Point and Figure (PnF) ChartThis is live and non-repainting Point and Figure Charting tool. The tool has it’s own P&F engine and not using integrated function of Trading View.
Point and Figure method is over 150 years old. It consist of columns that represent filtered price movements. Time is not a factor on P&F chart but as you can see with this script P&F chart created on time chart.
P&F chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify.
If you are new to Point & Figure Chart then you better get some information about it before using this tool. There are very good web sites and books. Please PM me if you need help about resources.
Options in the Script
Box size is one of the most important part of Point and Figure Charting. Chart price movement sensitivity is determined by the Point and Figure scale. Large box sizes see little movement across a specific price region, small box sizes see greater price movement on P&F chart. There are four different box scaling with this tool: Traditional, Percentage, Dynamic (ATR), or User-Defined
4 different methods for Box size can be used in this tool.
User Defined: The box size is set by user. A larger box size will result in more filtered price movements and fewer reversals. A smaller box size will result in less filtered price movements and more reversals.
ATR: Box size is dynamically calculated by using ATR, default period is 20.
Percentage: uses box sizes that are a fixed percentage of the stock's price. If percentage is 1 and stock’s price is $100 then box size will be $1
Traditional: uses a predefined table of price ranges to determine what the box size should be.
Price Range Box Size
Under 0.25 0.0625
0.25 to 1.00 0.125
1.00 to 5.00 0.25
5.00 to 20.00 0.50
20.00 to 100 1.0
100 to 200 2.0
200 to 500 4.0
500 to 1000 5.0
1000 to 25000 50.0
25000 and up 500.0
Default value is “ATR”, you may use one of these scaling method that suits your trading strategy.
If ATR or Percentage is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and box size (ATR/Percentage) is 0.00124 then box size becomes 0.001.
And also while using dynamic box size (ATR or Percentage), box size changes only when closing price changed.
Reversal : It is the number of boxes required to change from a column of Xs to a column of Os or from a column of Os to a column of Xs. Default value is 3 (most used). For example if you choose reversal = 2 then you get the chart similar to Renko chart.
Source: Closing price or High-Low prices can be chosen as data source for P&F charting.
Chart Style: There are 3 options for chart style: “Candle”, “Area” or “Don’t show”.
As Area:
As Candle:
X/O Column Style: it can show all columns from opening price or only last Xs/Os.
Color Theme: different themes exist => Green/Red, Yellow/Blue, White/Yellow, Orange/Blue, Lime/Red, Blue/Red
Show Breakouts is the option to show Breakouts
This tool detects & shows following Breakouts:
Triple Top/Bottom,
Triple Top Ascending,
Triple Bottom Descending,
Simple Buy/Sell (Double Top/Bottom),
Simple Buy With Rising Bottom,
Simple Sell With Declining Top
Catapult bullish/bearish
Show Horizontal Count Targets: Finds the congestion or consolidation pattern and if there is breakout then it calculates the Target by using Horizontal Count method (based on the width of congestion pattern). It shows how many column exist on congestion area. There is no guarantee that prices will reach the target.
Show Vertical Count Targets: When Triple Top/Bottom Breakouts occured the script calculates the target by using Vertical Count Method (based on the length of the column). There is no guarantee that prices will reach the target.
For both methods there is auto target cancellation if price goes below congestion bottom or above congestion top.
trend is calculated by EMA of closing price of the P&F
Whipsaw protection:
Last options are “Show info panel” and Labeling Offset. Script shows current box size, reversal, and recommanded minimum and maximum box size. And also it shows the price level to reverse the column (Xs <-> Os) and the price level to add at least 1 more box to column. This is the option to put these labels 10, 20, 30, 50 or 100 bars away from the last bar. Labeling content and color change according to X/O column.
do not hesitate to comment.
Cerca negli script per "纳斯达克100场外基金+投资回报率"
Technical Analysis - Panel Info//A. Oscillators & B. Moving Averages base on TradingView's Technical Analysis by ThiagoSchmitz
//C.Pivot base on Ultimate Pivot Points Alerts by elbartt
//D. Summary & Panel info by anhnguyen14
Panel Info base on these indicators:
A. Oscillators
1. Rsi (14)
2. Stochastic (14,3,3)
3. CCI (20)
4. ADX (14)
5. AO
6. Momentum (10)
7. MACD (12,26)
8. Stoch RSI (3,3,14,14)
9. %R (14)
10. Bull bear
11. UO (7,14,28)
B. Moving Averages
1. SMA & EMA: 5-10-20-30-50-100-200
2. Ichimoku Cloud - Baseline (26)
3. Hull MA (9)
C. Pivot
1. Traditional
2. Fibonacci
3. Woodie
4. Camarilla
D. Summary
Sum_red=A_red+B_red+C_red
Sum_blue=A_blue+B_blue+C_blue
sell_point=(Sum_red/32)*100
buy_point=(Sum_blue/32)*100
sell =
Sum_red>Sum_blue
and sell_point>50
Strong_sell =
A_red>A_blue
and B_red>B_blue
and C_red>C_blue
and sell_point>50
and not crossunder(sell_point,75)
buy =
Sum_red>Sum_blue
and buy_point>50
Strong_buy =
A_red50
and not crossunder(buy_point,75)
neutral = not sell and not Strong_sell and not buy and not Strong_buy
CCI RiderThis is my thank you to the TradingView community, for the people who are sharing their scripts, which allowed me to learn Pine Script.
So here is my first creation, feel free to experiment, modify and use it as you wish.
It is a CCI(default value is 100, can be changed), combined with an EMA of that CCI(default 21,changeable) that then colors the background according to the strength of the signal(if selected to do so).
To generate strong signals, it also uses Bollinger Bands to prevent whipsaws in high volatility situations.
The best signals are generated when the CCI crosses the limits set by the user (default is 100/-100), and is above/belov its EMA.
Exit signals are indicated, when the CCI crosses its EMA.
Unfortunately in strong trends, this exit signal is sometimes premature, using a 3x resolution of the indicator will improve this, maybe I will implement this in a later version.
I use it mostly in 15min charts and higher, I found in shorter timeframes still a lot of whipsaws, maybe experimenting with different lengths and levels will improve this.
As the Indicator allows the user to experiment with different lenghts and levels, and the colors will change according the setting, I find it a nice tool to search for the best mixture for different securities and timeframes.
