Balance Zone ExtensionBalance zones are an aspect of trading that many traders notice. Balance Zones are formed when a market is in equilibrium and respects a certain high and low multiple times. These zones could also be called accumulation or distribution areas depending on the price action. If the term "choppy" is used to describe a given markets price action, it is probably a fair statement to say that the market is currently in a Balance Zone.
This script is a take on vwaptrader1's teachings where you take a balance zone and "double it" to get a target if/when it does break out of balance. It provides an automated way of extending levels based on a given balance range.
The lines plotted by the script are calculated based off of the balance high/low inputs, how many sections are desired per zone, and how many boxes to plot based on the other user inputs.
Warning: Due to a current limitation of the Pine, this script is only allowed to plot up to 500 lines total. If you start to notice lines starting to disappear or you begin getting a script error, double check the input settings as the script may have crossed the 500 line threshold.
This can be used in conjunction with Fixed Range Volume Profile . Select the balance range with the Fixed Volume Profile . Note the Value Area High and Value Area Low prices and input those into the balance range High/Low inputs.
Use to create price targets from Balance Zone Breakouts
A recent example of this idea in action on ticker ES1! 2 hour chart where the balance range was found and the target (double the box size of the balance range) was hit.
Another example of this same concept but on a normal security like AAPL but on a 30 minute chart:
Extending the usefulness even further to crypto on BTCUSD with a 5 minute chart:
Use to create reference levels for future price action
The other way to utilize this is to provide future reference levels from a key balance range from the past.
Here is another example utilizing the AMD daily chart . First, a balance zone was noted for all of 2017:
Moving forward to the most recent price action in 2023, notice that the box extension levels are still fairly well respected almost 6 years later!
Cerca negli script per "vwap"
Range Analysis - By LeviathanThe Interactive Range Analysis script is an essential tool for analyzing price ranges. It automatically draws important range levels, generates a Volume Profile or Open Interest profile and horizontal/vertical heatmaps, plots the anchored VWAP, draws Fibonacci levels, and much more.
How to use the indicator:
1. The script will prompt you to select the "Start Time" and "End Time" using Tradingview's interactive interface. These two points will determine the length of the range.
2. Once you have selected the range, the script will automatically anchor the range highs and lows to the highest and lowest close/wick/hlc3/ohlc4 (whichever you prefer).
3. You can then begin exploring different tools and options such as Quarters, Eighths, Fibonacci, Outer Levels, VWAP, Horizontal Volume/OI Heatmap, Vertical Volume/OI Heatmap, Fixed Range Volume Profile, Open Interest Profile, Value Area, VAH, VAL, and POC.
4. You can adjust the range by dragging the Start Time and End Time anchors or by removing/reapplying the script.
Tool overview
Range Levels
After selecting your preferred time range, the script will identify and draw a range high level and a range low level, which serve as a base for other important levels. “Half” is the level halfway between the range high and range low. “Quarters” will, as the name suggests, split the range into four equal zones (quarters) and “Eighths” will split the range into eight equal zones (eighths).
”Fibonacci” option allows you to display Fibonacci retracement levels (0.786, 0.618, 0.382, 0.236). “VWAP” will plot a Volume Weighted Average Price, anchored to the start of the range. “Direction” input lets you choose whether your range is UP or DOWN trending in order to make sure that the Fibonacci levels and labels are generated and assigned correctly. With “Outer” turned ON, the script will also generate active levels (quarters/eighths/Fibonacci) above and below the selected price range. “Extend Right” will extend all levels to the right indefinitely, while “Extend (+Bars)” lets you choose how far right the levels get extended. “Diagonal Line” is drawn from the bottom left of the range to the top right of the range or from the top left of the range to the bottom right of the range, depending on the “Direction” input.
Volume Profile / Open Interest Profile
After selecting the “Data Type”, Volume Profile or OI Profile can be generated by turning ON the “Volume/OI Profile” option.
“Resolution” input defines the amount of nodes/rows in the range that are used in profile/heatmap generation for distributing the data. While you can increase the “Resolution” to get better, more granular profiles, you should keep in mind that you might need to lower the resolution when generating profiles for larger ranges.
”Node Type” offers you two options when it comes to the representation of data: Up/Down - divides a node in two sections for up volume/OI and down volume/OI, Total - one node for total volume/OI and Delta - net difference in up volume/OI and down volume/OI.
”Profile Position” lets you choose whether the profile is positioned on the left side of the range or on the right side of the range.
“Profile Direction” determines whether the profile nodes are facing right or left.
“Profile Type” enables you to visualize the nodes in a classic way (Type 1) or in a way where down volume/negative OI are positioned on the left side of the y axis and up volume/positive OI on the right side of the y axis.
“Node Size (%)” defines how much space in the range can be taken by the profile’s nodes. Eg. 50% will allow the largest node to extend to the middle of the range (and others scaled accordingly), 100% will allow the largest node to extend the max right point of the range (and others scaled accordingly).
”Value Area (%)” defines the VA zone, which represents the area where the most volume occured (usually 70% or 68%).
”Horizontal Heatmap” will display a heatmap-like overlay, that will help you identify the price levels where most volume/open interest action occurred.
”Vertical Heatmap” will display a heatmap-like overlay, that will help you identify the points in time where most volume/open interest action occurred.
A more detailed description of this indicator is coming in the next few days.
Important:
* If volume or OI profile does not get generated, try lowering the resolution.
* Once in a while, the script will disappear from your chart. Just remove and reapply.
* Open Interest data is only avaiable on Binance Perpetual Futures pairs
To learn more, read the tooltips in the indicator’s settings and stay tuned for upcoming additions (Range Market Structure, Liquidation Levels, Range Statistics,…)
Big Poppa Code Strat & Momentum Strategy IndicatorThis indicator is a combination of a few things in order to work with a unique trading style gleaned from Callme100k, jrgreatness, TrustMyLevels , FaithInTheStrat, Rob Smith and Saty Mahajan.
This Indicator is created to help you day trade using, ATR Fibonacci Levels, Price Action and Momentum.
It displays Fibonacci Levels Based on ATR to indicate when a security is 0.236, 0.382 +- the Days Open, +- the Days Open, 0.618 +- the Days Open and 1.0 +- Days Open.
To understand this script you need to understand
Average True Range (ATR)
1 Bar Inside Bar
2 Bar Outside Bar (Break either the top or bottom)
3 Bar Engulfing Bar
Strat Setups - 212, 322, 312
Fibonacci - 0.236, 0.382, 0.618, 1.0
Moving Averages
A Trend is considered bullish when (green)
Current Price is greater than the Fast EMA Value (8)
Fast EMA is greater than PIVOT EMA Value (21)
Pivot EMA is greater than SLOW EMA Value (34)
OR Hull is trending up and the Price is above the Volume Weighted Moving Average and price is above VWAP
A trend is considered Bearish when (red)
Current Price is less than the Fast EMA Value (8)
Fast EMA is less than PIVOT EMA Value (21)
Pivot EMA is less than SLOW EMA Value (34)
OR Hull is trending down and the Price is below the Volume Weighted Moving Average and price is below VWAP
If these conditions are not met then the Momentum is in Conflict (orange)
The Momentum band will match the color of the current trend
The table that is present can be turned off at any time lets you see
1) If Moving Averages are showing bullish, bearish or in conflict
2) If There us Time Frame Continuity, (if 5 min up, are all the other timeframes up also)
3) How much of the ATR have we moved on the day
4) Are we in Call or Put range for the day based on ATR Fib Levels
The Ideal situation for entering a call
1) Momentum is Green
2) FTFC on Green
3) A Strat Actionable Signal is present
4) You are in the call range, 0.236 - 0.618 ATR + the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Ideal situation from entering a put
1) Momentum is red
2) FTFC on Red
3) A Strat Actionable Signal is present
4) You are in the put range, 0.236 - 0.618 ATR - the Price
5) The ATR still has room, I.e only 50% of the ATR has been run already
Exit the trade for these reasons you entered (for profit or loss)
1) ATR has no more room
2) FTFC is now in conflict
3) Momentum has shifted
Take Profit when
1) You reach a new ATR Level 0.618, 1.0 , -0.618, -1, etc
Passive Stop Loss
1) Open Price if you are aggressive
2) Next ATR Level Down or Up
Feel free to take profit and leave runners
This script does not give signals, you should do your own research, I am not a financial advisors, I am simply applying principles of seasoned veterans to code. You make all decisions about how you buy, sell and trade. The creator of this script makes no promises and takes no responsibility for your personal trading.
To research the methods described above look up
Rob Smith : The Strat
Saty Mahajan : ATR Levels
Fibonacci
Using the HULL Moving Average
Exponential Moving Averages
VWAP
VWMA
TurntLibraryLibrary "TurntLibrary"
Collection of functions created for simplification/easy referencing. Includes variations of moving averages, length value oscillators, and a few other simple functions based upon HH/LL values.
ma(source, length, type)
Apply a moving average to a float value
Parameters:
source : Value to be used
length : Number of bars to include in calculation
type : Moving average type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Smoothed value of initial float value
curve(src, len, lb1, lb2)
Exaggerates curves of a float value designed for use as an exit signal.
