Fourier Adjusted Average True Range [BackQuant]Fourier Adjusted Average True Range
1. Conceptual Foundation and Innovation
The FA-ATR leverages the principles of Fourier analysis to dissect market prices into their constituent cyclical components. By applying Fourier Transform to the price data, the FA-ATR captures the dominant cycles and trends which are often obscured in noisy market data. This integration allows the FA-ATR to adapt its readings based on underlying market dynamics, offering a refined view of volatility that is sensitive to both market direction and momentum.
2. Technical Composition and Calculation
The core of the FA-ATR involves calculating the traditional ATR, which measures market volatility by decomposing the entire range of price movements. The FA-ATR extends this by incorporating a Fourier Transform of price data to assess cyclical patterns over a user-defined period 'N'. This process synthesizes both the magnitude of price changes and their rhythmic occurrences, resulting in a more comprehensive volatility indicator.
Fourier Transform Application: The Fourier series is calculated using price data to identify the fundamental frequency of market movements. This frequency helps in adjusting the ATR to reflect more accurately the current market conditions.
Dynamic Adjustment: The ATR is then adjusted by the magnitude of the dominant cycle from the Fourier analysis, enhancing or reducing the ATR value based on the intensity and phase of market cycles.
3. Features and User Inputs
Customizability: Traders can modify the Fourier period, ATR period, and the multiplication factor to suit different trading styles and market environments.
Visualization : The FA-ATR can be plotted directly on the chart, providing a visual representation of volatility. Additionally, the option to paint candles according to the trend direction enhances the usability and interpretative ease of the indicator.
Confluence with Moving Averages: Optionally, a moving average of the FA-ATR can be displayed, serving as a confluence factor for confirming trends or potential reversals.
4. Practical Applications
The FA-ATR is particularly useful in markets characterized by periodic fluctuations or those that exhibit strong cyclical trends. Traders can utilize this indicator to:
Adjust Stop-Loss Orders: More accurately set stop-loss orders based on a volatility measure that accounts for cyclical market changes.
Trend Confirmation: Use the FA-ATR to confirm trend strength and sustainability, helping to avoid false signals often encountered in volatile markets.
Strategic Entry and Exit: The indicator's responsiveness to changing market dynamics makes it an excellent tool for planning entries and exits in a trend-following or a breakout trading strategy.
5. Advantages and Strategic Value
By integrating Fourier analysis, the FA-ATR provides a volatility measure that is both adaptive and anticipatory, giving traders a forward-looking tool that adjusts to changes before they become apparent through traditional indicators. This anticipatory feature makes it an invaluable asset for traders looking to gain an edge in fast-paced and rapidly changing market conditions.
6. Summary and Usage Tips
The Fourier Adjusted Average True Range is a cutting-edge development in technical analysis, offering traders an enhanced tool for assessing market volatility with increased accuracy and responsiveness. Its ability to adapt to the market's cyclical nature makes it particularly useful for those trading in highly volatile or cyclically influenced markets.
Traders are encouraged to integrate the FA-ATR into their trading systems as a supplementary tool to improve risk management and decision-making accuracy, thereby potentially increasing the effectiveness of their trading strategies.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Cari dalam skrip untuk "range"
EM Visible Range Volume Profile█ OVERVIEW
ᴇᴍ VRVP (Visible Range Volume Profile) indicator calculates the volume profile within the visible range of prices.
Volume Profile is an advanced technical analysis indicator that shows trading activity over a specified period of time at certain price levels.
The indicator plots a histogram on the chart that reflects dominant or significant price levels based that are based on volume.
VP concept
VP Components
Open, High, Low, Close:
There are different types of volume profile indicators but the majority of them will designate the OHLC.
Point of Control:
A price level with the most traded volume during one session, also known as POC.
High Volume Node (HVN):
Area of high volume relative to surrounding price action.
Low Volume Node (LVN):
Area of low volume relative to surrounding price action.
