar into a human-readable string
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The string of the bar times
method to_string(this)
to_string - Formats the chart session into a human-readable string
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
Returns: - The string of the chart session
method get_size_in_secs(this)
get_size_in_secs - Count the seconds from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of seconds inside the time widow for the given timeframe
method get_size_in_secs(this)
get_size_in_secs - Calculate the seconds inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of seconds inside the session
method get_size_in_bars(this)
get_size_in_bars - Count the bars from start to end in the given timeframe
Namespace types: DateTimeWindow
Parameters:
this (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - The number of bars inside the time widow for the given timeframe
method get_size_in_bars(this)
get_size_in_bars - Calculate the bars inside the session
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The number of bars inside the session for the given timeframe
method from_chart(this)
from_chart - Initialize the session days object from the chart
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
Returns: - The user session object
method from_chart(this)
from_chart - Initialize the session time range object from the chart
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
Returns: - The session time range object
method from_chart(this)
from_chart - Initialize the session object from the chart
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that will hold the days and the time range shown in the chart
Returns: - The chart session object
method to_sess_string(this)
to_sess_string - Formats the session days into a session string with day ids
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object
Returns: - The string of the session day ids
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the session time into a session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - The string of the session time
method to_sess_string(this)
to_sess_string - Formats the user session into a session string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - The string of the user session
method to_sess_string(this)
to_sess_string - Formats the chart session into a session string
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
Returns: - The string of the chart session
method from_sess_string(this, sess)
from_sess_string - Initialize the session days object from the session string
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object that will hold the day selection
sess (string) : - The session string part that represents the days
Returns: - The session days object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
Returns: - The session time object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time object from the session string
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object that will hold the hour and minute of the time
sess (string) : - The session string part that represents the time HHmm
refTimezone (simple string) : - The timezone of reference of the 'hour' and 'minute'
Returns: - The session time object
method from_sess_string(this, sess)
from_sess_string - Initialize the session time range object from the session string in exchange timezone (syminfo.timezone)
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the session time range object from the session string
Namespace types: SessionTimeRange
Parameters:
this (SessionTimeRange) : - The session time range object that will hold the start and end time of the daily session
sess (string) : - The session string part that represents the time range HHmm-HHmm
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method from_sess_string(this, sess)
from_sess_string - Initialize the user session object from the session string in exchange timezone (syminfo.timezone)
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
sess (string) : - The session string that represents the user session HHmm-HHmm,HHmm-HHmm:ddddddd
Returns: - The session time range object
method from_sess_string(this, sess, refTimezone)
from_sess_string - Initialize the user session object from the session string
Namespace types: UserSession
Parameters:
this (UserSession) : - The user-defined session object that will hold the day and the time range selection
sess (string) : - The session string that represents the user session HHmm-HHmm,HHmm-HHmm:ddddddd
refTimezone (simple string) : - The timezone of reference of the time ranges
Returns: - The session time range object
method nth_day_after(this, day, n)
nth_day_after - The nth day after the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week after the given day
method nth_day_before(this, day, n)
nth_day_before - The nth day before the given day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
day (int) : - The day id of the reference day
n (int) : - The number of days after
Returns: - The day id of the nth session day of the week before the given day
method next_day(this)
next_day - The next day that is a session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the next session day of the week
method previous_day(this)
previous_day - The previous day that is session day (true) in the object
Namespace types: SessionDays
Parameters:
this (SessionDays) : - The session days object with the day selection
Returns: - The day id of the previous session day of the week
method get_sec_in_day(this)
get_sec_in_day - Count the seconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of seconds passed from the start of the day until that session time
method get_ms_in_day(this)
get_ms_in_day - Count the milliseconds since the start of the day this session time represents
Namespace types: SessionTime
Parameters:
this (SessionTime) : - The session time object with the hour and minute of the time of the day
Returns: - The number of milliseconds passed from the start of the day until that session time
method eq(this, other)
eq - Compare two bars
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
other (Bar) : - The bar object to compare with
Returns: - Whether this bar is equal to the other one
method get_open_time(this)
get_open_time - The open time object
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The open time object
method get_close_time(this)
get_close_time - The close time object
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The close time object
method get_time_range(this)
get_time_range - Get the time range of the bar
Namespace types: Bar
Parameters:
this (Bar) : - The bar object with the open and close times
Returns: - The time range that the bar is in
getBarNow()
getBarNow - Get the current bar object with time and time_close timestamps
Returns: - The current bar
getFixedBarNow()
getFixedBarNow - Get the current bar with fixed width defined by the timeframe. Note: There are case like SPX 15min timeframe where the last session bar is only 10min. This will return a bar of 15 minutes
Returns: - The current bar
method is_in_window(this, win)
is_in_window - Check if the given bar is between the start and end dates of the window