Parameters:
src : Initial value to curve
len : Number of bars to include in calculation
lb1 : (Default = 1) First lookback length
lb2 : (Default = 2) Second lookback length
Returns: Curved Average
fragma(src, len, space, str)
Average of a moving average and the previous value of the moving average
Parameters:
src : Initial float value to use
len : Number of bars to include in calculation
space : Lookback integer for second half of average
str : Moving average type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Fragmented Average
maxmin(x, y)
Difference of 2 float values, subtracting the lowest from the highest
Parameters:
x : Value 1
y : Value 2
Returns: The +Difference between 2 float values
oscLen(val, type)
Variable Length using a oscillator value and a corresponding slope shape ("Incline",Decline","Peak","Trough")
Parameters:
val : Oscillator Value to use
type : Slope of length curve ("Incline",Decline","Peak","Trough")
Returns: Variable Length Integer
hlAverage(val, smooth, max, min, type, include)
Average of HH,LL with variable lengths based on the slope shape ("Incline","Decline","Trough") value relative to highest and lowest
Parameters:
val : Source Value to use
smooth
max
min
type
include : Add "val" to the averaging process, instead of more weight to highest or lowest value
Returns: Variable Length Average of Highest Lowest "val"
pct(val)
Convert a positive float / price to a percentage of it's highest value on record
Parameters:
val : Value To convert to a percentage of it's highest value ever
Returns: Percentage
hlrange(x, len)
Difference between Highest High and Lowest Low of float value
Parameters:
x : Value to use in calculation
len : Number of bars to include in calculation
Returns: Difference
midpoint(x, len, smooth)
The average value of the float's Highest High and Lowest Low in a number of bars
Parameters:
x : Value to use in calculation
len
smooth : (Default=na) Optional smoothing type to use ("SMA","EMA","RMA","WMA","VWAP","SWMA","LRC")
Returns: Midpoint
Musashi_Katana=== Musashi-Katana ===
This tool was designed to fit my particular trading style and personal theories about the "Alchemy of the markets" and ''Harmonic Structure'.
Context
When following a Technical approach to to surf the markets, there are teachings that must be understood before reaching a confort-zone, this usually happen the possible worst way by constant experimentation, it hurts.
Here few technical hints:
- Align High timeframes with lower timeframes:
This simple concept relax a lot complexity of finding of a trend bias. Musashi-Katana allows you to use technical indicator corresponding to specific timeframes, like daily weekly or yearly. They wont change when you change the chart's timeframe, its very useful as you know where you're standing in the long term, Its quite relaxing.
- Use volume:
The constant usage of volume will allow you to sync with the market's breathing. This shows you the mass of money flowing into and out of the market, is key if you want to understand momentum. This tool can help here, as it have multi-period vwaps. You can use yearly, monthly for swing trading, and even weekly if you enjoy scalping.
Useful stuff:
- You have access to baselines, AMA and Kijun-sen with the possibility of adding ATR bands.
- AMAs come as two lines strategies for different approaches, fast medium or slow.
- You can experiment with normal and multi timeframe moving averages and other trend tools.
Final Note
If used correctly Musashi-Katana is a very powerful tool, which makes no sense as there is no correct usage. Don't add everything at the same time, experiment, combine stuff, every market is different.
Backtest every possible strategy before using it, see what works and doesn't. This gives you a lot of peace, specially while you're at the tip of the spear surfing the markets
--> I personally use this in combination with 'Musashi_Slasher (Mometum+Volatility)', as it gives me volatility and momentum in a very precise way.
Physics CandlesPhysics Candles embed volume and motion physics directly onto price candles or market internals according to the cyclic pattern of financial securities. The indicator works on both real-time “ticks” and historical data using statistical modeling to highlight when these values, like volume or momentum, is unusual or relatively high for some periodic window in time. Each candle is made out of one or more sub-candles that each contain their own information of motion, which converts to the color and transparency, or brightness, of that particular candle segment. The segments extend throughout the entire candle, both body and wicks, and Thick Wicks can be implemented to see the color coding better. This candle segmentation allows you to see if all the volume or energy is evenly distributed throughout the candle or highly contained in one small portion of it, and how intense these values are compared to similar time periods without going to lower time frames. Candle segmentation can also change a trader’s perspective on how valuable the information is. A “low” volume candle, for instance, could signify high value short-term stopping volume if the volume is all concentrated in one segment.
The Candles are flexible. The physics information embedded on the candles need not be from the same price security or market internal as the chart when using the Physics Source option, and multiple Candles can be overlayed together. You could embed stock price Candles with market volume, market price Candles with stock momentum, market structure with internal acceleration, stock price with stock force, etc. My particular use case is scalping the SPX futures market (ES), whose price action is also dictated by the volume action in the associated cash market, or SPY, as well as a host of other securities. Physics allows you to embed the ES volume on the SPY price action, or the SPY volume on the ES price action, or you can combine them both by overlaying two Candle streams and increasing the Number of Overlays option to two. That option decreases the transparency levels of your coloring scheme so that overlaying multiple Candles converges toward the same visual color intensity as if you had one. The Candle and Physics Sources allows for both Symbols and Spreads to visualize Candle physics from a single ticker or some mathematical transformation of tickers.
Due to certain TradingView programming restrictions, each Candle can only be made out of a maximum of 8 candle segments, or an “8-bit” resolution. Since limits are just an opportunity to go beyond, the user has the option to stack multiple Candle indicators together to further increase the candle resolution. If you don’t want to see the Candles for some particular period of the day, you can hide them, or use the hiding feature to have multiple Candles calibrated to show multiple parts of the trading day. Securities tend to have low volume after hours with sharp spikes at the open or close. Multiple Candles can be used for multiple parts of the trading day to accommodate these different cycles in volume.
The Candles do not need be associated with the nominal security listed on the TV chart. The Candle Source allows the user to look at AAPL Candles, for instance, while on a TSLA or SPY chart, each with their respective volume actions integrated into the candles, for instance, to allow the user to see multiple security price and volume correlation on a single chart.
The physics information currently embeddable on Candles are volume or time, velocity, momentum, acceleration, force, and kinetic energy. In order to apply equations of motion containing a mass variable to financial securities, some analogous value for mass must be assumed. Traders often regard volume or time as inextricable variables to a securities price that can indicate the direction and strength of a move. Since mass is the inextricable variable to calculating the momentum, force, or kinetic energy of motion, the user has the option to assume either time or volume is analogous to mass. Volume may be a better option for mass as it is not strictly dependent on the speed of a security, whereas time is.
Data transformations and outlier statistics are used to color code the intensity of the physics for each candle segment relative to past periodic behavior. A million shares during pre-market or a million shares during noontime may be more intense signals than a typical million shares traded at the open, and should have more intense color signals. To account for a specific cyclic behavior in the market, the user can specify the Window and Cycle Time Frames. The Window Time Frame splits up a Cycle into windows, samples and aggregates the statistics for each window, then compares the current physics values against past values in the same window. Intraday traders may benefit from using a Daily Cycle with a 30-minute Window Time Frame and 1-minute Sample Time Frame. These settings sample and compare the physics of 1-minute candles within the current 30-minute window to the same 30-minute window statistics for all past trading days, up until the data limit imposed by TradingView, or until the Data Collection Start Date specified in the settings. Longer-term traders may benefit from using a Monthly Cycle with a Weekly Time Frame, or a Yearly Cycle with a Quarterly Time Frame.
Multiple statistics and data transformation methods are available to convey relative intensity in different ways for different trading signals. Physics Candles allows for both Normal and Log-Normal assumptions in the physics distribution. The data can then be transformed by Linear, Logarithmic, Z-Score, or Power-Law scoring, where scoring simply assigns an intensity to the relative physics value of each candle segment based on some mathematical transformation. Z-scoring often renders adequate detection by scoring the segment value, such as volume or momentum, according to the mean and standard deviation of the data set in each window of the cycle. Logarithmic or power-law transformation with a gamma below 1 decreases the disparity between intensities so more less-important signals will show up, whereas the power-law transformation with gamma values above 1 increases the disparity between intensities, so less more-important signals will show up. These scores are then converted to color and transparency between the Min Score and the Max Score Cutoffs. The Auto-Normalization feature can automatically pick these cutoffs specific to each window based on the mean and standard deviation of the data set, or the user can manually set them. Physics was developed with novices in mind so that most users could calibrate their own settings by plotting the candle segment distributions directly on the chart and fiddling with the settings to see how different cutoffs capture different portions of the distribution and affect the relative color intensities differently. Security distributions are often skewed with fat-tails, known as kurtosis, where high-volume segments for example, have a higher-probabilities than expected for a normal distribution. These distribution are really log-normal, so that taking the logarithm leads to a standard bell-shaped distribution. Taking the Z-score of the Log-Normal distribution could make the most statistical sense, but color sensitivity is a discretionary preference.
Background Philosophy
This indicator was developed to study and trade the physics of motion in financial securities from a visually intuitive perspective. Newton’s laws of motion are loosely applied to financial motion:
“A body remains at rest, or in motion at a constant speed in a straight line, unless acted upon by a force”.
Financial securities remain at rest, or in motion at constant speed up or down, unless acted upon by the force of traders exchanging securities.
“When a body is acted upon by a force, the time rate of change of its momentum equals the force”.
Momentum is the product of mass and velocity, and force is the product of mass and acceleration. Traders render force on the security through the mass of their trading activity and the acceleration of price movement.
“If two bodies exert forces on each other, these forces have the same magnitude but opposite directions.”
Force arises from the interaction of traders, buyers and sellers. One body of motion, traders’ capitalization, exerts an equal and opposite force on another body of motion, the financial security. A securities movement arises at the expense of a buyer or seller’s capitalization.
Volume
The premise of this indicator assumes that volume, v, is an analogous means of measuring physical mass, m. This premise allows the application of the equations of motion to the movement of financial securities. We know from E=mc^2 that mass has energy. Energy can be used to create motion as kinetic energy. Taking a simple hypothetical example, the interaction of one short seller looking to cover lower and one buyer looking to sell higher exchange shares in a security at an agreed upon price to create volume or mass, and therefore, potential energy. Eventually the short seller will actively cover and buy the security from the previous buyer, moving the security higher, or the buyer will actively sell to the short seller, moving the security lower. The potential energy inherent in the initial consolidation or trading activity between buy and seller is now converted to kinetic energy on the subsequent trading activity that moves the securities price. The more potential energy that is created in the consolidation, the more kinetic energy there is to move price. This is why point and figure traders are said to give price targets based on the level of volatility or size of a consolidation range, or why Gann traders square price and time, as time is roughly proportional to mass and trading activity. The build-up of potential energy between short sellers and buyers in GME or TSLA led to their explosive moves beyond their standard fundamental valuations.
Position
Position, p, is simply the price or value of a financial security or market internal.