See below an example of a nice signal.
I do suggest to use it in combination with other indicators.
Yield Curve Version 2.55.2Welcome to Yield Curve Version 2.55.2
US10Y-US02Y
* Please read description to help understand the information displayed.
* NOTE - This script requires 1 real time update before accurate information is displayed, therefore WILL NOT display the correct information if the Bond Market is Closed over the Weekend.
* NOTE - When values are changed Via Input setting they do take a bit to display based off all the information that is required to display this script.
**FEATURES**
* Input Features let you view the information the way YOU like via Input Settings
* Displays Current Version Title - Toggleable On/Off via Input Settings - Default On
* Plots the Yield Curve of the Bonds listed (Middle Green and Red Line)
* Displays the Spread for each Bond (Top Green and Red Labels) - Toggleable On/Off via Input Settings - Change Size via Input Settings - Default On
* Displays the current Yield for each Bond (Bottom Green and Red Labels) - Toggleable On/Off via Input Settings - Change Size via Input Settings - Default On - Large Size
* Plots the Average of the Entire Yield Curve (BLUE Line within the Yield Curve) - Toggleable On/Off via Input Settings - Default On
* Displays messages based off Yield Inversions (Orange Text) - Toggleable On/Off via Input Settings - Default On if Applicable
* Displays 2 10 Inversion Warning Message (Orange Text) - Toggleable On/Off via Input Settings - Default On if Applicable
* Plots Column Data at the Bottom that tries to help determine the Stability of the Yield Curve (More information Below about Stability) - Toggleable On/Off via Input Settings - Default On
* Plots the 7,20 and 100 SMA of the STABILITY MAX OVERLOAD (More information Below about Stability Max Overload) - Toggleable On/Off via Input Settings - Default On for 100 SMA , 20 SMA and 7 SMA
* Ability to Display Indicator Name and Value via Input Settings - Default On - Displays Stability Max Overload SMA Labels. Toggleable to Non SMA Values. See Below.
**Bottom Columns are all about STABILITY**
* I have tried to come up with an algorithm that helps understand the Stability of the Yield Curve. There are 3 Sections to the Bottom Columns.
* Section 1 - STABILITY (Displayed as the lightest Green or Red Column) Values range from 0 to 1 where 1 equals the MOST UNSTABLE Curve and 0 equals the MOST STABLE Curve
* Section 2 - STABILITY OVERLOAD (Displayed just above the Stability Column a shade darker Green or Red Column)
* Section 3 - STABILITY MAX OVERLOAD (Displayed just above the Stability Overload Column a shade darker Green or Red Column)
What this section tries to do is help understand the Stability of the Curve based on the inversions data. Lower values represent a MORE STABLE curve. If the Yield Curve currently has 0 Inversions all Stability factors should equal 0 and therefore not plot any lower columns. As the Yield Curve becomes more inverted each section represents a value based off that data. GREEN columns represent a MORE Stable Curve from the resolution prior and vise versa.
(S SO SMO)
STABILITY - tests the current Stability of the Curve itself again ranging from 0 to 1 where 0 equals the MOST Stable Curve and 1 equals the MOST Unstable Curve.
STABILIY OVERLOAD - adds a value to STABLITY based off STABILITY itself.
STABILITY MAX OVERLOAD - adds the Entire value to STABILITY derived again from STABILITY.
This section also allows us to see the 7,20 and 100 SMA of the STABILITY MAX OVERLOAD which should always be the GREATEST of ALL STABILTY VALUES.
*Indicator Labels How to use*
Indicator Labels by default are turned On and will display Name and Value Labels for Stability Max Overload SMA values. To switch to (S SO SMO) Labels, toggle "Indicator Labels / SMO SMA Labels", via Input Settings. This button allows you to switch between the two Indicator Label Display options. You must have "Indicators" turned On to view the Labels and therefore is turned On by Default. To turn all of the Indicator Labels Off, simply disable "Indicators" via Input Settings.
Remember - All information displayed can be tuned On or Off besides the Curve itself. There are also other Features Accessible Via the Input Settings.
I will continue to update this script as there is more information I would like to gather and display!
I hope you enjoy,
OpptionsOnly
Ultimate Moving Average Package (17 MA's)Included is the:
VWAP
Current time frame 10 EMA
Current time frame 20 EMA
Current time frame 50 EMA
Current time frame 10 SMA
Current time frame 20 SMA
Current time frame 50 SMA
Daily 10 EMA
Daily 20 EMA
Daily 50 EMA
Daily 50 SMA
Daily 100 SMA
Daily 200 SMA
Weekly 100 SMA
Weekly 200 SMA
Monthly 100 SMA
Monthly 200 SMA
All Daily/Weekly/Monthly MA's can be seen on intraday charts. Current time frame MA's change depending on your time frame. Obviously you dont need all 17 on your chart but you can pick the ones you like and disable the rest.
Bilateral Stochastic Oscillator - For The Sake Of EfficiencyIntroduction
The stochastic oscillator is a feature scaling method commonly used in technical analysis, this method is the same as the running min-max normalization method except that the stochastic oscillator is in a range of (0,100) while min-max normalization is in a range of (0,1). The stochastic oscillator in itself is efficient since it tell's us when the price reached its highest/lowest or crossed this average, however there could be ways to further develop the stochastic oscillator, this is why i propose this new indicator that aim to show all the information a classical stochastic oscillator would give with some additional features.
Min-Max Derivation
The min-max normalization of the price is calculated as follow : (price - min)/(max - min) , this calculation is efficient but there is alternates forms such as :
price - (max - min) - min/(max - min)
This alternate form is the one i chosen to make the indicator except that both range (max - min) are smoothed with a simple moving average, there are also additional modifications that you can see on the code.
The Indicator
The indicator return two main lines, in blue the bull line who show the buying force and in red the bear line who show the selling force.
An orange line show the signal line who represent the moving average of the max(bull,bear), this line aim to show possible exit/reversals points for the current trend.
Length control the highest/lowest period as well as the smoothing amount, signal length control the moving average period of the signal line, the pre-filtering setting indicate which smoothing method will be used to smooth the input source before applying normalization.
The default pre-filtering method is the sma.
The ema method is slightly faster as you can see above.
The triangular moving average is the moving average of another moving average, the impulse response of this filter is a triangular function hence its name. This moving average is really smooth.