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes of the window
win (DateTimeWindow) : - The time window object with the from and to datetimes
Returns: - Whether the current bar is inside the datetime window
method is_in_timerange(this, rng)
is_in_timerange - Check if the given bar is inside the session time range
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes
rng (SessionTimeRange) : - The session time range object with the start and end time of the daily session
Returns: - Whether the bar is inside the session time range and if this part of the next trading day
method is_in_days(this, days)
is_in_days - Check if the given bar is inside the session days
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if its day is a trading day
days (SessionDays) : - The session days object with the day selection
Returns: - Whether the current bar day is inside the session
method is_in_session(this, sess)
is_in_session - Check if the given bar is inside the session as defined by the input params (what "not na(time(timeframe.period, this.to_sess_string()) )" should return if you could write it
Namespace types: Bar
Parameters:
this (Bar) : - The bar to check if it is between the from and to datetimes
sess (UserSession) : - The user-defined session object with the day and the time range selection
Returns: - Whether the current time is inside the session
method next_bar(this, offsetBars)
next_bar - Predicts the next bars open and close time based on the charts session
Namespace types: ChartSession
Parameters:
this (ChartSession) : - The chart session object that contains the days and the time range shown in the chart
offsetBars (simple int) : - The number of bars forward
Returns: - Whether the current time is inside the session
DateTimeWindow
DateTimeWindow - Object that represents a datetime window with a beginning and an end
Fields:
fromDateTime (series int) : - The beginning of the datetime window
toDateTime (series int) : - The end of the datetime window
SessionDays
SessionDays - Object that represent the trading days of the week
Fields:
days (map) : - The map that contains all days of the week and their session flag
SessionTime
SessionTime - Object that represents the time (hour and minutes)
Fields:
hourInDay (series int) : - The hour of the day that ranges from 0 to 24
minuteInHour (series int) : - The minute of the hour that ranges from 0 to 59
minuteInDay (series int) : - The minute of the day that ranges from 0 to 1440. They will be calculated based on hourInDay and minuteInHour when method is called
SessionTimeRange
SessionTimeRange - Object that represents a range that extends from the start to the end time
Fields:
startTime (SessionTime) : - The beginning of the time range
endTime (SessionTime) : - The end of the time range
isOvernight (series bool) : - Whether or not this is an overnight time range
UserSession
UserSession - Object that represents a user-defined session
Fields:
days (SessionDays) : - The map of the user-defined trading days
timeRanges (SessionTimeRange ) : - The array with all time ranges of the user-defined session during the trading days
Bar
Bar - Object that represents the bars' open and close times
Fields:
openUnixTime (series int) : - The open time of the bar
closeUnixTime (series int) : - The close time of the bar
chartDayOfWeek (series int)
ChartSession
ChartSession - Object that represents the default session that is shown in the chart
Fields:
days (SessionDays) : - A map with the trading days shown in the chart
timeRange (SessionTimeRange) : - The time range of the session during a trading day
isFinalized (series bool)
One Setup for Life ICTGuided by ICT tutoring, I create this versatile 'One Trading Set Up For Life' indicator
This indicator shows a different way of viewing the "Highs and Lows" of Previous Sessions, drawing from the current day until 09:30 AM, the time at which the Highs and Lows of the previous day's sessions can be taken into consideration for a Reversal or for a Take profit.
Levels tested after 9.30am will be blocked so you have a good and clear view of the levels affected
Timing Session =
London: 02:00 to 05:00
New York: 9.30am to 12.30pm
Lunch: 12.30pm to 1pm
PM Session: 1.30pm to 4pm
The user has the possibility to:
- Choose to view sessions or not
- Choose to show levels from previous sessions
- Choose to show today's session levels
- Choose between 08:30 and 09:30 the starting time for the Liquidity taken
- Choose to view High and Low only from the previous day
- See both the name of the Sessions and the price of the levels
The indicator must be used as ICT shows in its concepts, the indicator takes into consideration both previous sessions and today's sessions, and the session levels can be used both for a reversal and for a possible Take Profit like the example here under
Reversal =
Possible Take Profit =
If something is not clear, comment below and I will reply as soon as possible.
NYCSessionLibrary "NYCSession"
Library for New York trading session time functions
@author abneralvarado
@version 1.0
isInNYSession(sessionStart, sessionEnd)
Determines if the current bar is within New York trading session
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM) like 0930 for 9:30 AM ET
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM) like 1600 for 4:00 PM ET
Returns: True if current bar is within the NY session time, false otherwise
getNYSessionStartTime(lookback, sessionStart)
Gets the start time of NY session for a given bar
Parameters:
lookback (simple int) : Bar index to check (0 is current bar)
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
Returns: Unix timestamp for the start of NY session on the given bar's date
getNYSessionEndTime(lookback, sessionEnd)
Gets the end time of NY session for a given bar
Parameters:
lookback (simple int) : Bar index to check (0 is current bar)
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
Returns: Unix timestamp for the end of NY session on the given bar's date
isNYSessionOpen(sessionStart)
Checks if current bar opens the NY session
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
Returns: True if current bar marks the session opening, false otherwise
isNYSessionClose(sessionEnd)
Checks if current bar closes the NY session
Parameters:
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
Returns: True if current bar marks the session closing, false otherwise
isWeekday()
Determines if the current day is a weekday (Mon-Fri)
Returns: True if current bar is on a weekday, false otherwise
getSessionBackgroundColor(sessionStart, sessionEnd, bgColor)
Gets session background color with transparency
Parameters:
sessionStart (simple int) : Starting time of NY session in 24hr format (HHMM)
sessionEnd (simple int) : Ending time of NY session in 24hr format (HHMM)
bgColor (color) : Background color for session highlighting
Returns: Color value for background or na if not in session
London Breakout Tracker - Box Style📊 London Breakout Tracker (Pine Script v6)
This script is designed to track the Asian session range and identify breakout opportunities when the London session begins. It highlights high-probability trade setups and helps avoid fakeouts or overly wide ranges.