Analysis of price in relation to high and low volume nodes is useful when building context around your trades.
█ VOLUME PROFILE STRATEGIES
The distribution of a volume profile can help you determine the strength of a trend and spot potential reversal zones. Let’s take a look at the five different distribution types.
Neutral D
In order for price to break away from value, either the buyers or the sellers will have to become more aggressive than the other side. When this occurs, it gives us with a vital piece of information.
Now we know who were the agressors at this price level: either the buyers or the sellers. That's why this is a good level for a trading setup if the price bounces back.
Bearish P and Bullish P
Bearish P — reversal. Bullish P — confirmation.
Bearish Ь and Bullish Ь
Bearish Ь — confirmation. Bullish Ь — reversal.
Examples
█ INPUTS
Width — amplitude of the VP histogram.
Grid — the number of columns of the VP histogram.
Delta of volumes — combinatorial determination of the ratios of sellers and buyers.
In quoted units — conversion in units of quoted currency.
Logarithmic scale — recalculation the grid step to the logarithmic scale of the chart.
HTF — (Higher Timeframe) calculation of VP for the period of the selected timeframe. ISO: Isolated computation in HTF period.
Palette: Total volume, Volume of buyers, Volume of sellers, HTF bars.
Warnings: colour of the «⚠» icon, language of information in the Tooltip.
Addition: ᴇᴍ CHN-RMA — a grid of moving averages with periods of centered hexagonal numbers.
█ ОБЩИЕ СВЕДЕНИЯ
ᴇᴍ VRVP (Visible Range Volume Profile) рассчитывает профиль объёма в видимом диапазоне цен.
Профиль объёма — это продвинутый индикатор технического анализа, который показывает торговую активность за условленный период времени на определённых ценовых уровнях.
Индикатор строит на графике гистограмму, отражающую доминирующие или значимые ценовые уровни, основанные на объёме.
█ НАСТРОЙКИ
Ширина — амплитуда гистограммы VP.
Сетка — количество колонок гистограммы VP.
Дельта объёмов — комбинаторное определение соотношений продаж и покупок.
В котируемых единицах — пересчёт в единицах котируемой валюты.
Логарифмическая шкала — пересчёт шага сетки на логарифмическую шкалу графика.
HTF — (Higher Timeframe) расчёт VP за период выбранного таймфрейма. ISO: Изолированное вычисление в HTF-периоде.
Палитра: Суммарный объём, Объём покупок, Объём продаж, Бары HTF.
Предупреждения: цвет значка «⚠», язык информации в Tooltip.
Дополнение: ᴇᴍ CHN-RMA — сетка скользящих средних с периодами центрированных гексагональных чисел.
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
Deck@r True Range IndexThis Pine Script calculates the True Range Index (TRI) using ATR and Fib Levels and uses the result to generate buy and sell signals based on certain conditions.
Here's a breakdown of the code:
Inputs:
atr_period: Determines the period for calculating the Average True Range (ATR), preferred setting at 14.
atr_multiplier: Multiplier used to set the width of the ATR bands preferred setting at 1.
Calculations:
atr_value: Calculates the Average True Range (ATR) using the input period.
upper_band: Calculates the upper band of the ATR bands using a Simple Moving Average (SMA) of the close price plus the ATR multiplied by the multiplier.
lower_band: Calculates the lower band of the ATR bands using a Simple Moving Average (SMA) of the close price minus the ATR multiplied by the multiplier.
midline_75 and midline_25: Calculate midlines at Fibonacci retracement levels of 0.75 and 0.25, respectively, between the upper and lower bands.
Plotting:
Plots the upper and lower bands of the ATR bands.
Optionally plots midlines for the ATR bands (commented out in the code).
Buy and Sell Conditions:
buy_condition: Defines a condition for a buy signal, which occurs when the close price is above the midline at the Fibonacci retracement level of 0.25.
sell_condition: Defines a condition for a sell signal, which occurs when the close price is below the midline at the Fibonacci retracement level of 0.75.