Time
Time, t, is another means of measuring mass to discover price behavior beyond the time snapshots that simple candle charts provide. We know from E=mc^2 that time is related to rest mass and energy given the speed of light, c, where time ≈ distance * sqrt(mass/E). This relation can also be derived from F=ma. The more mass there is, the longer it takes to compute the physics of a system. The more energy there is, the shorter it takes to compute the physics of a system. Similarly, more time is required to build a “resting” low-volatility trading consolidation with more mass. More energy added to that trading consolidation by competing buyers and sellers decreases the time it takes to build that same mass. Time is also related to price through velocity.
Velocity = (p(t1) – p(t0)) / p(t0)
Velocity, v, is the relative percent change of a securities price, p, over a period of time, t0 to t1. The period of time is between subsequent candles, and since time is constant between candles within the same timeframe, it is not used to calculate velocity or acceleration. Price moves faster with higher velocity, and slower with slower velocity, over the same fixed period of time. The product of velocity and mass gives momentum.
Momentum = mv
This indicator uses physics definition of momentum, not finance’s. In finance, momentum is defined as the amount of change in a securities price, either relative or absolute. This is definition is unfortunate, pun intended, since a one dollar move in a security from a thousand shares traded between a few traders has the exact same “momentum” as a one dollar move from millions of shares traded between hundreds of traders with everything else equal. If momentum is related to the energy of the move, momentum should consider both the level of activity in a price move, and the amount of that price move. If we equate mass to volume to account for the level of trading activity and use physics definition of momentum as the product of mass and velocity, this revised definition now gives a thousand-times more momentum to a one-dollar price move that has a thousand-times more volume behind it. If you want to use finance’s volume-less definition of momentum, use velocity in this indicator.
Acceleration = v(t1) – v(t0)
Acceleration, a, is the difference between velocities over some period of time, t0 to t1. Positive acceleration is necessary to increase a securities speed in the positive direction, while negative acceleration is necessary to decrease it. Acceleration is related to force by mass.
Force = ma
Force is required to change the speed of a securities valuation. Price movements with considerable force have considerably more impact on future direction. A change in direction requires force.
Kinetic Energy = 0.5mv^2
Kinetic energy is the energy that a financial security gains from the change in its velocity by force. The built-up of potential energy in trading consolidations can be converted to kinetic energy on a breakout from the consolidation.
Cycle Theory and Relativity
Just as the physics of motion is relative to a point of reference, so too should the physics of financial securities be relative to a point of reference. An object moving at a 100 mph towards another object moving in the same direction at 100 mph will not appear to be moving relative to each other, nor will they collide, but from an outsider observer, the objects are going 100 mph and will collide with significant impact if they run into a stationary object relative to the observer. Similarly, trading with a hundred thousand shares at the open when the average volume is a couple million may have a much smaller impact on the price compared to trading a hundred thousand shares pre-market when the average volume is ten thousand shares. The point of reference used in this indicator is the average statistics collected for a given Window Time Frame for every Cycle Time Frame. The physics values are normalized relative to these statistics.
Examples
The main chart of this publication shows the Force Candles for the SPY. An intense force candle is observed pre-market that implicates the directional overtone of the day. The assumption that direction should follow force arises from physical observation. If a large object is accelerating intensely in a particular direction, it may be fair to assume that the object continues its direction for the time being unless acted upon by another force.
The second example shows a similar Force Candle for the SPY that counters the assumption made in the first example and emphasizes the importance of both motion and context. While it’s fair to assume that a heavy highly accelerating object should continue its course, if that object runs into an obstacle, say a brick wall, it’s course may deviate. This example shows SPY running into the 50% retracement wall from the low of Mar 2020, a significant support level noted in literature. The example also conveys Gann’s idea of “lost motion”, where the SPY penetrated the 50% price but did not break through it. A brick wall is not one atom thick and price support is not one tick thick. An object can penetrate only one layer of a wall and not go through it.
The third example shows how Volume Candles can be used to identify scalping opportunities on the SPY and conveys why price behavior is as important as motion and context. It doesn’t take a brick wall to impede direction if you know that the person driving the car tends to forget to feed the cats before they leave. In the chart below, the SPY breaks down to a confluence of the 5-day SMA, 20-day SMA, and an important daily trendline (not shown) after the bullish bounce from the 50% retracement days earlier. High volume candles on the SMA signify stopping volume that reverse price direction. The character of the day changes. Bulls become more aggressive than bears with higher volume on upswings and resistance, whiles bears take on a defensive position with lower volume on downswings and support. High volume stopping candles are seen after rallies, and can tell you when to take profit, get out of a position, or go short. The character change can indicate that its relatively safe to re-enter bullish positions on many major supports, especially given the overarching bullish theme from the large reaction off the 50% retracement level.
The last example emphasizes the importance of relativity. The Volume Candles in the chart below are brightest pre-market even though the open has much higher volume since the pre-market activity is much higher compared to past pre-markets than the open is compared to past opens. Pre-market behavior is a good indicator for the character of the day. These bullish Volume Candles are some of the brightest seen since the bounce off the 50% retracement and indicates that bulls are making a relatively greater attempt to bring the SPY higher at the start of the day.
Infrequently Asked Questions
Where do I start?
The default settings are what I use to scalp the SPY throughout most of the extended trading day, on a one-minute chart using SPY volume. I also overlay another Candle set containing ES future volume on the SPY price structure by setting the Physics Source to ES1! and the Number of Overlays setting to 2 for each Candle stream in order to account for pre- and post-market trading activity better. Since the closing volume is exponential-like up until the end of the regular trading day, adding additional Candle streams with a tighter Window Time Frame (e.g., 2-5 minute) in the last 15 minutes of trading can be beneficial. The Hide feature can allow you to set certain intraday timeframes to hide one Candle set in order to show another Candle set during that time.
How crazy can you get with this indicator?
I hope you can answer this question better. One interesting use case is embedding the velocity of market volume onto an internal market structure. The PCTABOVEVWAP.US is a market statistic that indicates the percent of securities above their VWAP among US stocks and is helpful for determining short term trends in the US market. When securities are rising above their VWAP, the average long is up on the day and a rising PCTABOVEVWAP.US can be viewed as more bullish. When securities are falling below their VWAP, the average short is up on the day and a falling PCTABOVEVWAP.US can be viewed as more bearish. (UPVOL.US - DNVOL.US) / TVOL.US is a “spread” symbol, in TV parlance, that indicates the decimal percent difference between advancing volume and declining volume in the US market, showing the relative flow of volume between stocks that are up on the day, and stocks that are down on the day. Setting PCTABOVEVWAP.US in the Candle Source, (UPVOL.US - DNVOL.US) / TVOL.US in the Physics Source, and selecting the Physics to Velocity will embed the relative velocity of the spread symbol onto the PCTABOVEVWAP.US candles. This can be helpful in seeing short term trends in the US market that have an increasing amount of volume behind them compared to other trends. The chart below shows Volume Candles (top) and these Spread Candles (bottom). The first top at 9:30 and second top at 10:30, the high of the day, break down when the spread candles light up, showing a high velocity volume transfer from up stocks to down stocks.
How do I plot the indicator distribution and why should I even care?
The distribution is visually helpful in seeing how different normalization settings effect the distribution of candle segments. It is also helpful in seeing what physics intensities you want to ignore or show by segmenting part of the distribution within the Min and Max Cutoff values. The intensity of color is proportional to the physics value between the Min and Max Cutoff values, which correspond to the Min and Max Colors in your color scheme. Any physics value outside these Min and Max Cutoffs will be the same as the Min and Max Colors.
Select the Print Windows feature to show the window numbers according to the Cycle Time Frame and Window Time Frame settings. The window numbers are labeled at the start of each window and are candle width in size, so you may need to zoom into to see them. Selecting the Plot Window feature and input the window number of interest to shows the distribution of physics values for that particular window along with some statistics.
A log-normal volume distribution of segmented z-scores is shown below for 30-minute opening of the SPY. The Min and Max Cutoff at the top of the graph contain the part of the distribution whose intensities will be linearly color-coded between the Min and Max Colors of the color scheme. The part of the distribution below the Min Cutoff will be treated as lowest quality signals and set to the Min Color, while the few segments above the Max Cutoff will be treated as the highest quality signals and set to the Max Color.
What do I do if I don’t see anything?
Troubleshooting issues with this indicator can involve checking for error messages shown near the indicator name on the chart or using the Data Validation section to evaluate the statistics and normalization cutoffs. For example, if the Plot Window number is set to a window number that doesn’t exist, an error message will tell you and you won’t see any candles. You can use the Print Windows option to show windows that do exist for you current settings. The auto-normalization cutoff values may be inappropriate for your particular use case and literally cut the candles out of the chart. Try changing the chart time frame to see if they are appropriate for your cycle, sample and window time frames. If you get a “Timeframe passed to the request.security_lower_tf() function must be lower than the timeframe of the main chart” error, this means that the chart timeframe should be increased above the sample time frame. If you get a “Symbol resolve error”, ensure that you have correct symbol or spread in the Candle or Physics Source.
How do I see a relative physics values without cycles?
Set the Window Time Frame to be equal to the Cycle Time Frame. This will aggregate all the statistics into one bucket and show the physics values, such as volume, relative to all the past volumes that TV will allow.
How do I see candles without segmentation?
Segmentation can be very helpful in one context or annoying in another. Segmentation can be removed by setting the candle resolution value to 1.
Notes
I have yet to find a trading platform that consistently provides accurate real-time volume and pricing information, lacking adequate end-user data validation or quality control. I can provide plenty of examples of real-time volume counts or prices provided by TradingView and other platforms that were significantly off from what they should have been when comparing against the exchanges own data, and later retroactively corrected or not corrected at all. Since no indicator can work accurately with inaccurate data, please use at your own discretion.
The first version is a beta version. Debugging and validating code in Pine script is difficult without proper unit testing. Please report any bugs with enough information to reproduce them and indicate why they are important. I also encourage you to export the data from TradingView and verify the calculations for your particular use case.