🧱 1. Session Time Definitions (Adjusted for Kenyan Time)
The Asian session is defined as:
3:00 AM to 11:00 AM (Kenyan Time)
🔐 2. Asian Session High & Low
During the Asian session:
The script tracks the highest high and lowest low to define the range.
These are stored in variables: asianHigh and asianLow.
🧊 3. Box Drawing for the Asian Range
Once the Asian session ends:
A visual box is drawn around the session using box.new().
This box spans from the session start to end bars and from the high to low.
It helps visually see the range price must break out from.
🚨 4. Breakout Signals
After the Asian session:
A Long Breakout signal is generated if:
The candle closes above the Asian High.
A Short Breakout signal is generated if:
The candle closes below the Asian Low.
This corresponds to 00:00 to 08:00 UTC
These are shown with:
✅ Green up label for long breakouts
❌ Red down label for short breakouts
🧯 5. Fakeout Detection
If price breaks out but closes back inside the Asian range, it’s marked as a Fakeout:
Long Fakeout: Price breaks above high, then closes back below.
Short Fakeout: Price breaks below low, then closes back above.
These are marked with orange X-crosses above or below candles.
⚠️ 6. Wide Range Filter
If the Asian session range is too wide (e.g. > 40 pips), a gray background is drawn.
This warns you not to trade that day since breakouts from wide ranges are unreliable.
📣 7. Alert Conditions
The script can trigger alerts in TradingView when:
🔔 A Long or Short Breakout occurs
⚠️ A Fakeout is detected
You can set these up via the TradingView alert system.
🎯 Overall Purpose:
The script helps you:
Clearly see the Asian session range
Identify breakout opportunities at the London open
Avoid trading during fakeouts or wide-range sessions
Get alerted when breakout/fakeout conditions occur
2022 Model ICT Entry Strategy [TradingFinder] One Setup For Life🔵 Introduction
The ICT 2022 model, introduced by Michael Huddleston, is an advanced trading strategy rooted in liquidity and price imbalance, where time and price serve as the core elements. This ICT 2022 trading strategy is an algorithmic approach designed to analyze liquidity and imbalances in the market. It incorporates concepts such as Fair Value Gap (FVG), Liquidity Sweep, and Market Structure Shift (MSS) to help traders identify liquidity movements and structural changes in the market, enabling them to determine optimal entry and exit points for their trades.
This Full ICT Day Trading Model empowers traders to pinpoint the Previous Day High/Low as well as the highs and lows of critical sessions like the London and New York sessions. These levels act as Liquidity Zones, which are frequently swept prior to a market structure shift (MSS) or a retracement to areas such as Optimal Trade Entry (OTE).
Bullish :
Bearish :
🔵 How to Use
The ICT 2022 model is a sophisticated trading strategy that focuses on identifying key liquidity levels and price movements. It operates based on two main principles. In the first phase, the price approaches liquidity zones and sweeps critical levels such as the previous day’s high or low and key session levels.
This movement is known as a Liquidity Sweep. In the second phase, following the sweep, the price retraces to areas like the FVG (Fair Value Gap), creating ideal entry points for trades. Below is a detailed explanation of how to apply this strategy in bullish and bearish setups.
🟣 Bullish ICT 2022 Model Setup
To use the ICT 2022 model in a bullish setup, start by identifying the Previous Day High/Low or key session levels, such as those of the London or New York sessions. In a bullish setup, the price usually moves downward first, sweeping the Liquidity Low. This move, known as a Liquidity Sweep, reflects the collection of buy orders by major market participants.
After the liquidity sweep, the price should shift market structure and start moving upward; this shift, referred to as Market Structure Shift (MSS), signals the beginning of an upward trend. Following MSS, areas like FVG, located within the Discount Zone, are identified. At this stage, the trader waits for the price to retrace to these zones. Once the price returns, a long trade is executed.
Finally, the stop-loss should be set below the liquidity low to manage risk, while the take-profit target is usually placed above the previous day’s high or other identified liquidity levels. This structure enables traders to take advantage of the upward price movement after the liquidity sweep.
🟣 Bearish ICT 2022 Model Setup
To identify a bearish setup in the ICT 2022 model, begin by marking the Previous Day High/Low or key session levels, such as the London or New York sessions. In this scenario, the price typically moves upward first, sweeping the Liquidity High. This move, known as a Liquidity Sweep, signifies the collection of sell orders by key market players.