The lsma or least squares moving average is the fastest moving average used in this indicator, this filter try to best fit a linear function to the data in a certain window by using the least squares method.
No filtering will use the source price without prior smoothing for the indicator calculation.
Relationship With The Stochastic Oscillator
The crosses between the bull and bear line mean that the stochastic oscillator crossed the 50 level. When the Bull line is equal to 0 this mean that the stochastic oscillator is equal to 0 while a bear line equal to 0 mean a stochastic oscillator equal to 100.
The indicator and below a stochastic oscillator of both period 100
Using Levels
Unlike a stochastic oscillator who would clip at the 0 and 100 level the proposed indicator is not heavily constrained in a range like the stochastic oscillator, this mean that you can apply levels to trigger signals
Possible levels could be 1,2,3... even if the indicator rarely go over 3.
Its then possible to create strategies using such levels as support or resistance one.
Conclusion
I've showed a modified stochastic oscillator who aim to show additional information to the user while keeping all the information a classical stochastic oscillator would give. The proposed indicator is no longer constrained in an hard range and posses more liberty to exploit its scale which in return allow to create strategies based on levels.
For pinescript users what you can learn from this is that alternates forms of specific formulas can be extremely interesting to modify, changes can be really surprising so if you are feeling stuck, modifying alternates forms of know indicators can give great results, use tools such as sympy gamma to get alternates forms of formulas.
Thanks for reading !
If you are looking for something or just want to say thanks try to pm me :)
High/Low bandsGives good idea about trend.
In last 100 days the lowest price was this.
In last 100 days the highest price was this.
Price makes new 100 days high! (uptrend)
Chaikin MF% (CMFP) w. Alerts, Bells & Whistles [LucF]This is Chaikin’s Money Flow indicator on a 0-100 scale with buy/sell signals, alerts and other bells & whistles.
It includes:
- a fast EMA (16 periods by default),
- a slow MA (64 periods by default),
- histograms,
- 3 different sorts of crosses,
- big swings identification,
- buy/sell signals on CMFP crossing back from outside user-defined levels,
- buy/sell signals on the slow MA pivots above/below user-defined levels,
- alerts on big swings and buy/sells.
This indicator started with @LazyBear code (VAPI) at:
@cI8DH then changed the scale to 0-100, which I find very useful:
I then added the rest.
The chart above shows both clean and busy versions of the indicator.
Note that the default length is 10 rather than the commonly used 20. I use CMFP in conjunction with VFI and like the fact that it is faster than VFI. The default inputs show the way I normally use this indicator, with the slow MA shown in histogram mode. I find it gives good context to the signal line. Crosses between the two are often useful.
The buy/sell signals aren’t the main attraction of this indicator, and nothing to write home about. Like the big swing markers, I think it’s more realistic to view them as pointers to potentially interesting areas on charts. Their nature makes them more suited to identifying reversals. They certainly aren’t reliable enough to turn this study into a strategy and I normally don’t use them. The levels pre-defined for the buy/sell signals on CMFP are most useful on short intervals. The buy/sell signals on the slow MA pivots work on a more complete range of intervals. Optimization for your specific instruments and intervals will improve their reliability.
As usual when defining alerts, be sure you already have defined proper inputs and that you are on the intended interval, as they will be used when triggering alerts.
3 of SlowStochastics
스토캐스틱 3개를 한번에 볼수 있습니다. 천장과 바닥은 각 100의 위치마다 존재합니다
You can see three slow stochastics at once. The ceiling and floor are located at each 100 (0 - 100 - 200- 300)
Percentage Price Oscillator (PPO)The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price.
Calculations
PPO: {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals as the MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price > 20K) can be compared against the PPO levels of IBM (price < 200) because the PPO “levels” the playing field. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for the MACD.
Limitations
Despite its advantages, the PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Source: Stockcharts
Multiple Moving AveragesThis is really simple. But useful for me as I don't have a paid account. No-pro users can only use 3 indicators at once and because I rely heavily on simple moving averages it can be a real pain.
This one indicator features:
20 MA
50 MA
100 MA
200 MA
which I find are the most useful overall. The 20 and 50 over all time frame but in particular < 1 day, the 100 and 200 at > 4 hr time frames. In general I don't use the 100 MA that much. The daily 200 MA is a critical support for many assets like stocks and cryptos. I'm by no means a pro and if you are learning I recommend becoming familiar with moving averages right at the beginning.
If you want to deactivate some of the lines, you can do it via the indicator's settings icon.
Exponential Moving Average (Set of 3) [Krypt] + 13/34 EMAsI took Krypt's script and essentially added on to it.
the 20/50/100/200 EMAs should be used together as support and resistance as normal.
Wait for price to break 200 EMA
Wait for 50 EMA to cross 200 EMA
Wait for pullback to 50 EMA to open position
20 and 100 EMAs are for extra information about moving support and resistance
and 13/34 EMAs should be used in conjunction
When 13 EMA crosses 34 EMA, open position
When price gets far from 13/34, close position (because price will attempt to revert back to mean)
This is better for scalping and swing trades than the 20/50/100/200 setup.
Twitter: @AzorAhai06
Ichimoku Cloud Score v1.0This script calculates a simple Ichimoku Score based on the signals documented here , with a few additions. Each of the score components can be individually weighted via the script inputs . The output is a plot of the normalized Ichimoku score, in the range of -100 to 100.
This script has been heavily modified from 'Ichimoku Cloud Signal Score v2.0.0 '. Credit to user 'dashed' for the initial implementation.
This has been modified with several refinements:
Clean/Organized Code
Simplified Inputs
Improved Style
Scores normalized to a range (-100, 100)
Bugfixes and Improvements
Script Inputs: i.imgur.com
Volume RatioDefinition:
Volume ratio can be obtained in a similar way to RSI.
Volume Ratio (%) = 100 - 100/(1+vr)
The parameter "vr" is defined as
vr=(A+U/2)/(D+U/2)
A=Total volume of the periods when the price advanced
D=Total volume of the periods when the price declined
U=Total volume of the periods when the price unchanged
After substitution, following expression can be derived and the denominator represents total volume of all periods.
Volume Ratio (%) = 100 x (A+U/2)/(A+D+U)
Notes:
A similar method to interpret RSI can be employed.