Candle Color:
Sets the candle color based on the buy and sell conditions.
Buy and Sell Signals:
buy_signal: Checks for a buy signal when the close price crosses above the midline at the Fibonacci retracement level of 0.25.
sell_signal: Checks for a sell signal when the close price crosses below the midline at the Fibonacci retracement level of 0.75.
Plots buy and sell signals on the chart.
DEMA Adjusted Average True Range [BackQuant]The use of the Double Exponential Moving Average (DEMA) within your Adjusted Average True Range (ATR) calculation serves as a cornerstone for enhancing the indicator's responsiveness to market changes. To delve deeper into why DEMA is employed specifically in the context of your ATR calculation, let's explore the inherent qualities of DEMA and its impact on the ATR's performance.
DEMA and Its Advantages
As previously mentioned, DEMA was designed to offer a more responsive alternative to the traditional Exponential Moving Average (EMA). By giving more weight to recent price data, DEMA reduces the lag typically associated with moving averages. This reduction in lag is especially beneficial for short-term traders looking to capitalize on trend reversals and other market movements as swiftly as possible.
The calculation of DEMA involves the following steps:
Calculate EMA1: This is the Exponential Moving Average of the price.
Calculate EMA2: This is the Exponential Moving Average of EMA1, thus it is a smoothing of a smoothing, leading to a greater lag.
Formulate DEMA: The formula
EMA1 = EMA of price
EMA2 = EMA of EMA1
DEMA = (2 x EMA1) - EMA2
effectively doubles the weighting of the most recent data points by subtracting the lagged, double-smoothed EMA2 from twice the single-smoothed EMA1.
This process enhances the moving average's sensitivity to recent price movements, allowing the DEMA to adhere more closely to the price bars than either EMA1 or EMA2 alone.
Integration with ATR
In the context of your ATR calculation, the integration of DEMA plays a crucial role in defining the indicator's core functionality. Here's a detailed explanation of how DEMA affects the ATR calculation:
Initial Determination of DEMA : By applying the DEMA formula to the chosen source data (which can be adjusted to use Heikin Ashi candle close prices for an even smoother analysis), you set a foundation for a more reactive trend-following mechanism within the ATR framework.
Application to ATR Bands : The calculated DEMA serves as the central line from which the ATR bands are derived. The ATR value, multiplied by a user-defined factor, is added to and subtracted from the DEMA to form the upper and lower bands, respectively. This dynamic adjustment not only reflects the volatility based on the ATR but does so in a way that is closely aligned with the most recent price action, thanks to the utilization of DEMA.
Enhanced Signal Quality : The responsiveness of DEMA ensures that the ATR bands adjust more promptly to changes in market conditions. This quality is vital for traders who rely on the ATR bands to identify potential entry and exit points, trend reversals, or to assess market volatility.
By employing DEMA as the core component in calculating the Adjusted Average True Range, your indicator leverages DEMA's reduced lag and increased weight on recent data to provide a more timely and accurate measure of market volatility. This innovative approach enhances the utility of the ATR by making it not only a tool for assessing volatility but also a more reactive indicator for trend analysis and trading signal generation.
The main concept of combining these is to reduce lag, get a more robust signal and still capture clear trends over medium time horizons.
For me, this is best used in confluence with other indicators, it can be made faster in order to get fasters response time, or slower. This is all depending on the needs of you as a trader.
User Inputs:
The script offers several user-configurable inputs, such as the period lengths for DEMA and ATR calculations, the multiplication factor for the ATR, and options to use Heikin Ashi candles or standard price data. Additionally, it allows for the toggling of visual features, like the plotting of the DEMA ATR and its moving average, and the application of color-coded trends on price bars.
Additional Features:
Moving Average Confluence: Traders can opt to display a moving average of the DEMA ATR, choosing from various types (e.g., SMA, EMA, HMA). This feature provides a layer of confluence, aiding in the identification of trend direction and strength.