After the liquidity sweep, the price should shift market structure downward. This movement, called the Market Structure Shift (MSS), indicates the start of a downtrend. Following MSS, areas such as FVG, found within the Premium Zone, are identified. At this stage, the trader waits for the price to retrace to these areas. Once the price revisits these zones, a short trade is executed.
In this setup, the stop-loss should be placed above the liquidity high to control risk, while the take-profit target is typically set below the previous day’s low or another defined liquidity level. This approach allows traders to capitalize on the downward price movement following the liquidity sweep.
🔵 Settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
FVG Length : Default is 120 Bar.
MSS Length : Default is 80 Bar.
FVG Filter : This refines the number of identified FVG areas based on a specified algorithm to focus on higher quality signals and reduce noise.
Types of FVG filters :
Very Aggressive Filter: Adds a condition where, for an upward FVG, the last candle's highest price must exceed the middle candle's highest price, and for a downward FVG, the last candle's lowest price must be lower than the middle candle's lowest price. This minimally filters out FVGs.
Aggressive Filter: Builds on the Very Aggressive mode by ensuring the middle candle is not too small, filtering out more FVGs.
Defensive Filter: Adds criteria regarding the size and structure of the middle candle, requiring it to have a substantial body and specific polarity conditions, filtering out a significant number of FVGs.
Very Defensive Filter: Further refines filtering by ensuring the first and third candles are not small-bodied doji candles, retaining only the highest quality signals.
🔵 Conclusion
The ICT 2022 model is a comprehensive and advanced trading strategy designed around key concepts such as liquidity, price imbalance, and market structure shifts (MSS). By focusing on the sweep of critical levels such as the previous day’s high/low and important trading sessions like London and New York, this strategy enables traders to predict market movements with greater precision.
The use of tools like FVG in this model helps traders fine-tune their entry and exit points and take advantage of bullish and bearish trends after liquidity sweeps. Moreover, combining this strategy with precise timing during key trading sessions allows traders to minimize risk and maximize returns.
In conclusion, the ICT 2022 model emphasizes the importance of time and liquidity, making it a powerful tool for both professional and novice traders. By applying the principles of this model, you can make more informed trading decisions and seize opportunities in financial markets more effectively.
Extended Hours Volume FlagOverview: The Extended Hours Volume Flag Indicator is a powerful tool designed for traders who are interested in monitoring and analyzing the volume activity during the extended trading hours—specifically the premarket (4:00 AM to 9:30 AM) and afterhours (4:00 PM to 8:00 PM) sessions. This indicator identifies and flags stocks where the trading volume during these extended hours exceeds 20% of the Average Volume (AVOL) during regular trading hours. Such occurrences often signal unusual activity or potential market-moving events, which can be crucial for informed trading decisions.
Concept: Volume is a critical factor in trading, often providing insights into market sentiment and potential price movements. However, volume during extended hours can be particularly revealing as it may indicate heightened interest or activity outside of the regular trading session. The Extended Hours Volume Flag Indicator is built on the concept that significant volume during premarket or afterhours trading sessions, relative to the average regular session volume, could be an early indicator of upcoming volatility or trends.
How It Works:
Session Segmentation: The indicator distinguishes between regular trading hours (9:30 AM to 4:00 PM) and extended hours (premarket and afterhours). It accumulates the trading volume separately for these sessions.
Volume Comparison: It calculates the Average Volume (AVOL) over a user-defined period (default is 14 days) during regular trading hours. It then compares the extended hours volume to this AVOL.
Flagging Condition: If the volume during the extended hours exceeds 20% of the AVOL, the indicator flags the stock with a warning symbol on the chart. This visual cue helps traders quickly identify stocks with potentially significant afterhours or premarket activity.
Reset Mechanism: The accumulated volumes reset at the start of the new trading day, ensuring accurate calculations for each day.
Usage: This indicator is ideal for traders who are looking for early signals of market activity outside regular hours, which might not be immediately visible when looking solely at price action. It is particularly useful for day traders and swing traders who want to keep an eye on potential premarket or afterhours catalysts.
FIRST-HOUR TOOL V.1.8.08.23Three horizontal lines are drawn on the chart to represent session prices. These prices are calculated based on the user-specified session:
"FirstHour Session High" represents the highest price reached during the firsthour session.
"FirstHour Session Open" represents the opening price of the firsthour session
"FirstHour Session Low" represents the lowest price reached during the firsthour session.
These prices are respectively colored with light blue, light yellow, and light pink.
The chart background can change color based on whether the current time is within the specified session. If the current time is within the session, the background will be colored in semi-transparent aqua green. Otherwise, it will remain transparent.
Upward-pointing triangle markers are used to highlight points where the closing price crosses above (crossover) or below (crossunder) the session levels.
These markers appear below the corresponding bar.
They are colored based on the type of crossover:
Yellow for crossover above the "FirstHour High"
Red for crossover above the "FirstHour Open"
Green for crossover above the "FirstHour Low"
Alerts:
Alert messages are generated when crossovers or crossunders of the closing price relative to the session levels occur.
The alerts appear once per bar. Alerts are generated for the following events:
Crossover of the price above the "Session High" with the message "High First Hour Crossover."