The indicator works on real-time updates that occur at a higher frequency than the candle time frame, which TV incorrectly refers to as ticks. They use this terminology inaccurately as updates are really aggregated tick data that can take place at different prices and may not accurately reflect the real tick price action. Consequently, this inaccuracy also impacts the real-time segmentation accuracy to some degree. TV does not provide a means of retaining “tick” information, so the higher granularity of information seen real-time will be lost on a disconnect.
TV does not provide time and sales information. The volume and price information collected using the Sample Time Frame is intraday, which provides only part of the picture. Intraday volume is generally 50 to 80% of the end of day volume. Consequently, the daily+ OHLC prices are intraday, and may differ significantly from exchanged settled OHLC prices.
The Cycle and Window Time Frames refer to calendar days and time, not trading days or time. For example, the first window week of a monthly cycle is the first seven days of the month, not the first Monday through Friday of trading for the month.
Chart Time Frames that are higher than the Window Time Frames average the normalized physics for price action that occurred within a given Candle segment. It does not average price action that did not occur.
One of the main performance bottleneck in TradingView’s Pine Script is client-side drawing and plotting. The performance of this indicator can be increased by lowering the resolution (the number of sub-candles this indicator plots), getting a faster computer, or increasing the performance of your computer like plugging your laptop in and eliminating unnecessary processes.
The statistical integrity of this indicator relies on the number of samples collected per sample window in a given cycle. Higher sample counts can be obtained by increasing the chart time frame or upgrading the TradingView plan for a higher bar count. While increasing the chart time frame doesn’t increase the visual number of bars plotted on the chart, it does increase the number of bars that can be pulled at a lower time frame, up to 100,000.
Due to a limitation in Pine Scripts request_lower_tf() function, using a spread symbol will only work for regular trading hours, not extended trading hours.
Ideally, velocity or momentum should be calculated between candle closes. To eliminate the need to deal with price gaps that would lead to an incorrect statistical distributions, momentum is calculated between candle open and closes as a percent change of the price or value, which should not be an issue for most liquid securities.
Moving Average Compendium RefurbishedThis is my effort to bring together in a single script the widest range of moving averages possible.
I aggregated the calculation of averages within a library.
For more information about the library follow the link:
Basically this indicator is the visual result of this library.
You can choose the moving average and the script updates the chart as per the type.
The unique parameters of certain moving averages remain at their default values.
To have a rainbow of moving averages I also made an indicator:
Available moving averages:
AARMA = 'Adaptive Autonomous Recursive Moving Average'
ADEMA = '* Alpha-Decreasing Exponential Moving Average'
AHMA = 'Ahrens Moving Average'
ALMA = 'Arnaud Legoux Moving Average'
ALSMA = 'Adaptive Least Squares'
AUTOL = 'Auto-Line'
CMA = 'Corrective Moving average'
CORMA = 'Correlation Moving Average Price'
COVWEMA = 'Coefficient of Variation Weighted Exponential Moving Average'
COVWMA = 'Coefficient of Variation Weighted Moving Average'
DEMA = 'Double Exponential Moving Average'
DONCHIAN = 'Donchian Middle Channel'
EDMA = 'Exponentially Deviating Moving Average'
EDSMA = 'Ehlers Dynamic Smoothed Moving Average'
EFRAMA = '* Ehlrs Modified Fractal Adaptive Moving Average'
EHMA = 'Exponential Hull Moving Average'
EMA = 'Exponential Moving Average'
EPMA = 'End Point Moving Average'
ETMA = 'Exponential Triangular Moving Average'
EVWMA = 'Elastic Volume Weighted Moving Average'
FAMA = 'Following Adaptive Moving Average'
FIBOWMA = 'Fibonacci Weighted Moving Average'
FISHLSMA = 'Fisher Least Squares Moving Average'
FRAMA = 'Fractal Adaptive Moving Average'
GMA = 'Geometric Moving Average'
HKAMA = 'Hilbert based Kaufman\'s Adaptive Moving Average'
HMA = 'Hull Moving Average'
JURIK = 'Jurik Moving Average'
KAMA = 'Kaufman\'s Adaptive Moving Average'
LC_LSMA = '1LC-LSMA (1 line code lsma with 3 functions)'
LEOMA = 'Leo Moving Average'
LINWMA = 'Linear Weighted Moving Average'
LSMA = 'Least Squares Moving Average'
MAMA = 'MESA Adaptive Moving Average'
MCMA = 'McNicholl Moving Average'
MEDIAN = 'Median'
REGMA = 'Regularized Exponential Moving Average'
REMA = 'Range EMA'
REPMA = 'Repulsion Moving Average'
RMA = 'Relative Moving Average'
RSIMA = 'RSI Moving average'
RVWAP = '* Rolling VWAP'
SMA = 'Simple Moving Average'
SMMA = 'Smoothed Moving Average'
SRWMA = 'Square Root Weighted Moving Average'
SW_MA = 'Sine-Weighted Moving Average'
SWMA = '* Symmetrically Weighted Moving Average'
TEMA = 'Triple Exponential Moving Average'
THMA = 'Triple Hull Moving Average'
TREMA = 'Triangular Exponential Moving Average'
TRSMA = 'Triangular Simple Moving Average'
TT3 = 'Tillson T3'
VAMA = 'Volatility Adjusted Moving Average'
VIDYA = 'Variable Index Dynamic Average'
VWAP = '* VWAP'
VWMA = 'Volume-weighted Moving Average'
WMA = 'Weighted Moving Average'
WWMA = 'Welles Wilder Moving Average'
XEMA = 'Optimized Exponential Moving Average'
ZEMA = 'Zero-Lag Exponential Moving Average'
ZSMA = 'Zero-Lag Simple Moving Average'
Moving_AveragesLibrary "Moving_Averages"
This library contains majority important moving average functions with int series support. Which means that they can be used with variable length input. For conventional use, please use tradingview built-in ta functions for moving averages as they are more precise. I'll use functions in this library for my other scripts with dynamic length inputs.
ema(src, len)
Exponential Moving Average (EMA)
Parameters:
src : Source
len : Period
Returns: Exponential Moving Average with Series Int Support (EMA)
alma(src, len, a_offset, a_sigma)
Arnaud Legoux Moving Average (ALMA)
Parameters:
src : Source
len : Period
a_offset : Arnaud Legoux offset
a_sigma : Arnaud Legoux sigma
Returns: Arnaud Legoux Moving Average (ALMA)
covwema(src, len)
Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
covwma(src, len)
Coefficient of Variation Weighted Moving Average (COVWMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Moving Average (COVWMA)
dema(src, len)
DEMA - Double Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: DEMA - Double Exponential Moving Average
edsma(src, len, ssfLength, ssfPoles)
EDSMA - Ehlers Deviation Scaled Moving Average
Parameters:
src : Source
len : Period
ssfLength : EDSMA - Super Smoother Filter Length
ssfPoles : EDSMA - Super Smoother Filter Poles
Returns: Ehlers Deviation Scaled Moving Average (EDSMA)
eframa(src, len, FC, SC)
Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
Parameters:
src : Source
len : Period
FC : Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
Returns: Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
ehma(src, len)
EHMA - Exponential Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Exponential Hull Moving Average (EHMA)
etma(src, len)
Exponential Triangular Moving Average (ETMA)
Parameters:
src : Source
len : Period
Returns: Exponential Triangular Moving Average (ETMA)
frama(src, len)
Fractal Adaptive Moving Average (FRAMA)
Parameters:
src : Source
len : Period
Returns: Fractal Adaptive Moving Average (FRAMA)
hma(src, len)
HMA - Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Hull Moving Average (HMA)
jma(src, len, jurik_phase, jurik_power)
Jurik Moving Average - JMA
Parameters:
src : Source
len : Period
jurik_phase : Jurik (JMA) Only - Phase
jurik_power : Jurik (JMA) Only - Power
Returns: Jurik Moving Average (JMA)
kama(src, len, k_fastLength, k_slowLength)
Kaufman's Adaptive Moving Average (KAMA)
Parameters:
src : Source
len : Period
k_fastLength : Number of periods for the fastest exponential moving average
k_slowLength : Number of periods for the slowest exponential moving average
Returns: Kaufman's Adaptive Moving Average (KAMA)
kijun(_high, _low, len, kidiv)
Kijun v2
Parameters:
_high : High value of bar
_low : Low value of bar
len : Period
kidiv : Kijun MOD Divider
Returns: Kijun v2
lsma(src, len, offset)
LSMA/LRC - Least Squares Moving Average / Linear Regression Curve
Parameters:
src : Source
len : Period
offset : Offset
Returns: Least Squares Moving Average (LSMA)/ Linear Regression Curve (LRC)
mf(src, len, beta, feedback, z)
MF - Modular Filter
Parameters:
src : Source
len : Period
beta : Modular Filter, General Filter Only - Beta
feedback : Modular Filter Only - Feedback
z : Modular Filter Only - Feedback Weighting
Returns: Modular Filter (MF)
rma(src, len)
RMA - RSI Moving average
Parameters:
src : Source
len : Period
Returns: RSI Moving average (RMA)
sma(src, len)
SMA - Simple Moving Average
Parameters:
src : Source
len : Period
Returns: Simple Moving Average (SMA)
smma(src, len)
Smoothed Moving Average (SMMA)
Parameters:
src : Source
len : Period
Returns: Smoothed Moving Average (SMMA)
stma(src, len)
Simple Triangular Moving Average (STMA)
Parameters:
src : Source
len : Period
Returns: Simple Triangular Moving Average (STMA)
tema(src, len)