Trend Identification :
The script employs logical conditions to ascertain the trend direction based on the movement of the DEMA ATR. It assigns colors to represent bullish or bearish trends, which are reflected in the plotted lines and the coloring of price bars.
Alerts :
Customizable alert conditions for trend reversals enhance the utility of the indicator for active trading, notifying users of significant changes in trend direction.
1D Backtests
We include these backtests as a general proxy for how they work.
Please do your own calibrating to suit it to your own needs and backtest.
Past results don't = future results but they can help you understand how it functions.
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
Time Candle Range HistoryThe 'Intraday Candle Range Average' indicator is designed to provide traders with insights into the average price range of intraday candles, specifically focusing on the period around 9:30 AM. By calculating the difference between the high and low of candles occurring at 9:30 AM, the indicator offers a dynamic view of market volatility during this critical time window. Users can customize parameters such as the number of days to consider for the average calculation, allowing for flexibility in analyzing short-term price movements. Additionally, the indicator offers a clear visualization of the current candle range compared to the historical average, aiding traders in identifying potential trading opportunities based on volatility patterns. Whether used independently or in conjunction with other technical analysis tools, the 'Intraday Candle Range Average' indicator empowers traders with valuable insights into intraday market dynamics.
Opening Range Reversal ZonesThis script finds a reversal zone beyond the opening range for the selected period. I borrowed most of the opening range script itself from asenski.
I added a few things:
Trade Entry Times -- this restricts the "alert times."
Shading for the above mentioned times for the two "reversal" zones
A couple of other visuals for lines for the hi, mid, low of the opening range and lines for the fibs
Alerts while in the trading entry time session for fibbonacci crossovers.
I use this on NDX, SPY, and QQQs and have found buying "at the money" 0DTE puts in the "red zone" or 0DTE calls in the "green zone" frequently wins.
I have no statistics, as I am very methodical when I choose to enter, paying attention to the news, recent momentum, etc, and am not blindly entering when alert comes, but when one does, I do research and enter a trade.
In any case, thought I would share.
Price Cross Time Custom Range Interactive█ OVERVIEW
This indicator was a time-based indicator and intended as educational purpose only based on pine script v5 functions for ta.cross() , ta.crossover() and ta.crossunder() .
I realised that there is some overlap price with the cross functions, hence I integrate them into Custom Range Interactive with value variance and overlap displayed into table.
This was my submission for Pinefest #1 , I decided to share this as public, I may accidentally delete this as long as i keep as private.
█ INSPIRATION
Inspired by design, code and usage of CAGR. Basic usage of custom range / interactive, pretty much explained here . Credits to TradingView.
█ FEATURES
1. Custom Range Interactive
2. Label can be resize and change color.
3. Label show tooltip for price and time.
4. Label can be offset to improve readability.
5. Table can show price variance when any cross is true.
6. Table can show overlap if found crosss is overlap either with crossover and crossunder.
7. Table text color automatically change based on chart background (light / dark mode).
8. Source 2 is drawn as straight line, while Source 1 will draw as label either above line for crossover, below line for crossunder and marked 'X' if crossing with Source 2's line.
9. Cross 'X' label can be offset to improve readability.
10. Both Source 1 and Source 2 can select Open, Close, High and Low, which can be displayed into table.
█ LIMITATIONS
1. Table is limited to intraday timeframe only as time format is not accurate for daily timeframe and above. Example daily timeframe will give result less 1 day from actual date.