Crossunder of the price below the "Session Open" with the message "Open First Hour Crossunder."
Crossunder of the price below the "Session Low" with the message "Low First Hour Crossunder."
Crossover of the price above the "Session Low" with the message "Low First Hour Crossover."
In summary, this indicator provides a visual representation of session prices and events, helping traders spot significant crossovers and crossunders relative to key price levels.
Author @tumiza999
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
NYSE, Euronext, and Shanghai Stock Exchange Hours IndicatorNYSE, Euronext, and Shanghai Stock Exchange Hours Indicator
This script is designed to enhance your trading experience by visually marking the opening and closing hours of major global stock exchanges: the New York Stock Exchange (NYSE), Euronext, and Shanghai Stock Exchange. By adding vertical lines and background fills during trading sessions, it helps traders quickly identify these critical periods, potentially informing better trading decisions.
Features of This Indicator:
NYSE, Euronext, and Shanghai Stock Exchange Hours: Displays vertical lines at market open and close times for these three exchanges. You can easily switch between showing or hiding the different exchanges to customize the indicator for your needs.
Background Fill: Highlights the trading hours of these exchanges using faint background colors, making it easy to spot when markets are in session. This feature is crucial for timing trades around overlapping trading hours and volume peaks.
Customizable Visuals: Adjust the color, line style (solid, dotted, dashed), and line width to match your preferences, making the indicator both functional and visually aligned with your chart's aesthetics.
How to Use the Indicator:
Add the Indicator to Your Chart: Add the script to your chart from the TradingView script library. Once added, the indicator will automatically plot vertical lines at the opening and closing times of the NYSE, Euronext, and Shanghai Stock Exchange.
Customize Display Settings: Choose which exchanges to display by enabling or disabling the NYSE, Euronext, or Shanghai sessions in the indicator settings. This allows you to focus only on the exchanges that are relevant to your trading strategy.
Adjust Visual Properties: Customize the appearance of the vertical lines and background fill through the settings. Modify the color of each exchange, adjust the line style (solid, dotted, dashed), and control the line thickness to suit your chart preferences. The background fill can also be customized to clearly highlight active trading sessions.
Identify Key Market Hours: Use the vertical lines and background fills to identify the market open and close times. This is particularly useful for understanding how price action changes during specific trading hours or for finding high liquidity periods when multiple markets are open simultaneously.
Adapt Trading Strategies: By knowing when major stock exchanges are open, you can adapt your trading strategy to take advantage of potential price movements, increased volatility, or volume. This can help you avoid low-liquidity times and capitalize on more active trading periods.
This indicator is especially valuable for traders focusing on cross-market dynamics or those interested in understanding how different sessions influence market liquidity and price action. With this tool, you can gain insight into market conditions and adapt your trading strategies accordingly. The clean visual separation of session times helps you maintain context, whether you're trading Forex, stocks, or cryptocurrencies.
Disclaimer: This script is intended for informational and educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any financial instrument. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions. Trading involves risk, and past performance is not indicative of future results.
Time Range### Indicator Name: **Time Range**
#### Description:
The **Time Range** indicator allows users to highlight specific time ranges on a chart for each day of the week. It uses customizable time inputs for every day (Monday to Sunday), allowing the user to define trading sessions or any time-based range. These sessions are visualized by shading the background of the chart within the defined periods.
#### Key Features:
- **Custom Sessions**: For each day of the week (Monday to Sunday), the user can define a unique time session by specifying the start time using the input fields.
- **Day-wise Session Activation**: The user can toggle the activation of sessions for each day by using checkboxes. If the session for a particular day is disabled, no background shading will appear for that day.
- **Background Highlighting**: When a session is active, the background of the chart during the specified session period will be shaded in gray with a 70% transparency. This helps the user visually identify active time ranges across multiple days.
#### Use Cases:
- **Highlighting Trading Sessions**: Traders can use this indicator to easily visualize specific market sessions such as the New York or London trading sessions.
- **Visualizing Custom Time Blocks**: Can be used to highlight any custom time blocks that are important for the trader, such as key trading hours, news release periods, or other time-based strategies.
#### Customizable Parameters:
- **Day Toggles**: Checkboxes to activate or deactivate sessions for each day of the week.
- **Time Range Inputs**: Time range inputs allow the user to set start times for each session, which are applied based on the user's selection for the day.
This indicator helps streamline chart analysis by giving clear visual markers for time-based events or trading windows.
time_and_sessionA library that provides utilities for working with trading sessions and time-based conditions. Functions include session checks, date range checks, day-of-week matching, and session high/low calculations for daily, weekly, monthly, and yearly timeframes. This library streamlines time-related calculations and enhances time-based strategies and indicators.