TEMA - Triple Exponential Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Exponential Moving Average (TEMA)
thma(src, len)
THMA - Triple Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Hull Moving Average (THMA)
vama(src, len, volatility_lookback)
VAMA - Volatility Adjusted Moving Average
Parameters:
src : Source
len : Period
volatility_lookback : Volatility lookback length
Returns: Volatility Adjusted Moving Average (VAMA)
vidya(src, len)
Variable Index Dynamic Average (VIDYA)
Parameters:
src : Source
len : Period
Returns: Variable Index Dynamic Average (VIDYA)
vwma(src, len)
Volume-Weighted Moving Average (VWMA)
Parameters:
src : Source
len : Period
Returns: Volume-Weighted Moving Average (VWMA)
wma(src, len)
WMA - Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Weighted Moving Average (WMA)
zema(src, len)
Zero-Lag Exponential Moving Average (ZEMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Exponential Moving Average (ZEMA)
zsma(src, len)
Zero-Lag Simple Moving Average (ZSMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Simple Moving Average (ZSMA)
evwma(src, len)
EVWMA - Elastic Volume Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Elastic Volume Weighted Moving Average (EVWMA)
tt3(src, len, a1_t3)
Tillson T3
Parameters:
src : Source
len : Period
a1_t3 : Tillson T3 Volume Factor
Returns: Tillson T3
gma(src, len)
GMA - Geometric Moving Average
Parameters:
src : Source
len : Period
Returns: Geometric Moving Average (GMA)
wwma(src, len)
WWMA - Welles Wilder Moving Average
Parameters:
src : Source
len : Period
Returns: Welles Wilder Moving Average (WWMA)
ama(src, _high, _low, len, ama_f_length, ama_s_length)
AMA - Adjusted Moving Average
Parameters:
src : Source
_high : High value of bar
_low : Low value of bar
len : Period
ama_f_length : Fast EMA Length
ama_s_length : Slow EMA Length
Returns: Adjusted Moving Average (AMA)
cma(src, len)
Corrective Moving average (CMA)
Parameters:
src : Source
len : Period
Returns: Corrective Moving average (CMA)
gmma(src, len)
Geometric Mean Moving Average (GMMA)
Parameters:
src : Source
len : Period
Returns: Geometric Mean Moving Average (GMMA)
ealf(src, len, LAPercLen_, FPerc_)
Ehler's Adaptive Laguerre filter (EALF)
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Adaptive Laguerre filter (EALF)
elf(src, len, LAPercLen_, FPerc_)
ELF - Ehler's Laguerre filter
Parameters:
src : Source
len : Period
LAPercLen_ : Median Length
FPerc_ : Median Percentage
Returns: Ehler's Laguerre Filter (ELF)
edma(src, len)
Exponentially Deviating Moving Average (MZ EDMA)
Parameters:
src : Source
len : Period
Returns: Exponentially Deviating Moving Average (MZ EDMA)
pnr(src, len, rank_inter_Perc_)
PNR - percentile nearest rank
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Nearest Rank (PNR)
pli(src, len, rank_inter_Perc_)
PLI - Percentile Linear Interpolation
Parameters:
src : Source
len : Period
rank_inter_Perc_ : Rank and Interpolation Percentage
Returns: Percentile Linear Interpolation (PLI)
rema(src, len)
Range EMA (REMA)
Parameters:
src : Source
len : Period
Returns: Range EMA (REMA)
sw_ma(src, len)
Sine-Weighted Moving Average (SW-MA)
Parameters:
src : Source
len : Period
Returns: Sine-Weighted Moving Average (SW-MA)
vwap(src, len)
Volume Weighted Average Price (VWAP)
Parameters:
src : Source
len : Period
Returns: Volume Weighted Average Price (VWAP)
mama(src, len)
MAMA - MESA Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: MESA Adaptive Moving Average (MAMA)
fama(src, len)
FAMA - Following Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Following Adaptive Moving Average (FAMA)
hkama(src, len)
HKAMA - Hilbert based Kaufman's Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Hilbert based Kaufman's Adaptive Moving Average (HKAMA)
NoBrain BreakoutUse 3min. Time frame.
Buy Stock Selection:-
When Close Price Cross Monthly Standard Pivot R1 & Monthly Standard Pivot R1 is Greater than Previous Day High( PDH ) Or Close.
Price must be Above 44 MA ,48 EMA & Vwap
***Buy When 3min Candle closed Above Camarilla R4 or Monthly Standard Pivot R1 whichever is High.
Sell Stock Selection:-
When Close Price Cross Monthly Standard Pivot S1 & Monthly Standard Pivot S1 is Less than Previous Day Low( PDL ) Or Close.
Price must be Below 44 MA ,48 EMA & Vwap
***Sell When 3min Candle closed Below Camarilla S4 or Monthly Standard Pivot S1 whichever is Low.
Trading time for
1st wave 9.30am to 10.45am.
2nd wave 12.45pm to 2.45pm.
(Based on NSE/ BSE India)
Indicators:-
1) Pivot Points Standard - Time Frame monthly.only select R1
2) Pivot Points Camarilla- Only select R4.
3) SMA 44
4) EMA 48
5) Vwap
6) For Trailing Stop Loss use SuperTrend- Length-13 Factor-2.7 or Length-15 Factor-3 (3min Timeframe)
Multi-Timeframe (MTF) Dashboard by RiTzMulti-Timeframe Dashboard
Shows values of different Indiactors on Multiple-Timeframes for the selected script/symbol
VWAP : if LTP is trading above VWAP then Bullish else if LTP is trading below VWAP then Bearish.
ST(21,1) : if LTP is trading above Supertrend (21,1) then Bullish , else if LTP is trading below Supertrend (21,1) then Bearish.
ST(14,2) : if LTP is trading above Supertrend (14,2) then Bullish , else if LTP is trading below Supertrend (14,2) then Bearish.
ST(10,3) : if LTP is trading above Supertrend (10,3) then Bullish , else if LTP is trading below Supertrend (10,3) then Bearish.
RSI(14) : Shows value of RSI (14) for the current timeframe.
ADX : if ADX is > 75 and DI+ > DI- then "Bullish ++".
if ADX is < 75 but >50 and DI+ > DI- then "Bullish +".
if ADX is < 50 but > 25 and DI+ > DI- then "Bullish".
if ADX is above 75 and DI- > DI+ then "Bearish ++".
if ADX is < 75 but > 50 and DI- > DI+ then "Bearish+".
if ADX is < 50 but > 25 and DI- > DI+ then "Bearish".
if ADX is < 25 then "Neutral".
MACD : if MACD line is above Signal Line then "Bullish", else if MACD line is below Signal Line then "Bearish".
PH-PL : "< PH > PL" means LTP is trading between Previous Timeframes High(PH) & Previous Timeframes Low(PL) which indicates Rangebound-ness.
"> PH" means LTP is trading above Previous Timeframes High(PH) which indicates Bullish-ness.
"< PL" means LTP is trading below Previous Timeframes Low(PL) which indicates Bearish-ness.
Alligator : If Lips > Teeth > Jaw then Bullish.
If Lips < Teeth < Jaw then Bearish.
If Lips > Teeth and Teeth < Jaw then Neutral/Sleeping.
If Lips < Teeth and Teeth > Jaw then Neutral/Sleeping.
Settings :
Style settings :-
Dashboard Location: Location of the dashboard on the chart
Dashboard Size: Size of the dashboard on the chart
Bullish Cell Color: Select the color of cell whose value is showing Bullish-ness.
Bearish Cell Color: Select the color of cell whose value is showing Bearish-ness.
Neutral Cell Color: Select the color of cell whose value is showing Rangebound-ness.
Cell Transparency: Select Transparency of cell.
Column Settings :-
You can select which Indicators values should be displayed/hidden.
Timeframe Settings :-
You can select which timeframes values should be displayed/hidden.
Note :- I'm not a pro Developer/Coder , so if there are any mistakes or any suggestions for improvements in the code then do let me know!
Note :- Use in Live market , might show wrong values for timeframes other than current timeframe in closed market!!
Nifty / Banknifty Dashboard by RiTzNifty / Banknifty Dashboard :
Shows Values of different Indicators on current Timeframe for the selected Index & it's main constituents according to weightage in index.
customized for Nifty & Banknifty (You can customize it according to your needs for the markets/indexes you trade in)
Interpretation :-
VWAP : if LTP is trading above VWAP then Bullish else if LTP is trading below VWAP then Bearish.
ST(21,1) : if LTP is trading above Supertrend (21,1) then Bullish , else if LTP is trading below Supertrend (21,1) then Bearish.
ST(14,2) : if LTP is trading above Supertrend (14,2) then Bullish , else if LTP is trading below Supertrend (14,2) then Bearish.
ST(10,3) : if LTP is trading above Supertrend (10,3) then Bullish , else if LTP is trading below Supertrend (10,3) then Bearish.
RSI(14) : Shows value of RSI (14) for the current timeframe.
ADX : if ADX is > 75 and DI+ > DI- then "Bullish ++".
if ADX is < 75 but >50 and DI+ > DI- then "Bullish +".
if ADX is < 50 but > 25 and DI+ > DI- then "Bullish".
if ADX is above 75 and DI- > DI+ then "Bearish ++".
if ADX is < 75 but > 50 and DI- > DI+ then "Bearish+".
if ADX is < 50 but > 25 and DI- > DI+ then "Bearish".
if ADX is < 25 then "Neutral".
MACD : if MACD line is above Signal Line then "Bullish", else if MACD line is below Signal Line then "Bearish".
PDH-PDL : "< PDH > PDL" means LTP is trading between Previous Days High(PDH) & Previous Days Low(PDL) which indicates Rangebound-ness.
"> PDH" means LTP is trading above Previous Days High(PDH) which indicates Bullish-ness.
"< PDL" means LTP is trading below Previous Days Low(PDL) which indicates Bearish-ness.
Alligator : If Lips > Teeth > Jaw then Bullish.
If Lips < Teeth < Jaw then Bearish.
If Lips > Teeth and Teeth < Jaw then Neutral/Sleeping.
If Lips < Teeth and Teeth > Jaw then Neutral/Sleeping.
Settings :
Style settings :-
Dashboard Location: Location of the dashboard on the chart
Dashboard Size: Size of the dashboard on the chart
Bullish Cell Color: Select the color of cell whose value is showing Bullish-ness.
Bearish Cell Color: Select the color of cell whose value is showing Bearish-ness.
Neutral Cell Color: Select the color of cell whose value is showing Rangebound-ness.