2. I did not include other sources such external source or any built in sources such as hl2, hlc3, ohlc4 and hlcc4.
█ CODE EXPLAINATION
I pretty much create custom function with method which returns tuple value.
method crossVariant(float price = na, chart.point ref = na) =>
cross = ta.cross( price, ref.price)
over = ta.crossover( price, ref.price)
under = ta.crossunder(price, ref.price)
Unfortunately, I unable make the labels into array which i plan to return string value by getting the text value from array label, hence i use label.all and add incremental int value as reference.
series label labelCross = na, labelCross.delete()
var int num = 0
if over
num += 1
labelCross := label.new()
if under
num += 1
labelCross := label.new()
if cross
num += 1
labelCross := label.new()
I realised cross value can be overlap with crossover and crossunder, hence I add bool to enable force overlap and add additional bools.
series label labelCross = na, labelCross.delete()
var int num = 0
if forceOverlap
if over
num += 1
labelCross := label.new()
if under
num += 1
labelCross := label.new()
if cross
num += 1
labelCross := label.new()
else
if cross and over
num += 1
labelCross := label.new()
if cross and under
num += 1
labelCross := label.new()
if cross and not over and not under
num += 1
labelCross := label.new()
█ USAGE / EXAMPLES
True Range Moving Average Deviation🔶 Overview
The True Range Moving Average Deviation Indicator (TRMAD) is a technical analysis tool that combines elements of price deviation, volatility, and overbought/oversold conditions.
🔶 Key Components
Current price (Close) : most recent closing price of the asset.
Moving Average (MA) : represents a smoothed trendline of the asset's closing prices over a specified period. By default, TRMAD uses the Simple Moving Average (SMA) with a 20-period setting.
Average True Range (ATR) : reflects the average price range between the high and low over a given time frame. By default, TRMAD uses a 14-period ATR setting with a Simple Moving Average (SMA) calculation. ATR quantifies the historical price volatility of the asset, which is crucial for normalizing the price deviation.
🔶 Calculation
(Close - MA) / ATR
🔶 Interpretation
When TRMAD is above +3 ATR , it is often considered an indication that the asset may be overbought, suggesting a potential reversal or correction to the downside.
When TRMAD is below -3 ATR , it is often considered an indication that the asset may be oversold, suggesting a potential reversal or bounce to the upside.
TRMAD values around 0 ATR may indicate a balanced market condition.
🔶 Usage
🔹 Overbought and Oversold Conditions:
TRMAD can help identify overbought and oversold conditions. When TRMAD reaches or exceeds certain user-defined thresholds (e.g., +3 ATR or -3 ATR), it can signal that the asset is in an extreme condition.
Traders can use these extreme conditions to adjust their positions or look for potential reversal opportunities.
🔹 Divergence Analysis:
Traders often analyze divergences between the TRMAD indicator and price movements. For example, if the price is making higher highs while TRMAD is making lower highs (bearish divergence), it could indicate a potential trend reversal.
🔹 Trend Confirmation:
TRMAD can be used in conjunction with other technical indicators to confirm trends. For example, if TRMAD is consistently positive during an uptrend, it can provide confirmation of the trend's strength.
Positive TRMAD : When TRMAD is positive but hasn't reached the overbought threshold (e.g., +3 ATR), it suggests that there is some bullish momentum, but traders may exercise caution and look for other confirming signals before considering a long position.
Negative TRMAD : When TRMAD is negative but hasn't reached the oversold threshold (e.g., -3 ATR), it suggests some bearish sentiment, but traders may want to seek additional confirmation before considering a short position.
🔹 Risk Management:
Traders can use TRMAD as part of their risk management strategy. For instance, if TRMAD suggests that an asset is overbought, a trader might consider tightening their stop-loss orders to manage potential downside risk.
🔶 Credits
The idea about this indicator came from Fabio Figueiredo (Vlad)
ICT True Day Range [MK]The indicator displays the following:
Vertical line day separator from 00:00 to 00:00 EST
High/Low lines for the days true range from 00:00 to EOD
Opening line from 00:00 EST to EOD
Opening line from 08:30 EST to EOD
Weekly Opening line from Sunday open at 18:00 EST to last bar in the week
Monday range high/low/mid line, which can be extended to EOW
Text displaying Days of the Week
All functions can be fully customized regarding color/style and line width.
Below shows image of indicator with day separator: (it didn't show on the main chart despite being enabled?)