Library "time_and_session"
Provides functions for checking time and session-based conditions and retrieving session-specific high and low values.
is_session(session, timeframe, timezone)
Checks if the current time is within the specified trading session
Parameters:
session (string) : The trading session, defined using input.session()
timeframe (string) : The timeframe to use, defaults to the current chart's timeframe
timezone (string) : The timezone to use, defaults to the symbol's timezone
Returns: A boolean indicating whether the current time is within the specified trading session
is_date_range(start_time, end_time)
Checks if the current time is within a specified date range
Parameters:
start_time (int) : The start time, defined using input.time()
end_time (int) : The end time, defined using input.time()
Returns: A boolean indicating whether the current time is within the specified date range
is_day_of_week(sunday, monday, tuesday, wednesday, thursday, friday, saturday)
Checks if the current day of the week matches any of the specified days
Parameters:
sunday (bool) : A boolean indicating whether to check for Sunday
monday (bool) : A boolean indicating whether to check for Monday
tuesday (bool) : A boolean indicating whether to check for Tuesday
wednesday (bool) : A boolean indicating whether to check for Wednesday
thursday (bool) : A boolean indicating whether to check for Thursday
friday (bool) : A boolean indicating whether to check for Friday
saturday (bool) : A boolean indicating whether to check for Saturday
Returns: A boolean indicating whether the current day of the week matches any of the specified days
daily_high(source)
Returns the highest value of the specified source during the current daily session
Parameters:
source (float) : The data series to evaluate, defaults to high
Returns: The highest value during the current daily session, or na if the timeframe is not suitable
daily_low(source)
Returns the lowest value of the specified source during the current daily session
Parameters:
source (float) : The data series to evaluate, defaults to low
Returns: The lowest value during the current daily session, or na if the timeframe is not suitable
regular_session_high(source, persist)
Returns the highest value of the specified source during the current regular trading session
Parameters:
source (float) : The data series to evaluate, defaults to high
persist (bool) : A boolean indicating whether to retain the last value outside of regular market hours, defaults to true
Returns: The highest value during the current regular trading session, or na if the timeframe is not suitable
regular_session_low(source, persist)
Returns the lowest value of the specified source during the current regular trading session
Parameters:
source (float) : The data series to evaluate, defaults to low
persist (bool) : A boolean indicating whether to retain the last value outside of regular market hours, defaults to true
Returns: The lowest value during the current regular trading session, or na if the timeframe is not suitable
premarket_session_high(source, persist)
Returns the highest value of the specified source during the current premarket trading session
Parameters:
source (float) : The data series to evaluate, defaults to high
persist (bool) : A boolean indicating whether to retain the last value outside of premarket hours, defaults to true
Returns: The highest value during the current premarket trading session, or na if the timeframe is not suitable
premarket_session_low(source, persist)
Returns the lowest value of the specified source during the current premarket trading session
Parameters:
source (float) : The data series to evaluate, defaults to low
persist (bool) : A boolean indicating whether to retain the last value outside of premarket hours, defaults to true
Returns: The lowest value during the current premarket trading session, or na if the timeframe is not suitable
postmarket_session_high(source, persist)
Returns the highest value of the specified source during the current postmarket trading session
Parameters:
source (float) : The data series to evaluate, defaults to high
persist (bool) : A boolean indicating whether to retain the last value outside of postmarket hours, defaults to true
Returns: The highest value during the current postmarket trading session, or na if the timeframe is not suitable
postmarket_session_low(source, persist)
Returns the lowest value of the specified source during the current postmarket trading session
Parameters:
source (float) : The data series to evaluate, defaults to low
persist (bool) : A boolean indicating whether to retain the last value outside of postmarket hours, defaults to true
Returns: The lowest value during the current postmarket trading session, or na if the timeframe is not suitable
weekly_high(source)
Returns the highest value of the specified source during the current weekly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to high
Returns: The highest value during the current weekly session, or na if the timeframe is not suitable
weekly_low(source)
Returns the lowest value of the specified source during the current weekly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to low
Returns: The lowest value during the current weekly session, or na if the timeframe is not suitable
monthly_high(source)
Returns the highest value of the specified source during the current monthly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to high
Returns: The highest value during the current monthly session, or na if the timeframe is not suitable
monthly_low(source)
Returns the lowest value of the specified source during the current monthly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to low
Returns: The lowest value during the current monthly session, or na if the timeframe is not suitable
yearly_high(source)
Returns the highest value of the specified source during the current yearly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to high
Returns: The highest value during the current yearly session, or na if the timeframe is not suitable
yearly_low(source)
Returns the lowest value of the specified source during the current yearly session. Can fail on lower timeframes.
Parameters:
source (float) : The data series to evaluate, defaults to low
Returns: The lowest value during the current yearly session, or na if the timeframe is not suitable
RSI Supreme Multi-Method [MyTradingCoder]Introducing the "RSI Supreme Multi-Method" indicator, a powerful tool that combines the Relative Strength Index (RSI) with selectable manipulation methods to identify overbought and oversold conditions in the market, along with the ability to detect divergences for enhanced trading insights.
The indicator features four distinct manipulation methods for the RSI, each providing valuable insights into market conditions:
1. Standard RSI Method: The indicator uses the traditional RSI calculation to identify overbought and oversold areas.
2. Volatility Weighted RSI Method: This method applies a volatility formula to the RSI calculation, allowing for a more responsive indication of market conditions during periods of heightened volatility. Users can adjust the length of the volatility formula to fine-tune this method.