1) Overbought level over 70% and oversold level under 30%. These levels need to be adjusted according to the periods, time frames and issues.
2) Bullish picture over 50% line and bearish picture under 50% line.
3) Crossing oversold level to the upside can be taken as a confirmation of bullish reversal. - and vice versa for a bearish reversal.
4) After a long-term bearish market, the increase of volume can happen in the early stage of a bullish market.
5) Buying opportunity can be suggested when the volume ratio is declining and the price is either advancing or leveling off.
CCI with Volume Weighted EMA Here is an attempt to improve on the CCI using a volume weighted ema which is then plugged into the CCI formula.
Use:
The CCI with VW EMA is an oscillator that gives readings between -100 and +100. The usual use is to 'go long' with values over +100 and short on values less than -100.
Another use of this oscillator is a countertrend indicator where one sells at crosses under +100 and buys on crosses over -100.
Multi-Functional Fisher Transform MTF with MACDL TRIGGERWhat this indicator gives you is a true signal when price is exhausted and ready for a fast turnaround. Fisher Transform is set for multi-time frame and also allows the user to change the length. This way a user can compare two or more time spans and lengths to look for these MACDL divergent triggers after a Fisher exhaustion. With so many indicators, it's probably best to merge these indicators and change the Fisher and Trigger colors so you can still have a look at price action (remember to scale right after merger). I've noticed from time to time when you have Fisher 34 100 and 300 up and running on two different time frames such as 5 and 15 min charts, with MACDL triggers on the 100/300 or 34/100 you get a high probability trade trigger. However, there are rare exceptions such as when price moves in a parabolic state up or down for a long period where this indication does not work. Ideally this indicator works best in a sideways market or slow rising/descending moving market.
This indicator was worked on by Glaz, nmike and myself
LazyBear also introduced the MACDL indicator
CCI Crossover AlertThis very simple indicator will give you a blue background where the CCI crossed from below -100 to above -100, and a red background where it crossed from above 100 to below 100.
Dynamic S/R Levels# Complete Parameter Guide
## 1. Lookback Bars (Default: 500)
- **Function**: Number of historical bars the script analyzes to identify levels
- **Example**: If set to 500, the script examines the last 500 candles
- **Increase when**: Trading long-term, searching for old historical levels
- **Decrease when**: Day trading or short-term trading, viewing only recent levels
- **Recommendation**: 200-300 for day trading, 500-1000 for swing trading
## 2. Min Touches (Default: 3)
- **Function**: Minimum number of touches required for a level to be considered valid
- **Example**: If set to 3, a level with only 2 touches will not be displayed
- **Increase (4-5) when**: You want only very strong and confirmed levels
- **Decrease (2) when**: You want to identify potential levels early
- **Recommendation**: 3 is a balanced value - not too loose, not too strict
## 3. Extrema Type (Default: both)
- **Function**: Which type of extrema to identify
- **Options**:
- **min**: Support levels only (pivot lows)
- **max**: Resistance levels only (pivot highs)
- **both**: Both types
- **When to change**:
- In uptrend looking for support only: select "min"
- In downtrend looking for resistance only: select "max"
## 4. Pivot Window (Default: 5)
- **Function**: How many bars on each side are required to confirm a pivot
- **Technical explanation**: pivot low = price lower than 5 bars before it and 5 bars after it
- **Increase (7-10) when**:
- More significant extrema needed
- Less noise, fewer levels
- Good for higher timeframes
- **Decrease (3-4) when**:
- More sensitivity needed
- More levels wanted
- Good for scalping
- **Important**: Higher value = quality over quantity
## 5. Clustering Sensitivity % (Default: 0.5%)
- **Function**: Percentage deviation allowed to group touches into the same level
- **Example**: If level at $100 and sensitivity 0.5%, touches between $99.5-$100.5 count as same level
- **Increase (1-2%) when**:
- Volatile assets (crypto, small stocks)
- More consolidation of nearby levels
- Fewer levels on chart
- **Decrease (0.2-0.3%) when**:
- Stable assets (indices, forex majors)
- Higher precision needed
- Separation between close levels
- **Recommendation**: Start at 0.5% and adjust per instrument
## 6. Max Levels to Show (Default: 10)
- **Function**: Maximum number of support/resistance lines displayed on chart
- **Selection criteria**: Script prioritizes levels by:
1. Number of touches (more = stronger)
2. Price spread (tighter = more accurate)
3. Recency (most recent touch closer to present)
- **Low value (5-10)**: Clean chart with only strongest levels
- **High value (20-50)**: More options, including weaker levels
## 7. Min Bar Separation (Default: 5)
- **Function**: Minimum distance in bars between two touches of the same type (min or max)
- **Why important**: Prevents double-counting the same extremum
- **Example**: If pivot low at bar 100 and another at bar 103, only one counts
- **Increase (10-20) when**:
- Lower timeframes with much noise
- Avoiding false consolidation
- **Decrease (2-3) when**:
- Higher timeframes
- Identifying quick movements
## 8. Alert Proximity % (Default: 1%)
- **Function**: Distance from level at which to trigger alert
- **Example**: Level at $100, proximity 1% = alert between $99-$101
- **Increase (2-3%) when**:
- Earlier alerts wanted
- More preparation time needed
- May create false alerts
- **Decrease (0.5%) when**:
- More precise alerts wanted
- Stronger confirmation needed
- Less reaction time
- **Recommendation**: 1% works well for most cases
## 9. Show Price Bands (Default: true)
- **Function**: Displays zone around level instead of just a line
- **Zone size**: Plus/minus Clustering Sensitivity %
- **Why useful**:
- Levels are never exact lines
- Zone better represents reality
- Helps identify entries and exits within zone
- **Off**: Cleaner chart with only lines
## 10. Show Info Table (Default: true)
- **Function**: Displays information table in chart corner
- **Table contents**:
- Type: S (Support) / R (Resistance) / N (Neutral)
- Price: Level price
- Touches: Number of touches
- Bars Ago: How many bars since last touch
- **Off**: If you know the levels and want a clean chart
## Recommended Settings by Trading Style:
### Day Trading (Intraday)
```
Lookback Bars: 200-300
Min Touches: 2-3
Pivot Window: 3-5
Sensitivity: 0.3-0.5%
Max Levels: 5-8
```
### Swing Trading (Days-Weeks)
```
Lookback Bars: 500-800
Min Touches: 3-4
Pivot Window: 5-7
Sensitivity: 0.5-1%
Max Levels: 10-15
```
### Position Trading (Months)
```
Lookback Bars: 1000-2000
Min Touches: 4-5
Pivot Window: 7-10
Sensitivity: 1-2%
Max Levels: 8-12
```
**Important tip**: Start with default values and adjust gradually based on the asset and results.
Historical Matrix Analyzer [PhenLabs]📊Historical Matrix Analyzer
Version: PineScriptv6
📌Description
The Historical Matrix Analyzer is an advanced probabilistic trading tool that transforms technical analysis into a data-driven decision support system. By creating a comprehensive 56-cell matrix that tracks every combination of RSI states and multi-indicator conditions, this indicator reveals which market patterns have historically led to profitable outcomes and which have not.