All of the above are to be used to give the user all the tools necessary to analyze the following concepts which can be studied on ICTs you tube channel:
Weekly profile, eg, has the weekly manipulated below the weekly open to then rise the rest of the week?
Daily profile, eg, has the day manipulated below the daily open (00:00 EST) to then rise the rest of the day?
Daily liquidity grab, eg has the current day taken PDH/PDL at the start of the current day?
Daily targets, eg will the current day end up taking liquidity from the PDH/PDL?
Monday range, will Mondays high/low range act as the accumulation phase of the weekly AMD profile?
Tuesday/Wednesday/Thursday/Friday reversal, eg, does a day of the week line up with a HTF target and a high volatility news event which could see price reverse after the manipulation phase of the weekly AMD profile?
In strong trending markets, will the 0830 open line be used in the NY session as manipulation reference in the same manner as the 00:00 line is normally used?
The above examples of how the indicator 'could' be used are not the only ways to use the indicator.
The indicator is by no means a trading strategy on its own. Users should be fully aware of ICT concepts and have performed extensive back-testing before using the indicator with live accounts.
Globex, Extended, Daily, Weekly, Monthly, Yearly Range* Adds Right Side Only Price Line & Labels for Tracking without Extending Both Sides
* Tracks Current, Previous, and Two Previous Globex Sessions/ Futures:
* Tracks Current, Previous, and Two Previous Extended Session/ Stocks:
* Tracks Current, Previous, Two, & Three Previous Day Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Week Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Month Session/ Equities:
* Tracks Current, Last, Two, Three, Four, & Five Year Session/ Equities:
* Allows Custom Range on Globex, Extended, & Daily Sessions
* Allows Custom Range on Weekly, Monthly, & Yearly Sessions
* Lines & Labels Are Not Visible on Chart Scales
* Reversible Text & Background Color
* Lines Extend Accordingly with Range
* Labels show Price & Percent Change
* Background Colors should match Chart Color to avoid Overlapping Text & Labels
* Lines have Offset Extension
* Labels have Offset Extension
* Globex Session is only visible on Futures & if Current Timeframe is Intraday
* Extended Session is only visible on Stocks & if Current Timeframe is Intraday
* Daily, Weekly, Monthly, & Yearly Sessions are visible on All Symbols & All Timeframes
* Globex, Extended, & Regular use their Default Time Sessions but allow Customization
* For Back Testing Default Sessions, switch over on the Menu to Style and Turn On/Off their Background Color; Any Area on the Chart Without Background Color is Regular Session
Volatility Price RangeThe Volatility Price Range is an overlay which estimates a price range for the next seven days and next day, based on historical volatility (already available in TradingView). The upper and lower bands are calculated as follows:
The Volatility for one week is calculated using the formula: WV = HV * √t where:
WV: one-week volatility
HV: annual volatility
√: square root
t: the time factor expressed in years
From this formula we can deduce the weekly volatility WV = HV * √(1 / 52) = HV / 7.2 where 52: weeks in a year.
The daily volatility DV = HV * √(1 / 365) = HV / 19.1 where 365: days in a year.
To calculate the lower and upper value of the bands, the weekly/daily volatility value obtained will be subtracted/added from/to the current price.
CPR (Central Pivot Range)Central Pivot Range is a trend and volatility forecasting tool. It is calculated from previous session's (day, week, or month) high, low, close values. It works on the idea that every trading session must be the result of its previous trading session.
Pivot, top pivot and bottom pivot values form the CPR. If the CPR for each trading session is getting higher (and also the price is trading above it) then it denotes bullish bias and vice versa for bearish. And the width of the CPR (i.e., distance between top and bottom pivot) denotes the volatility of the session.
If the CPR width is narrow, we can expect a trending or volatile trading session. If it's wide, then we can expect a range bound or sideways trading session.
Support and Resistance levels can be used as a profit booking zone or to add/reduce position sizing.