3. Smoothed RSI Method: The smoothed RSI method utilizes a smoothing algorithm to reduce noise in the RSI values, presenting a clearer representation of overbought and oversold conditions. The length of the smoothing can be adjusted to match your trading preferences.
4. Session Weighted RSI Method: With this innovative method, users can specify multipliers for different time sessions throughout the day to manipulate the base RSI. Each session can be customized with start and end times, enabling or disabling specific sessions, and specifying the multiplier for each session. This feature allows traders to adapt the RSI to different market sessions dynamically.
Additionally, the "RSI Supreme Multi-Method" indicator draws divergences on the oscillator, providing an extra layer of analysis for traders. Divergences occur when the direction of the RSI differs from the direction of the price movement, potentially signaling trend reversals.
Key Settings:
RSI Length: Adjust the length of the base RSI before applying any manipulation.
RSI Source: Determine the data source for the base RSI calculation.
Overbought Value: Set the RSI value at which overbought conditions are indicated.
Oversold Value: Set the RSI value at which oversold conditions are indicated.
RSI Type: Choose from four options: Standard, Smoothed, Volatility Manipulated, or Session Manipulated.
Volatility Manipulated Settings: Adjust the length of the volatility formula (applicable to Volatility Manipulated method).
Smoothed Settings: Adjust the length of the smoothing (applicable to Smoothed method).
Session Manipulated Settings: Customize six different time sessions with start and end times, enable or disable specific sessions, and specify multipliers for each session.
Divergence Color: Adjust the color of the drawn divergences to suit your chart's aesthetics.
Divergence Tuning: Fine-tune the sensitivity of the divergence detection for more accurate signals.
The "RSI Supreme Multi-Method" indicator is a versatile and comprehensive tool that can be used to identify overbought and oversold areas, as well as to spot potential trend reversals through divergences. However, like all technical analysis tools, it should be used in conjunction with other indicators and analysis methods to make well-informed trading decisions.
Enhance your trading insights with the "RSI Supreme Multi-Method" indicator and gain an edge in identifying critical market conditions and divergences with precision.
Breaking Bar [5ema]I reused some functions, made by (i believe that):
@LeviathanCapital: Market Sessions.
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How to use?
More suitable for Scalping
1. Plan A: Break out the highest bar
Find the bar with the largest range (high – low) and high volume of the previous N bars.
When the price close breaks down to highest bar, give a SELL signal.
When the price close breaks up the highest, give a BUY signal.
2. Plan B: Break out the bar opened market
The price close breaks through the open bar, give a Buy and Sell signal.
Market sessions: Tokyo, London, Sydney, New York.
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How to set up?
Choose the plan.
Lookback bar to find highest bar.
Right bar: What position of signal will appear from the open market bar (or high bar).
Number break: The maximum bars have price close breaked before giving signal.
Session time: The open and close of market.
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This indicator is for reference only, you need your own method and strategy.
If you have any questions, please let me know in the comments.
Open Interest Profile (OI)- By LeviathanThis script implements the concept of Open Interest Profile, which can help you analyze the activity of traders and identify the price levels where they are opening/closing their positions. This data can serve as a confluence for finding the areas of support and resistance , targets and placing stop losses. OI profiles can be viewed in the ranges of days, weeks, months, Tokyo sessions, London sessions and New York sessions.
A short introduction to Open Interest
Open Interest is a metric that measures the total amount of open derivatives contracts in a specific market at a given time. A valid contract is formed by both a buyer who opens a long position and a seller who opens a short position. This means that OI represents the total value of all open longs and all open shorts, divided by two. For example, if Open Interest is showing a value of $1B, it means that there is $1B worth of long and $1B worth of short contracts currently open/unsettled in a given market.
OI increasing = new long and short contracts are entering the market
OI decreasing = long and short contracts are exiting the market
OI unchanged = the net amount of positions remains the same (no new entries/exits or just a transfer of contracts occurring)
About this indicator
*This script is basically a modified version of my previous "Market Sessions and Volume Profile by @LeviathanCapital" indicator but this time, profiles are generated from Tradingview Open Interest data instead of volume (+ some other changes).
The usual representation of OI shows Open Interest value and its change based on time (for a particular day, time frame or each given candle). This indicator takes the data and plots it in a way where you can see the OI activity (change in OI) based on price levels. To put it simply, instead of observing WHEN (time) positions are entering/exiting the market, you can now see WHERE (price) positions are entering/exiting the market. This is the same concept as when it comes to Volume and Volume profile and therefore, similar strategies and ways of understanding the given data can be applied here. You can even combine the two to gain an edge (eg. high OI increase + Volume Profile showing dominant market selling = possible aggressive shorts taking place)
Green nodes = OI increase
Red nodes = OI decrease
A cluster of large green nodes can be used for support and resistance levels (*trapped traders theory) or targets (lots of liquidations and stop losses above/below), OI Profile gaps can present an objective for the price to fill them (liquidity gaps, imbalances, inefficiencies, etc), and more.