At its core, the indicator continuously monitors seven distinct RSI states (ranging from Extreme Oversold to Extreme Overbought) and eight unique indicator combinations (MACD direction, volume levels, and price momentum). For each of these 56 possible market states, the system calculates average forward returns, win rates, and occurrence counts based on your configurable lookback period. The result is a color-coded probability matrix that shows you exactly where you stand in the historical performance landscape.
The standout feature is the Current State Panel, which provides instant clarity on your active market conditions. This panel displays signal strength classifications (from Strong Bullish to Strong Bearish), the average return percentage for similar past occurrences, an estimated win rate using Bayesian smoothing to prevent small-sample distortions, and a confidence level indicator that warns you when insufficient data exists for reliable conclusions.
🚀Points of Innovation
Multi-dimensional state classification combining 7 RSI levels with 8 indicator combinations for 56 unique trackable market conditions
Bayesian win rate estimation with adjustable smoothing strength to provide stable probability estimates even with limited historical samples
Real-time active cell highlighting with “NOW” marker that visually connects current market conditions to their historical performance data
Configurable color intensity sensitivity allowing traders to adjust heat-map responsiveness from conservative to aggressive visual feedback
Dual-panel display system separating the comprehensive statistics matrix from an easy-to-read current state summary panel
Intelligent confidence scoring that automatically warns traders when occurrence counts fall below reliable thresholds
🔧Core Components
RSI State Classification: Segments RSI readings into 7 distinct zones (Extreme Oversold <20, Oversold 20-30, Weak 30-40, Neutral 40-60, Strong 60-70, Overbought 70-80, Extreme Overbought >80) to capture momentum extremes and transitions
Multi-Indicator Condition Tracking: Simultaneously monitors MACD crossover status (bullish/bearish), volume relative to moving average (high/low), and price direction (rising/falling) creating 8 binary-encoded combinations
Historical Data Storage Arrays: Maintains rolling lookback windows storing RSI states, indicator states, prices, and bar indices for precise forward-return calculations
Forward Performance Calculator: Measures price changes over configurable forward bar periods (1-20 bars) from each historical state, accumulating total returns and win counts per matrix cell
Bayesian Smoothing Engine: Applies statistical prior assumptions (default 50% win rate) weighted by user-defined strength parameter to stabilize estimated win rates when sample sizes are small
Dynamic Color Mapping System: Converts average returns into color-coded heat map with intensity adjusted by sensitivity parameter and transparency modified by confidence levels
🔥Key Features
56-Cell Probability Matrix: Comprehensive grid displaying every possible combination of RSI state and indicator condition, with each cell showing average return percentage, estimated win rate, and occurrence count for complete statistical visibility
Current State Info Panel: Dedicated display showing your exact position in the matrix with signal strength emoji indicators, numerical statistics, and color-coded confidence warnings for immediate situational awareness
Customizable Lookback Period: Adjustable historical window from 50 to 500 bars allowing traders to focus on recent market behavior or capture longer-term pattern stability across different market cycles
Configurable Forward Performance Window: Select target holding periods from 1 to 20 bars ahead to align probability calculations with your trading timeframe, whether day trading or swing trading
Visual Heat Mapping: Color-coded cells transition from red (bearish historical performance) through gray (neutral) to green (bullish performance) with intensity reflecting statistical significance and occurrence frequency
Intelligent Data Filtering: Minimum occurrence threshold (1-10) removes unreliable patterns with insufficient historical samples, displaying gray warning colors for low-confidence cells
Flexible Layout Options: Independent positioning of statistics matrix and info panel to any screen corner, accommodating different chart layouts and personal preferences
Tooltip Details: Hover over any matrix cell to see full RSI label, complete indicator status description, precise average return, estimated win rate, and total occurrence count
🎨Visualization
Statistics Matrix Table: A 9-column by 8-row grid with RSI states labeling vertical axis and indicator combinations on horizontal axis, using compact abbreviations (XOverS, OverB, MACD↑, Vol↓, P↑) for space efficiency
Active Cell Indicator: The current market state cell displays “⦿ NOW ⦿” in yellow text with enhanced color saturation to immediately draw attention to relevant historical performance
Signal Strength Visualization: Info panel uses emoji indicators (🔥 Strong Bullish, ✅ Bullish, ↗️ Weak Bullish, ➖ Neutral, ↘️ Weak Bearish, ⛔ Bearish, ❄️ Strong Bearish, ⚠️ Insufficient Data) for rapid interpretation
Histogram Plot: Below the price chart, a green/red histogram displays the current cell’s average return percentage, providing a time-series view of how historical performance changes as market conditions evolve
Color Intensity Scaling: Cell background transparency and saturation dynamically adjust based on both the magnitude of average returns and the occurrence count, ensuring visual emphasis on reliable patterns
Confidence Level Display: Info panel bottom row shows “High Confidence” (green), “Medium Confidence” (orange), or “Low Confidence” (red) based on occurrence counts relative to minimum threshold multipliers
📖Usage Guidelines
RSI Period
Default: 14
Range: 1 to unlimited
Description: Controls the lookback period for RSI momentum calculation. Standard 14-period provides widely-recognized overbought/oversold levels. Decrease for faster, more sensitive RSI reactions suitable for scalping. Increase (21, 28) for smoother, longer-term momentum assessment in swing trading. Changes affect how quickly the indicator moves between the 7 RSI state classifications.