In this Indicator you have the following:
1. CPR with traditional support and resistance levels (S1-S5 & R1-R5).
2. Developing CPR for next trading day, week, and month.
3. Customizable lookback period, line width.
4. Option to show/hide labels, prices, SR levels, developing CPR.
True Range/Expected MoveThis indicator plots the ratio of True Range/Expected Move of SPX. True Range is simple the high-low range of any period. Expected move is the amount that SPX is predicted to increase or decrease from its current price based on the current level of implied volatility. There are several choices of volatility indexes to choose from. The shift in color from red to green is set by default to 1 but can be adjusted in the settings.
Red bars indicate the true range was below the expected move and green bars indicate it was above. Because markets tend to overprice volatility it is expected that there would be more red bars than green. If you sell SPX or SPY option premium red days tend to be successful while green days tend to get stopped out. On a 1D chart it is interesting to look at the clusters of bar colors.
Average Range PercentageIt is indicator for average percent range (range from high to low of stock/index price) of N days,
This will help to find high percentage moving stock/index for intraday.
Focused Average True RangeThe Focused Average True Range (FATR) is a modified version of the classic Average True Range (ATR) indicator. It is designed to provide traders with more accurate data on volatility, minimizing the impact of sharp spikes in volatility.
The main distinction between the Focused ATR and the standard ATR lies in the utilization of percentiles. Instead of calculating the average price change as the regular ATR does, the Focused ATR selects a value in the middle of the range of price changes. This makes it less sensitive to sharp changes in volatility, which can be beneficial in certain trading scenarios.
Settings:
Percentile. This parameter determines which value in the series of price changes will be used. For example, if the percentile is set to 50, the indicator will use the median value of the series of price changes. This is the default value. Imagine a class of students lined up by height, and instead of calculating the average height of all students, we take the height of the students in the middle of the line. Similarly here, we take the ATR from the middle of the series. Increasing the percentile will lead to the use of a value closer to the upper bound of the range, while decreasing the percentile will lead to the use of a value closer to the lower bound.
How to Use:
The Focused ATR is especially useful for determining the sizes of stop-losses and take-profits, thanks to its ability to consider the value in the middle of the series of price changes rather than the average value. This allows traders to more accurately assess volatility and risk, which in turn can assist in optimizing trading strategies
---
Фокусированный Средний Истинный Диапазон (Focused ATR) представляет собой модифицированную версию классического индикатора ATR. Он разработан с целью предоставления трейдерам более точных данных о волатильности, минимизируя влияние резких скачков волатильности.
Основное отличие Фокусированного ATR от стандартного ATR заключается в использовании процентиля. Вместо того, чтобы рассчитывать среднее значение изменений цены, как это делает обычный ATR, Фокусированный ATR выбирает значение в середине диапазона изменений цены. Это делает его менее чувствительным к резким изменениям волатильности, что может быть полезно в некоторых торговых сценариях.
Настройки:
Процентиль. Этот параметр определяет, какое значение в ряду изменений цены будет использоваться. Например, если процентиль равен 50, то индикатор будет использовать медианное значение ряда изменений цены. Это стандартное значение. Представьте себе, что ученики класса выстроились по росту, и мы считаем не средний рост всех учеников, а берем рост учеников из середины колонны. Так и тут. Мы берем ATR из середины ряда. Увеличение процентиля приведет к использованию значения, ближе к верхней границе диапазона, в то время как уменьшение процентиля приведет к использованию значения, ближе к нижней границе.
Как использовать:
Фокусированный ATR особенно полезен для определения размеров стоп-лоссов и тейк-профитов, благодаря своей способности учитывать значение в середине ряда изменений цены, а не среднее значение. Это позволяет трейдерам более точно оценить волатильность и риск, что в свою очередь может помочь в оптимизации торговых стратегий.
.
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
COT-index rangeA graph showing the commercials (part of COT-data) positioning in relation to its own range, X periods back. I usually choose the look-back period to equal approximately one year. This will be around 52 on a weekly chart and 250 on a daily chart.