Cell Transparency: Select Transparency of cell.
Columns Settings :-
You can select which Indicators values should be displayed/hidden.
Rows Settings :-
You can select which Stocks/Symbols values should be displayed/hidden.
Symbol Settings :-
Here you can select the Index & Stocks/Symbols
Dashboard for Index : select Nifty/Banknifty
if you select Nifty then Nifty spot, Nifty current Futures and the stocks with most weightage in Nifty index will be displayed on the Dashboard/Table.
if you select Banknifty then Banknifty spot, Banknifty current Futures and the stocks with most weightage in Banknifty index will be displayed on the Dashboard/Table.
You can Customise it according to your needs, you can choose any Symbols you want to use.
Note :- This is inspired from "RankDelta" by AsitPati and "Nifty and Bank Nifty Dashboard v2" by cvsk123 (Both these scripts are closed source!)
I'm not a pro Developer/Coder , so if there are any mistakes or any suggestions for improvements in the code then do let me know!
Super scalpThis is scalp strategy based on the confluence of 3 indicators
ema 9 , supertrend and vwap
when supertrend buy signal is generated and the price is above ema and vwap scalp buy signal is generated
when supertrend sell signal is generated and the price is below ema and vwap scalp sell signal is generated
pandas_taLibrary "pandas_ta"
Level: 3
Background
Today is the first day of 2022 and happy new year every tradingviewers! May health and wealth go along with you all the time. I use this chance to publish my 1st PINE v5 lib : pandas_ta
This is not a piece of cake like thing, which cost me a lot of time and efforts to build this lib. Beyond 300 versions of this script was iterated in draft.
Function
Library "pandas_ta"
PINE v5 Counterpart of Pandas TA - A Technical Analysis Library in Python 3 at github.com
The Original Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns.
I realized most of indicators except Candlestick Patterns because tradingview built-in Candlestick Patterns are even more powerful!
I use this to verify pandas_ta python version indicators for myself, but I realize that maybe many may need similar lib for pine v5 as well.
Function Brief Descriptions (Pls find details in script comments)
bton --> Binary to number
wcp --> Weighted Closing Price (WCP)
counter --> Condition counter
xbt --> Between
ebsw --> Even Better SineWave (EBSW)
ao --> Awesome Oscillator (AO)
apo --> Absolute Price Oscillator (APO)
xrf --> Dynamic shifted values
bias --> Bias (BIAS)
bop --> Balance of Power (BOP)
brar --> BRAR (BRAR)
cci --> Commodity Channel Index (CCI)
cfo --> Chande Forcast Oscillator (CFO)
cg --> Center of Gravity (CG)
cmo --> Chande Momentum Oscillator (CMO)
coppock --> Coppock Curve (COPC)
cti --> Correlation Trend Indicator (CTI)
dmi --> Directional Movement Index(DMI)
er --> Efficiency Ratio (ER)
eri --> Elder Ray Index (ERI)
fisher --> Fisher Transform (FISHT)
inertia --> Inertia (INERTIA)
kdj --> KDJ (KDJ)
kst --> 'Know Sure Thing' (KST)
macd --> Moving Average Convergence Divergence (MACD)
mom --> Momentum (MOM)
pgo --> Pretty Good Oscillator (PGO)
ppo --> Percentage Price Oscillator (PPO)
psl --> Psychological Line (PSL)
pvo --> Percentage Volume Oscillator (PVO)
qqe --> Quantitative Qualitative Estimation (QQE)
roc --> Rate of Change (ROC)
rsi --> Relative Strength Index (RSI)
rsx --> Relative Strength Xtra (rsx)
rvgi --> Relative Vigor Index (RVGI)
slope --> Slope
smi --> SMI Ergodic Indicator (SMI)
sqz* --> Squeeze (SQZ) * NOTE: code sufferred from very strange error, code was commented.
sqz_pro --> Squeeze PRO(SQZPRO)
xfl --> Condition filter
stc --> Schaff Trend Cycle (STC)
stoch --> Stochastic (STOCH)
stochrsi --> Stochastic RSI (STOCH RSI)
trix --> Trix (TRIX)
tsi --> True Strength Index (TSI)
uo --> Ultimate Oscillator (UO)
willr --> William's Percent R (WILLR)
alma --> Arnaud Legoux Moving Average (ALMA)
xll --> Dynamic rolling lowest values
dema --> Double Exponential Moving Average (DEMA)
ema --> Exponential Moving Average (EMA)
fwma --> Fibonacci's Weighted Moving Average (FWMA)
hilo --> Gann HiLo Activator(HiLo)
hma --> Hull Moving Average (HMA)
hwma --> HWMA (Holt-Winter Moving Average)
ichimoku --> Ichimoku Kinkō Hyō (ichimoku)
jma --> Jurik Moving Average Average (JMA)
kama --> Kaufman's Adaptive Moving Average (KAMA)
linreg --> Linear Regression Moving Average (linreg)
mgcd --> McGinley Dynamic Indicator
rma --> wildeR's Moving Average (RMA)
sinwma --> Sine Weighted Moving Average (SWMA)
ssf --> Ehler's Super Smoother Filter (SSF) © 2013
supertrend --> Supertrend (supertrend)
xsa --> X simple moving average
swma --> Symmetric Weighted Moving Average (SWMA)
t3 --> Tim Tillson's T3 Moving Average (T3)
tema --> Triple Exponential Moving Average (TEMA)
trima --> Triangular Moving Average (TRIMA)
vidya --> Variable Index Dynamic Average (VIDYA)
vwap --> Volume Weighted Average Price (VWAP)
vwma --> Volume Weighted Moving Average (VWMA)
wma --> Weighted Moving Average (WMA)
zlma --> Zero Lag Moving Average (ZLMA)
entropy --> Entropy (ENTP)
kurtosis --> Rolling Kurtosis
skew --> Rolling Skew
xev --> Condition all
zscore --> Rolling Z Score
adx --> Average Directional Movement (ADX)
aroon --> Aroon & Aroon Oscillator (AROON)
chop --> Choppiness Index (CHOP)
xex --> Condition any
cksp --> Chande Kroll Stop (CKSP)
dpo --> Detrend Price Oscillator (DPO)
long_run --> Long Run
psar --> Parabolic Stop and Reverse (psar)
short_run --> Short Run
vhf --> Vertical Horizontal Filter (VHF)
vortex --> Vortex
accbands --> Acceleration Bands (ACCBANDS)
atr --> Average True Range (ATR)
bbands --> Bollinger Bands (BBANDS)
donchian --> Donchian Channels (DC)
kc --> Keltner Channels (KC)
massi --> Mass Index (MASSI)
natr --> Normalized Average True Range (NATR)
pdist --> Price Distance (PDIST)
rvi --> Relative Volatility Index (RVI)
thermo --> Elders Thermometer (THERMO)
ui --> Ulcer Index (UI)
ad --> Accumulation/Distribution (AD)
cmf --> Chaikin Money Flow (CMF)
efi --> Elder's Force Index (EFI)
ecm --> Ease of Movement (EOM)
kvo --> Klinger Volume Oscillator (KVO)
mfi --> Money Flow Index (MFI)
nvi --> Negative Volume Index (NVI)
obv --> On Balance Volume (OBV)
pvi --> Positive Volume Index (PVI)
dvdi --> Dual Volume Divergence Index (DVDI)
xhh --> Dynamic rolling highest values
pvt --> Price-Volume Trend (PVT)
Remarks
I also incorporated func descriptions and func test script in commented mode, you can test the functino with the embedded test script and modify them as you wish.
This is a Level 3 free and open source indicator library.
Feedbacks are appreciated.
This is not the end of pandas_ta lib publication, but it is start point with pine v5 lib function and I will add more and more funcs into this lib for my own indicators.
Function Name List:
bton()
wcp()
count()
xbt()
ebsw()
ao()
apo()
xrf()
bias()
bop()
brar()
cci()
cfo()
cg()
cmo()
coppock()
cti()
dmi()
er()
eri()
fisher()
inertia()
kdj()
kst()
macd()
mom()
pgo()
ppo()
psl()
pvo()
qqe()
roc()
rsi()
rsx()
rvgi()
slope()
smi()
sqz_pro()
xfl()
stc()
stoch()
stochrsi()
trix()
tsi()
uo()
willr()
alma()
wcx()
xll()
dema()
ema()
fwma()
hilo()
hma()
hwma()
ichimoku()
jma()
kama()
linreg()
mgcd()
rma()
sinwma()
ssf()
supertrend()
xsa()
swma()
t3()
tema()
trima()
vidya()
vwap()
vwma()
wma()
zlma()
entropy()
kurtosis()
skew()
xev()
zscore()
adx()
aroon()
chop()
xex()
cksp()
dpo()
long_run()
psar()
short_run()
vhf()
vortex()
accbands()
atr()
bbands()
donchian()
kc()
massi()
natr()
pdist()
rvi()
thermo()
ui()
ad()
cmf()
efi()
ecm()
kvo()
mfi()
nvi()
obv()
pvi()
dvdi()
xhh()
pvt()
Bogdan Ciocoiu - Looking Glass► Description
The script shows a multi-timeline suite of information for the current ticker. This information refers to configurable moving averages, RSI, Stochastic RSI, VWAP and TSI data. The timeframes reflected in the script vary from 1m to 1h. I recommend the tool for 3m scalping as it provides good visibility upwards.
The headings from the table are:
{Close} - {MA1}
{Close} - {MA2}
{Close} - {MA3}
{MA1} - {MA2}
{MA2} - {MA3}
{RSI}
{Stoch RSI K}
{Stoch RSI D}
{VWAP}
{TSI}
{TSI EMA}
{TSI} - {TSI EMA}
► Originality and usefulness
This tool is helpful because it helps users read a chart much quicker than if they were to navigate between timeframes. The colour coding indicates an accident/descendant trend between any two values (i.e. close vs MA1, MA1-MA2, RSI K vs RSI D, etc.).
► Open-source reuse
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
WaveTrend 4h/24mWaveTrend 4h/24m is a trading tool based on two WaveTrend timeframes.