MACD Fast Length
Default: 12
Range: 1 to unlimited
Description: Sets the faster exponential moving average for MACD calculation. Standard 12-period setting works well for daily charts and captures short-term momentum shifts. Decreasing creates more responsive MACD crossovers but increases false signals. Increasing smooths out noise but delays signal generation, affecting the bullish/bearish indicator state classification.
MACD Slow Length
Default: 26
Range: 1 to unlimited
Description: Defines the slower exponential moving average for MACD calculation. Traditional 26-period setting balances trend identification with responsiveness. Must be greater than Fast Length. Wider spread between fast and slow increases MACD sensitivity to trend changes, impacting the frequency of indicator state transitions in the matrix.
MACD Signal Length
Default: 9
Range: 1 to unlimited
Description: Smoothing period for the MACD signal line that triggers bullish/bearish state changes. Standard 9-period provides reliable crossover signals. Shorter values create more frequent state changes and earlier signals but with more whipsaws. Longer values produce more confirmed, stable signals but with increased lag in detecting momentum shifts.
Volume MA Period
Default: 20
Range: 1 to unlimited
Description: Lookback period for volume moving average used to classify volume as “high” or “low” in indicator state combinations. 20-period default captures typical monthly trading patterns. Shorter periods (10-15) make volume classification more reactive to recent spikes. Longer periods (30-50) require more sustained volume changes to trigger state classification shifts.
Statistics Lookback Period
Default: 200
Range: 50 to 500
Description: Number of historical bars used to calculate matrix statistics. 200 bars provides substantial data for reliable patterns while remaining responsive to regime changes. Lower values (50-100) emphasize recent market behavior and adapt quickly but may produce volatile statistics. Higher values (300-500) capture long-term patterns with stable statistics but slower adaptation to changing market dynamics.
Forward Performance Bars
Default: 5
Range: 1 to 20
Description: Number of bars ahead used to calculate forward returns from each historical state occurrence. 5-bar default suits intraday to short-term swing trading (5 hours on hourly charts, 1 week on daily charts). Lower values (1-3) target short-term momentum trades. Higher values (10-20) align with position trading and longer-term pattern exploitation.
Color Intensity Sensitivity
Default: 2.0
Range: 0.5 to 5.0, step 0.5
Description: Amplifies or dampens the color intensity response to average return magnitudes in the matrix heat map. 2.0 default provides balanced visual emphasis. Lower values (0.5-1.0) create subtle coloring requiring larger returns for full saturation, useful for volatile instruments. Higher values (3.0-5.0) produce vivid colors from smaller returns, highlighting subtle edges in range-bound markets.
Minimum Occurrences for Coloring
Default: 3
Range: 1 to 10
Description: Required minimum sample size before applying color-coded performance to matrix cells. Cells with fewer occurrences display gray “insufficient data” warning. 3-occurrence default filters out rare patterns. Lower threshold (1-2) shows more data but includes unreliable single-event statistics. Higher thresholds (5-10) ensure only well-established patterns receive visual emphasis.
Table Position
Default: top_right
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the 56-cell statistics matrix table. Position to avoid overlapping critical price action or other indicators on your chart. Consider chart orientation and candlestick density when selecting optimal placement.
Show Current State Panel
Default: true
Options: true, false
Description: Toggle visibility of the dedicated current state information panel. When enabled, displays signal strength, RSI value, indicator status, average return, estimated win rate, and confidence level for active market conditions. Disable to declutter charts when only the matrix table is needed.
Info Panel Position
Default: bottom_left
Options: top_left, top_right, bottom_left, bottom_right
Description: Screen location for the current state information panel (when enabled). Position independently from statistics matrix to optimize chart real estate. Typically placed opposite the matrix table for balanced visual layout.
Win Rate Smoothing Strength
Default: 5
Range: 1 to 20
Description: Controls Bayesian prior weighting for estimated win rate calculations. Acts as virtual sample size assuming 50% win rate baseline. Default 5 provides moderate smoothing preventing extreme win rate estimates from small samples. Lower values (1-3) reduce smoothing effect, allowing win rates to reflect raw data more directly. Higher values (10-20) increase conservatism, pulling win rate estimates toward 50% until substantial evidence accumulates.
✅Best Use Cases
Pattern-based discretionary trading where you want historical confirmation before entering setups that “look good” based on current technical alignment
Swing trading with holding periods matching your forward performance bar setting, using high-confidence bullish cells as entry filters
Risk assessment and position sizing, allocating larger size to trades originating from cells with strong positive average returns and high estimated win rates
Market regime identification by observing which RSI states and indicator combinations are currently producing the most reliable historical patterns
Backtesting validation by comparing your manual strategy signals against the historical performance of the corresponding matrix cells
Educational tool for developing intuition about which technical condition combinations have actually worked versus those that feel right but lack historical evidence
⚠️Limitations
Historical patterns do not guarantee future performance, especially during unprecedented market events or regime changes not represented in the lookback period
Small sample sizes (low occurrence counts) produce unreliable statistics despite Bayesian smoothing, requiring caution when acting on low-confidence cells
Matrix statistics lag behind rapidly changing market conditions, as the lookback period must accumulate new state occurrences before updating performance data
Forward return calculations use fixed bar periods that may not align with actual trade exit timing, support/resistance levels, or volatility-adjusted profit targets
💡What Makes This Unique
Multi-Dimensional State Space: Unlike single-indicator tools, simultaneously tracks 56 distinct market condition combinations providing granular pattern resolution unavailable in traditional technical analysis
Bayesian Statistical Rigor: Implements proper probabilistic smoothing to prevent overconfidence from limited data, a critical feature missing from most pattern recognition tools
Real-Time Contextual Feedback: The “NOW” marker and dedicated info panel instantly connect current market conditions to their historical performance profile, eliminating guesswork
Transparent Occurrence Counts: Displays sample sizes directly in each cell, allowing traders to judge statistical reliability themselves rather than hiding data quality issues
Fully Customizable Analysis Window: Complete control over lookback depth and forward return horizons lets traders align the tool precisely with their trading timeframe and strategy requirements
🔬How It Works
1. State Classification and Encoding
Each bar’s RSI value is evaluated and assigned to one of 7 discrete states based on threshold levels (0: <20, 1: 20-30, 2: 30-40, 3: 40-60, 4: 60-70, 5: 70-80, 6: >80)
Simultaneously, three binary conditions are evaluated: MACD line position relative to signal line, current volume relative to its moving average, and current close relative to previous close
These three binary conditions are combined into a single indicator state integer (0-7) using binary encoding, creating 8 possible indicator combinations
The RSI state and indicator state are stored together, defining one of 56 possible market condition cells in the matrix
2. Historical Data Accumulation
As each bar completes, the current state classification, closing price, and bar index are stored in rolling arrays maintained at the size specified by the lookback period
When the arrays reach capacity, the oldest data point is removed and the newest added, creating a sliding historical window
This continuous process builds a comprehensive database of past market conditions and their subsequent price movements
3. Forward Return Calculation and Statistics Update
On each bar, the indicator looks back through the stored historical data to find bars where sufficient forward bars exist to measure outcomes
For each historical occurrence, the price change from that bar to the bar N periods ahead (where N is the forward performance bars setting) is calculated as a percentage return
This percentage return is added to the cumulative return total for the specific matrix cell corresponding to that historical bar’s state classification
Occurrence counts are incremented, and wins are tallied for positive returns, building comprehensive statistics for each of the 56 cells
The Bayesian smoothing formula combines these raw statistics with prior assumptions (neutral 50% win rate) weighted by the smoothing strength parameter to produce estimated win rates that remain stable even with small samples
💡Note:
The Historical Matrix Analyzer is designed as a decision support tool, not a standalone trading system. Best results come from using it to validate discretionary trade ideas or filter systematic strategy signals. Always combine matrix insights with proper risk management, position sizing rules, and awareness of broader market context. The estimated win rate feature uses Bayesian statistics specifically to prevent false confidence from limited data, but no amount of smoothing can create reliable predictions from fundamentally insufficient sample sizes. Focus on high-confidence cells (green-colored confidence indicators) with occurrence counts well above your minimum threshold for the most actionable insights.