In my opinion a high data-point for the commercials is bullish and vice versa. But instead of only looking att absolute values I now look more at how the commercials are positioned compared to the previous 12 och 6 months.
Example:
a) if COT-index range = 0.8, then the commercials are in the 80th percentile for this specific look-back period, i.e. the commercials has only been more bullish 20% of the time and more bearish 80% of the time.
b) a) if COT-index range = 0.5, then the commercials are in the 50th percentile for this specific look-back period, i.e. the commercials has been more bullish 50% of the time and more bearish 50% of the time.
c) if COT-index range = 0.2, then the commercials are in the 20th percentile for this specific look-back period, i.e. the commercials has been more bullish 80% of the time and more bearish 20% of the time.
In other words, a high reading is bullish and a low reading is bearish.
Opening Range with FibsThe indicator uses a time range and another instrument for time reference, so that it works in the time zone you care about. I have set the default to SPX500USD since it is in EST ( SPX , ES and many futures are on Chicago time and opening range gets confused). You can change the reference instrument in the settings.
You can also change the multipliers and use other values instead of 1.272 and 1.618 for Fib extensions.
TradingView has a limit as to how many objects an indicator can create so if you want to go back further for visual backtesting - use the replay tool - it will be able to draw up to the time you selected within its limits.
Let me know if you need anything else...
Happy Trading!
True Range Adjusted Exponential Momentum [CC]-[burgered]Original Script by CheatCountry, used with permission (chill guy):
I have made a sort of conversion of CheatCountries implementation of the True Range Adjusted Exponential Moving Average into a momentum oscillator.
Being True Range based, it the bounds vary based on the chart.
Includes a Bollinger Band for bounds that forms a trend follower based on the 0 point.
Includes CheatCountry color code signals, different color scheme. Bright colors are strong signals, ark are weak, green bull, red bear, the basics.
This oscillator can be used for divergences, trends, signal strength, confirmation, volatility readings, you name it.
Works well on smoothed/filtered signals as well.
Give CheatCountry a follow, hes one of the MVPs of Tradingview Pinescripters, constantly giving us access to novel new concepts as they are published by professionals.
[blackcat] L1 True Range Adjusted EMA (TRAdj EMA) Level: 1
Background
In Traders’ Tips in January 2023, Vitali Apirine published an article in the January 2023 issue, “True Range Adjusted Exponential Moving Average (TRAdj EMA)”.
I use pine v4 to script it.
Function
Vitali Apirine's article True Range Adjusted Exponential Moving Average (TRAdj EMA) presents how a security's True Range, which measures volatility, can be integrated into a traditional exponential moving average. The trend following indicator called True Range Adjusted Exponential Moving Average (TRAdj EMA) applied with different lengths can help define turning points and filter price movements. By comparing the indicator to an exponential moving average of the same length, the trader can gain insight into the overall trend.
Remarks
Feedbacks are appreciated.
Average True Range Refurbished💡 Objective
This script is a rebuild of the pre-existing ATR indicator, with improvements and fine-tuning.
🪄Improvements
1. Normalization option (range 0 to 100)
2. Optional calculation of the ratio between current volatility and average volatility
3. Optional smoothing
4. Show a moving average
5. Show Bollinger Bands with 3 bands
6. Change bar colors according to ATR and Bollinger Bands
📚 Definition
'The Average True Range (ATR) is a tool used in technical analysis to measure volatility. Unlike many of today's popular indicators, the ATR is not used to indicate the direction of price. Rather, it is a metric used solely to measure volatility, especially volatility caused by price gaps or limit moves.'
(TradingView)
True Range Outlier Detector (TROD)True Range Outlier Detector (TROD) shows you weather or not a candle is larger than normal. This works by taking the normalized true range and if the candle exceeds a score of 0.5 or -0.5 it triggers the outlier detection. This is great for building strategies if you want to refrain from buying larger than normal up or down ticks. The only feature is the ability to change the lookback period of the normalization. I hope you find this as useful as I do!
Enjoy!