For this script the WaveTrend calculations made by LazyBear were used. WaveTrend is a widely used indicator for finding direction of an asset.
The strategy is developed by Youtuber Jayson Casper. The main strategy on the 4 hour and 24 minute timeframes, this will be the default timeframes. Timeframes can be adjusted in the indicator interface.
With Jaysons' we wait for both timeframes to have last printed a green dot for longs, and both timeframes to have last printed a red dot for shorts. When this occurs a green diamond will be printed for longs, a red diamond for shorts.
Make sure to always use the chart from the smallest timeframe you're using, so by defaults use the 24 minute chart.
Features of the indicator:
- WaveTrend Timeframe 1 (Blue/Lightblue wave).
- WaveTrend Timeframe 2 (Blue/Purple line with filled background between the lines).
- VWAP (Yellow wave which is turned off by default)
- Green/Red Diamonds
What to look for?
This script is all about the Green and Red Diamonds.
A Green diamond will be printed when on both the 4 hour and 24 minute timeframe the last printed dot was a green dot.
A Red diamond will be printed when on both the 4 hour and 24 minute timeframe the last printed dot was a red dot.
What are the Green and Red Diamonds based on?
When both VWAP timeframes are ABOVE 0, a green diamond will be printed. This is equivalent to the last dot on both WaveTrend timeframes being a green dot.
When both VWAP timeframes are BELOW 0, a red diamond will be printed. This is equivalent to the last dot on both WaveTrend timeframes being a red dot.
Happy Trading!
PROFIT INDICATORFirst let me tell you which indicators have been used in this script so that you have the confidence while taking the trade:
(a) Bollinger Band with 20 SMA Inside it - Currently it is off, you can turn it on from settings.
(b) HMA 33, I have added the option of using two HMA's simultaneously. You can use HMA, EMA, SMA as per your settings and it would be color trending.
(c) VWAP- you can turn it on from settings
(d) CPR- you can turn it on from settings
(e) EMA's 20, 50, 200. Currently off, you can turn it on from settings.
(d) SMA's 50 and 200. Currently off, yu can turn it on from settings, if you want to use 20 SMA you can use bollinger band basis that is 20 period SMA.
(f) Trend bar at bottom on the basis of 50 EMA.
(g) Half Trend
(h) Trend strength Detector
(d) EMA 50 high and low to show the pac channel. I am not using this however as per request I have added this. Currently, it is trun on and you can turn it off from settings.
(f) Auto Fib levels
Please use a stick note for few days and mention imp notes before taking trade to check if all the conditions are matching to take the trade.
Buy Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close above support in green.
3. Check the trend bar at bottom, it should be green, if it is grey in colour dont enter in trade.
4. Candle should be closing above EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in green for buy.
7. Half trend Indicator should give buy signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big upside, you can go for buy.
9. Exit from buy trade when it start showing very small arrow which means trend is about to change.
10.Exit buy trade at 61.8 Fib level
Sell Condition:-
1. Bolling band should be widely open.
2. Check the support and resistance from CPR. Candle should close below resistance in red.
3. Check the trend bar at bottom, it should be red, if it is grey in colour dont enter in trade.
4. Candle should be closing below EMA 50 and its upto you if you need additional confirmation, you can use EMA 20, 50, 200 and SMA 50 and 200, this is optional.
5. You can use VWAP as support or resistance and you can turn it on from settings.
6. Trending HMA of 33 should be in red for sell.
7. Half trend Indicator should give sell signal.
8. Trend Strength Indicator for checking the strength of the trend, if the arrow is big downside, you can go for sell.
9. Exit from sell trade when down arrows start showing very small in size which means trend is about to change.
10.Exit sell trade at 61.8 Fib level
Pulu's 3 Moving Averages
Pulu's 3 Moving Averages
Release version 1, date 2021-09-28
This script allows you to customize three sets of moving averages, turn on/off, set color and parameters. It also tags the start date of the last set of moving average if there is. This, release version 1, supports eight moving average algorithms:
ALMA, Arnaud Legoux Moving Average
EMA, Exponential Moving Average
RMA, Adjusted exponential moving average (aka Wilder’s EMA)
SMA, Simple Moving Average
SWMA, Symmetrically-Weighted Moving Average
VWAP, Volume-Weighted Average Price
VWMA, Volume-Weighted Moving Average
WMA, Weighted Moving Average
The availability and function parameters
Func. Availability Parameters
ALMA
MA1, MA2, MA3
source
length
offset
sigma
EMA
RMA
SMA
VWMA
WMA
MA1, MA2, MA3
source
length
SWMA
VWAP
MA1
source
Parameters
Parameter Description
source the series of values to process. The default is to use the closing price to calculate the moving average.
length an integer value that defines the number of bars to calculate the moving average on. The SWMA and VWAP do not use this parameter.
ALMA offset a floating-point value that controls the tradeoff between smoothness (with a value closer to 1) and responsiveness (with a value closer to 0). This parameter is only used by ALMA.
ALMA sigma a floating-point value that specifies the ALMA’s smoothness. The larger this value, the smoother the moving average is. This parameter is only used by ALMA.
I'm not sure if it is needed, so I do not let the three Moving Averages of the script to have indivial algorithm setting. Because that will involve much complicated condition testing and use up more TradingView script lines limit. If you need to combine different algorithms in the three sets of moving averages, or have other ideas, leave a message to let me know; maybe I will try it in the next update.
我不確定是否需要，所以我沒有讓腳本的三組移動平均線有各別的算法設置。因為這將涉及更多複雜的條件測試，並使用更多 TradingView 腳本列數限制。如果您需要在三組均線中組合不同的算法，或者有其他想法，請留言告訴我；也許我會在下一次更新中嘗試。
Exponential moving averages Convergence to identify Strength of Exponential moving averages Convergence to identify Strength of the stock.
Description:
This script is developed to find Convergences for many indicators. It analyses Convergences of 20days, 50days, 100days, 150days and 200days exponential moving averages. When all the plotted lines are converged and Price of stock is above the Convergence the stock is bullish, similarly if the price of the stock is below the convergence stock is bearish.
This indicator gives you VWAP and EMA’s for convergence along with Bollinger Bands.
VWAP and Bollinger bands and EMA’s can be altered as you required.
In settings menu we can enable and disable VWAP, EMA’S & Bollinger bands and in style menu even we can choose required EMA
It helps for convergence.
TWAP TrendHere we are experimenting with using TWAP for trend analysis. It appears to work better than VWAP on lower timeframes.
TWAP is a tool used by algorithm based traders that allows them to distribute their orders throughout the day without disturbing price or having their positions known to rival traders in the market. It's similar to VWAP and serves the same function, except it lacks the volume aspect. This can be an issue when position entry/exit may be affected by slippage.
The main benefit of TWAP is deciding how to distribute orders throughout the chosen timeframe. However, just like the VWAP traders will normally use it as a moving average or target for price action to pull into.
There is an option to change the timeframe that TWAP is calculated from.
Originally by NeoButane:
Non Parametric Adaptive Moving AverageIntroduction
Not be confused with non-parametric statistics, i define a "non-parametric" indicator as an indicator who does not have any parameter input. Such indicators can be useful since they don't need to go through parameter optimization. I present here a non parametric adaptive moving average based on exponential averaging using a modified ratio of open-close to high-low range indicator as smoothing variable.
The Indicator
The ratio of open-close to high-low range is a measurement involving calculating the ratio between the absolute close/open price difference and the range (high - low) , now the relationship between high/low and open/close price has been studied in econometrics for some time but there are no reason that the ohlc range ratio may be an indicator of volatility, however we can make the hypothesis that trending markets contain less indecision than ranging market and that indecision is measured by the high/low movements, this is an idea that i've heard various time.
Since the range is always greater than the absolute close/open difference we have a scaled smoothing variable in a range of 0/1, this allow to perform exponential averaging. The ratio of open-close to high-low range is calculated using the vwap of the close/high/low/open price in order to increase the smoothing effect. The vwap tend to smooth more with low time frames than higher ones, since the indicator use vwap for the calculation of its smoothing variable, smoothing may differ depending on the time frame you are in.
1 minute tf
1 hour tf
Conclusion
Making non parametric indicators is quite efficient, but they wont necessarily outperform classical parametric indicators. I also presented a modified version of the ratio of open-close to high-low range who can provide a smoothing variable for exponential averaging. I hope the indicator can help you in any way.
Thanks for reading !
The Great Anchors: Dual AVWAP Powered by RSI
The Great Anchors
*Dual Anchored Volume Weighted Average Price Powered by RSI*
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📌 Overview
The Great Anchors is a dual AVWAP-based indicator that resets dynamically using RSI extremes — either from the current asset or a master symbol (e.g., BTCUSDT). It identifies meaningful shifts in price structure and momentum using these "anchored" levels.
It’s designed to help traders spot trend continuations, momentum inflection points, and entry signals aligned with overbought/oversold conditions — but only when the market confirms through volume-weighted price direction.
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🛠 Core Logic
• AVWAP 1 (favwap): Anchored when RSI reaches overbought levels (top anchor)
• AVWAP 2 (savwap): Anchored when RSI reaches oversold levels (bottom anchor)
• AVWAPs are recalculated each time a new OB/OS condition is triggered — acting like "fresh anchors" at key market turning points.
---
⚙️ Key Features
🔁 Auto or Manual RSI Thresholds
→ Automatically determines dynamic RSI OB/OS levels based on past peaks and troughs, or lets you set fixed levels.
🧠 Master Symbol Control
→ Use the RSI of a separate asset (like BTCUSDT, ETHUSDT, SOLUSDT, BNBUSDT, SUPRAUSDT) or indices (like TOTAL, TOTAL2, BFR) to control resets — ideal for tracking how BTC/major coins impacts altcoins/others.
🔍 Trend-Filtering Signal Logic
→ Signals are filtered for less noise and are triggered when:
- Both AVWAPs are rising (bullish) or falling (bearish)
- Price action confirms the structure
🎯 Visual Markers & Alerts
→ "💥" for bullish signals and "🔥" for bearish ones. Alerts included for automation or push notifications.