Fair Value Lead-Lag Model [BackQuant]Fair Value Lead-Lag Model
A cross-asset model that estimates where price "should" be relative to a chosen reference series, then tracks the deviation as a normalized oscillator. It helps you answer two questions: 1) is the asset rich or cheap vs its driver, and 2) is the driver leading or lagging price over the next N bars.
Concept in one paragraph
Many assets co-move with a macro or sector driver. Think BTC vs DXY, gold vs real yields, a stock vs its sector ETF. This tool builds a rolling fair value of the charted asset from a reference series and shows how far price is above or below that fair value in standard deviation units. You can shift the reference forward or backward to test who leads whom, then use the deviation and its bands to structure mean-reversion or trend-following ideas.
What the model does
Reference mapping : Pulls a reference symbol at a chosen timeframe, with an optional lead or lag in bars to test causality.
Fair value engine : Converts the reference into a synthetic fair value of the chart using one of four methods:
Ratio : price/ref with a rolling average ratio. Good when the relationship is proportional.
Spread : price minus ref with a rolling average spread. Good when the relationship is additive.
Z-Score : normalizes both series, aligns on standardized units, then re-projects to price space. Good when scale drifts.
Beta-Adjusted : rolling regression style. Uses covariance and variance to compute beta, then builds a fair value = mean(price) + beta * (ref − mean(ref)).
Deviation and bands : Computes a z-scored deviation of price vs fair value and plots sigma bands (±1, ±2, ±3) around the fair value line on the chart.
Correlation context : Shows rolling correlation so you can judge if deviations are meaningful or just noise when co-movement is weak.
Visuals :
Fair value line on price chart with sigma envelopes.
Deviation as a column oscillator and optional line.
Threshold shading beyond user-set upper and lower levels.
Summary table with reference, deviation, status, correlation, and method.
Why this is useful
Mean reversion framework : When correlation is healthy and deviation stretches beyond your sigma threshold, probability favors reversion toward fair value. This is classic pairs logic adapted to a driver and a target.
Trend confirmation : If price rides the fair value line and deviation stays modest while correlation is positive, it supports trend persistence. Pullbacks to negative deviation in an uptrend can be buyable.
Lead-lag discovery : Shift the reference forward by +N bars. If correlation improves, the reference tends to lead. Shift backward for the reverse. Use the best setting for planning early entries or hedges.
Regime detection : Large persistent deviations with falling correlation hint at regime change. The relationship you relied on may be breaking down, so reduce confidence or switch methods.
How to use it step by step
Pick a sensible reference : Choose a macro, index, currency, or sector driver that logically explains the asset’s moves. Example: gold with DXY, a semiconductor stock with SOXX.
Test lead-lag : Nudge Lead/Lag Periods to small positive values like +1 to +5 to see if the reference leads. If correlation improves, keep that offset. If correlation worsens, try a small negative value or zero.
Select a method :
Start with Beta-Adjusted when the relationship is approximately linear with drift.
Use Ratio if the assets usually move in proportional terms.
Use Spread when they trade around a level difference.
Use Z-Score when scales wander or volatility regimes shift.
Tune windows :
Rolling Window controls how quickly fair value adapts. Shorter equals faster but noisier.
Normalization Period controls how deviations are standardized. Longer equals stabler sigma sizing.
Correlation Length controls how co-movement is measured. Keep it near the fair value window.
Trade the edges :
Mean reversion idea : Wait for deviation beyond your Upper or Lower Threshold with positive correlation. Fade back toward fair value. Exit at the fair value line or the next inner sigma band.
Trend idea : In an uptrend, buy pullbacks when deviation dips negative but correlation remains healthy. In a downtrend, sell bounces when deviation spikes positive.
Read the table : Deviation shows how many sigmas you are from fair value. Status tells you overvalued or undervalued. Correlation color hints confidence. Method tells you the projection style used.
Reading the display
Fair value line on price chart: the model’s estimate of where price should trade given the reference, updated each bar.
Sigma bands around fair value: a quick sense of residual volatility. Reversions often target inner bands first.
Deviation oscillator : above zero means rich vs fair value, below zero means cheap. Color bins intensify with distance.
Correlation line (optional): scale is folded to match thresholds. Higher values increase trust in deviations.
Parameter tips
Start with Rolling Window 20 to 30, Normalization Period 100, Correlation Length 50.
Upper and Lower Threshold at ±2.0 are classic. Tighten to ±1.5 for more signals or widen to ±2.5 to focus on outliers.
When correlation drifts below about 0.3, treat deviations with caution. Consider switching method or reference.
If the fair value line whipsaws, increase Rolling Window or move to Beta-Adjusted which tends to be smoother.