Indicator settings
1. Session/Lookback - Choose the range from where the OI Profile will be generated
2. OI Profile Mode - Mode 1 (shows only OI increase), Mode 2 (shows both OI increase and decrease), Mode 3 (shows OI decrease on left side and OI increase on the right side).
3. Show OI Value Area - Shows the area where most OI activity took place (useful as a range or S/R level )
4. Show Session Box - Shows the box around chosen sessions/lookback
5. Show Profile - Show/hide OI Profile
6. Show Current Session - Show/hide the ongoing session
7. Show Session Labels - Show/hide the text labels for each session
8. Resolution - The higher the value, the more refined a profile is, but fewer profiles are shown on the chart
9. OI Value Area % - Choose the percentage of VA (same as in Volume Profile's VA)
10. Smooth OI Data - Useful for assets that have very large spikes in OI over large bars, helps create better profiles
11. OI Increase - Pick the color of OI increase nodes in the profile
12. OI Decrease - Pick the color of OI decrease nodes in the profile
13. Value Area Box - Pick the color of the Value Area Box
14. Session Box Thickness - Pick the thickness of the lines surrounding the chosen sessions
Advice
The indicator calculates the profile based on candles - the more candles you can show, the better profile will be formed. This means that it's best to view most sessions on timeframes like 15min or lower. The only exception is the Monthly profile, where timeframes above 15min should be used. Just take a few minutes and switch between timeframes and sessions and you will figure out the optimal settings.
This is the first version of Open Interest Profile script so please understand that it will be improved in future updates.
Thank you for your support.
** Some profile generation elements are inspired by @LonesomeTheBlue's volume profile script
OHLCVRangeXThe OHLCVRange library provides modular range-building utilities for Pine Script v6 based on custom conditions like time, price, volatility, volume, and pattern detection. Each function updates a persistent range (OHLCVRange) passed in from the calling script, based on live streaming candles.
This library is designed to support dynamic windowing over incoming OHLCV bars, with all persistent state handled externally (in the indicator or strategy). The library merely acts as a filter and updater, appending or clearing candles according to custom logic.
📦
export type OHLCVRange
OHLCV.OHLCV candles // Sliding window of candles
The OHLCVRange is a simple container holding an array of OHLCV.OHLCV structures.
This structure should be declared in the indicator using var to ensure persistence across candles.
🧩 Range Updater Functions
Each function follows this pattern:
export updateXxxRange(OHLCVRange r, OHLCV.OHLCV current, ...)
r is the range to update.
current is the latest OHLCV candle (typically from your indicator).
Additional parameters control the behavior of the range filter.
🔁 Function List
1. Fixed Lookback Range
export updateFixedRange(OHLCVRange r, OHLCV.OHLCV current, int barsBack)
Keeps only the last barsBack candles.
Sliding window based purely on number of bars.
2. Session Time Range
export updateSessionRange(OHLCVRange r, OHLCV.OHLCV current, int minuteStart, int minuteEnd)
Keeps candles within the [minuteStart, minuteEnd) intraday session.
Clears the range once out of session bounds.
3. Price Zone Range
export updatePriceZoneRange(OHLCVRange r, OHLCV.OHLCV current, float minP, float maxP)
Retains candles within the vertical price zone .
Clears when a candle exits the zone.
4. Consolidation Range
export updateConsolidationRange(OHLCVRange r, OHLCV.OHLCV current, float thresh)
Stores candles as long as the candle range (high - low) is less than or equal to thresh.
Clears on volatility breakout.
5. Volume Spike Range
export updateVolumeSpikeRange(OHLCVRange r, OHLCV.OHLCV current, float avgVol, float mult, int surround)
Triggers a new range when a volume spike ≥ avgVol * mult occurs.
Adds candles around the spike (total surround * 2 + 1).
Can be used to zoom in around anomalies.
6. Engulfing Pattern Range
export updateEngulfingRange(OHLCVRange r, OHLCV.OHLCV current, int windowAround)
Detects bullish or bearish engulfing candles.
Stores 2 * windowAround + 1 candles centered around the pattern.
Clears if no valid engulfing pattern is found.
7. HTF-Aligned Range
export updateHTFAlignedRange(OHLCVRange r, OHLCV.OHLCV current, OHLCV.OHLCV prevHtf)
Used when aligning lower timeframe candles to higher timeframe bars.
Clears and restarts the range on HTF bar transition (compare prevHtf.bar_index with current).
Requires external management of HTF candle state.
💡 Usage Notes
All OHLCVRange instances should be declared as var in the indicator to preserve state:
var OHLCVRange sessionRange = OHLCVRange.new()
sessionRange := OHLCVRange.updateSessionRange(sessionRange, current, 540, 900)
All OHLCV data should come from the OHLCVData library (v15 or later):
import userId/OHLCVData/15 as OHLCV
OHLCV.OHLCV current = OHLCV.getCurrentChartOHLCV()
This library does not use var internally to enforce clean separation of logic and persistence.
📅 Planned Enhancements
Fib zone ranges: capture candles within custom Fibonacci levels.
Custom event ranges: combine multiple filters (e.g., pattern + volume spike).
Trend-based ranges: windowing based on moving average or trend breaks.