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🎯 How to Use It
1. Add the indicator to your chart.
2. Choose whether to use RSI from the current symbol or a master symbol (e.g., BTC).
3. Select auto-adjusted or manual OB/OS levels.
4. Watch for:
- AVWAP(s) making a significant change (at this point it's one of the AVWAPs resetting)
- Check if price flip it upwards or downwards
- If price goes above both AVWAPs thats a likely bullish trend
- If price can't go above both AVWAPs up and fall bellow both that's a likely bearish trend
- Price retesting upper AVWAP and bounce
- likely bullish continuation
- Price retesting lower AVWAP and dip
- likely bearish continuation
- Signal icons on chart ("💥 - Bullish" or "🔥- Bearish")
Best suited for:
• Swing traders
• Momentum traders
• Traders timing altcoin entries using BTC/Major asset's RSI
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🔔 Signal Explanation
💥 Bullish Signal =
• Both AVWAPs rising
• Higher lows in price structure
• Bullish candle close
• Triggered from overbought RSI reset
🔥 Bearish Signal =
• Both AVWAPs falling
• Lower highs in price structure
• Bearish candle close
• Triggered from oversold RSI reset
Signals reset by opposite signals to prevent noise or overfitting.
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⚠️ Tips & Notes
• Use AVWAPs as dynamic support/resistance, even without signal triggers
• Pair with volume or divergence tools for stronger confirmation
---
🧩 Credits & Philosophy
This tool is built with a simple philosophy:
"Anchor your trades to meaningful moments in price — not arbitrary time."
The dual AVWAP concept helps you see how price reacts after momentum peaks, giving you a cleaner bias and more precise trade setups.
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Relative Directional Index (RDI)🔍 Overview
The Relative Directional Index (RDI) is a hybrid tool that fuses the Average Directional and the Relative Strength Indices (ADX and RSI) into a single, highly visual interface. While the former captures trend strength, the latter reveals momentum shifts and potential exhaustion. Together, they can confirm trend structure, anticipate reversals, and sharpen the timing entries and exits.
📌 Why Combine ADX with RSI?
Most indicators focus on either trend-following (like ADX) or momentum detection (like RSI)—but rarely both. Each comes with trade-offs:
- ADX alone confirms trend strength but ignores momentum.
- RSI alone signals overbought/oversold, but lacks trend context.
The RDI resolves this by integrating both, offering:
- Smarter filters for trend entries
- Early warnings of momentum breakdowns
- More confident signal validation
🧠 Design Note: Fibonacci Harmony
All default values—5, 13, 21—are Fibonacci numbers. This is intentional, as these values reflect the natural rhythm of market cycles, and promote harmonic calibration between price action and indicator logic.
🔥 Key Features
✅ ADX Histogram
- Green bars = trend gaining strength
- Red bars = trend weakening
- Adjustable transparency for visual tuning
✅ ADX Line (Orange)
- Measures trend strength over time
- Rising = accelerating trend
- Falling = trend may be fading
✅ RSI Line (Lemon Yellow)
- Captures momentum surges and slowdowns
- Above 50 = bullish control
- Below 50 = bearish pressure
✅ Trend Strength Squares
- Bright green = strong uptrend
- Bright red = strong downtrend
- Faded colors = range-bound or indecisive
✅ ADX/RSI Crossover Markers
- Yellow square = RSI crosses above ADX → momentum building
- Orange square = ADX crosses above RSI → trend still dominant
✅ Customizable Reference Lines
- Yellow (50) = strong trend threshold
- Red (30) = weak trend zone
- Green (70) = overextended, potential exhaustion
_______________________________________________________
🎯 How to Trade with the RDI
The RDI helps traders identify momentum-supported trends, catch early reversals, and avoid false signals during consolidation.
✅ Trend Confirmation Entries
🔼 Bullish → Enter long on pullbacks or resistance breakouts
- ADX rising above 30
- RSI above 50
- Green trend square visible
🔽 Bearish → Enter short on breakdowns or failed retests
- ADX rising
- RSI below 50
- Red trend square visible
🧯 Exit if RSI crosses back against trend direction or ADX flattens
🚨 Reversal Setups Using Divergence
📈 Bullish Divergence → Long entry after confirmation (e.g. engulfing bar, volume spike)
- Price prints lower low
- RSI prints higher low
- Green triangle
📉 Bearish Divergence → Short entry on breakdown
- Price prints higher high
- RSI prints lower high
- Red triangle
Tip: Stronger if ADX is declining (fading trend strength)
🔂 Breakout Detection via Cross Markers
- Yellow square = RSI > ADX → breakout brewing
- Orange square = ADX > RSI → trend continuation likely
⏸️ Avoid Choppy Markets
- RSI between 45–55
- Faded trend squares
- Flat ADX below 20–30
🧠 Pro Tips
- Combine RDI with VWAPs, moving averages and/or pitchforks
- Watch for alignment between trend and momentum
- Use divergence markers as confirmation, not stand-alone triggers
_______________________________________________________
⚠️ Hidden Divergence (Optional)
The RDI includes optional hidden divergence detection. These signals suggest trend continuation but are off by default. Use with discretion—best in established trends, not sideways markets.
🙈 Hidden Bullish
- Price prints higher low
- RSI prints lower low
🙈 Hidden Bearish
- Price prints lower high
- RSI prints higher high
CPR by NKDCentral Pivot Range (CPR) Trading Strategy:
The Central Pivot Range (CPR) is a widely-used tool in technical analysis, helping traders pinpoint potential support and resistance levels in the market. By using the CPR effectively, traders can better gauge market trends and determine favorable entry and exit points. This guide explores how the CPR works, outlines its calculation, and describes how traders can enhance their strategies using an extended 10-line version of CPR.
What Really Central Pivot Range (CPR) is?
At its core, the CPR consists of three key lines:
Pivot Point (PP) – The central line, calculated as the average of the previous day’s high, low, and closing prices.
Upper Range (R1) – Positioned above the Pivot Point, acting as a potential ceiling where price may face resistance.
Lower Range (S1) – Found below the Pivot Point, serving as a potential floor where price might find support.
Advanced traders often expand on the traditional three-line CPR by adding extra levels above and below the pivot, creating up to a 10-line system. This extended CPR allows for a more nuanced understanding of the market and helps identify more detailed trading opportunities.
Applying CPR for Trading Success
1. How CPR is Calculation
The CPR relies on the previous day's high (H), low (L), and close (C) prices to create its structure:
Pivot Point (PP) = (H + L + C) / 3
First Resistance (R1) = (2 * PP) - L
First Support (S1) = (2 * PP) - H
Additional resistance levels (R2, R3) and support levels (S2, S3) are calculated by adding or subtracting multiples of the previous day’s price range (H - L) from the Pivot Point.
2. Recognizing the Market Trend
To effectively trade using CPR, it’s essential to first determine whether the market is trending up (bullish) or down (bearish). In an upward-trending market, traders focus on buying at support levels, while in a downward market, they look to sell near resistance.
3. Finding Ideal Entry Points
Traders often look to enter trades when price approaches key levels within the CPR range. Support levels (S1, S2) offer buying opportunities, while resistance levels (R1, R2) provide selling opportunities. These points are considered potential reversal zones, where price may bounce or reverse direction.
4. Managing Risk with Stop-Loss Orders
Proper risk management is crucial in any trading strategy. A stop-loss should be set slightly beyond the support level for buy positions and above the resistance level for sell positions, ensuring that losses are contained if the market moves against the trader’s position.
5. Determining Profit Targets
Profit targets are typically set based on the distance between entry points and the next support or resistance level. Many traders apply a risk-reward ratio, aiming for larger potential profits compared to the potential losses. However, if the next resistance and support level is far then middle levels are used for targets (i.e. 50% of R1 and R2)
6. Confirmation Through Other Indicators
While CPR provides strong support and resistance levels, traders often use additional indicators to confirm potential trade setups. Indicators such as moving averages can
help validate the signals provided by the CPR.
7. Monitoring Price Action At CPR Levels
Constantly monitoring price movement near CPR levels is essential. If the price fails to break through a resistance level (R1) or holds firm at support (S1), it can offer cues on when to exit or adjust a trade. However, a strong price break past these levels often signals a continued trend.
8. Trading Breakouts with CPR
When the price breaks above resistance or below support with strong momentum, it may signal a potential breakout. Traders can capitalize on these movements by entering positions in the direction of the breakout, ideally confirmed by volume or other technical indicators.
9. Adapting to Changing Market Conditions
CPR should be used in the context of broader market influences, such as economic reports, news events, or geopolitical shifts. These factors can dramatically affect market direction and how price reacts to CPR levels, making it important to stay informed about external market conditions.
10. Practice and Backtesting for Improvements
Like any trading tool, the CPR requires practice. Traders are encouraged to backtest their strategies on historical price data to get a better sense of how CPR works in different market environments. Continuous analysis and practice help improve decision-making and strategy refinement.
The Advantages of Using a 10-Line CPR System
An extended 10-line CPR system—comprising up to five resistance and five support levels—provides more granular control and insight into market movements. This expanded view helps traders better gauge trends and identify more opportunities for entry and exit. Key benefits include:
R2, S2 Levels: These act as secondary resistance or support zones, giving traders additional opportunities to refine their trade entries and exits.
R3, S3 Levels: Provide an even wider range for identifying reversals or trend continuations in more volatile markets.
Flexibility: The broader range of levels allows traders to adapt to changing market conditions and make more precise decisions based on market momentum.
So in Essential:
The Central Pivot Range is a valuable tool for traders looking to identify critical price levels in the market. By providing a clear framework for identifying potential support and resistance zones, it helps traders make informed decisions about entering and exiting trades. However, it’s important to combine CPR with sound risk management and additional confirmation through other technical indicators for the best results.
Although no trading tool guarantees success, the CPR, when used effectively and combined with practice, can significantly enhance a trader’s ability to navigate market fluctuations.