Playbook examples
Pairs-style reversion : Asset is +2.3 sigma rich vs reference, correlation 0.65, trend flat. Short the deviation back toward fair value. Cover near the fair value line or +1 sigma.
Pro-trend pullback : Uptrend with correlation 0.7. Deviation dips to −1.2 sigma while price sits near the −1 sigma band. Buy the dip, target the fair value line, trail if the line is rising.
Lead-lag timing : Reference leads by +3 bars with improved correlation. Use reference swings as early cues to anticipate deviation turns on the target.
Caveats
The model assumes a stable relationship over the chosen windows. Structural breaks, policy shocks, and index rebalances can invalidate recent history.
Correlation is descriptive, not causal. A strong correlation does not guarantee future convergence.
Do not force trades when the reference has low liquidity or mismatched hours. Use a reference timeframe that captures real overlap.
Bottom line
This tool turns a loose cross-asset intuition into a quantified, visual fair value map. It gives you a consistent way to find rich or cheap conditions, time mean-reversion toward a statistically grounded target, and confirm or fade trends when the driver agrees.
ATR-Normalized MACD w/ Visual BackgroundChatGPT said:
Absolutely! Let’s break down the YON MACD indicator in detail so you understand what it does, how it works, and how to use it.
1. Purpose
The YON MACD is a volatility-adjusted version of the classic MACD. Instead of just using EMA differences, it normalizes the MACD by the Average True Range (ATR), which means:
High-volatility markets → the MACD signal is scaled down.
Low-volatility markets → the MACD signal is scaled up.
This gives a more consistent momentum signal across different market conditions, avoiding false spikes during high volatility.
2. Components
a. Fast and Slow EMAs
fastEMA → Typically 12-period EMA of price.
slowEMA → Typically 26-period EMA of price.
The difference between them measures short-term momentum.
b. ATR Normalization
atr → Average True Range over a specified period (default 26).
Formula:
YON MACD=fastEMA - slowEMAATR×100
YON MACD=
ATR
fastEMA - slowEMA
×100
This adjusts the MACD for market volatility.
c. Signal Line
EMA of the YON MACD (default 9 periods).
Acts like a trigger line for crossovers.
d. Histogram
hist = YON MACD - Signal Line
Visualizes divergence: how far the MACD is from the signal line.
Positive histogram → bullish momentum, negative → bearish momentum.
3. Visual Features
Plot Lines
YON MACD → colored green (rising), red (falling), gray (unchanged).
Signal line → always blue.
Histogram → columns: green (positive), red (negative).
Background Coloring
Green → MACD rising + histogram positive (bullish momentum).
Red → MACD falling + histogram negative (bearish momentum).
Yellow/Orange → histogram flips (early momentum change).
This makes trend and momentum immediately visible without having to study the panel in detail.
4. Alerts
MACD Cross Alerts
YON MACD crosses above the signal → potential buy.
YON MACD crosses below the signal → potential sell.
Histogram Flip Alerts
Histogram flips from negative → positive → early bullish signal.
Histogram flips from positive → negative → early bearish signal.
This allows automation or notifications for momentum changes.
5. How to Use
Trend Confirmation
Green background + MACD above signal → trend is bullish.
Red background + MACD below signal → trend is bearish.
Entry/Exit Signals
Buy: MACD crosses above signal or histogram flips positive.
Sell: MACD crosses below signal or histogram flips negative.
Volatility Adjustment
Since the MACD is ATR-normalized, it avoids overreacting in volatile conditions and highlights true momentum shifts.
Summary
The YON MACD is a trend-following and momentum indicator with:
Volatility normalization (ATR)
MACD cross signals
Histogram divergence visualization
Background colors for instant momentum reading
Alerts for crossovers and early momentum flips
It’s a powerful all-in-one momentum tool that can work for day trading, swing trading, or even longer-term analysis.
2 Bandas de Bollinguer (10-20) + 4 EMA + 2 SMA 2 BB (10-20) + 4 EMA (35-50-100-200) + 2 SMA (75-100) configurable
Ripster: DTR/ATR + SMA Div + RVOL🧭 Overview
The indicator combines three major analytical tools into one TradingView Pine v6 script — designed for clean, at-a-glance insight into range, divergence, and volume activity.
It shows:
DTR vs ATR Table – current Daily True Range compared to Average True Range.
SMA Price Divergence + EMA Signal – a histogram with color-coded momentum bands.
RVOL Table + Candle Coloring + Change Labels – relative-volume analysis with visual cues on the chart.
Short title: ripcombo
Runs on chart overlay (no separate pane).
📊 1. DTR vs ATR Table
Compares today’s price range (High-Low) to the average true range over a selectable length.
Supports multiple smoothing methods: EMA, RMA, SMA, WMA.
Table position and text size are configurable.
Color logic:
🟢 ≤ 70 % of ATR → low volatility
🟡 70–90 % → average
🔴 ≥ 90 % → expanded range
📈 2. SMA Divergence + EMA Signal
Computes fast (14 SMA) and slow (30 SMA) divergences of price.
Plots two histograms plus an EMA signal line of the slow divergence.
Visuals:
Columns shaded by transparency for clarity.
Rising EMA → lime line (up momentum).
Falling EMA → red line (down momentum).
Optional upper/lower bands and zero line provide quick overbought/oversold zones.
🔥 3. RVOL (Relative Volume)
Adds powerful volume-based context:
a. Table Display
Shows:
Candle Volume
RVOL (Now)
RVOL (Prev)
Δ RVOL (change Now − Prev)
Colors:
🔴 > 200 % (very high volume)
🟠 100–200 % (high volume)
🟡 < 100 % (normal/low volume)
Δ column is green ▲ for increase, red ▼ for decrease.
b. Candle Coloring (optional)
Colors price candles themselves by current RVOL threshold so high-volume candles visually stand out.
c. Last-Bar Label (optional)
Prints a compact label on the latest candle showing:
RVOL: ### % Δ: ▲/▼## %
so you can instantly see the current volume strength and how it changed from the previous bar.
⚙️ User Settings
All major elements are toggle-controlled:
Enable/disable ATR, Divergence, or RVOL sections.
Choose table positions (top/middle/bottom × left/center/right).
Select text sizes, smoothing types, color modes, and visual transparency.
Candle coloring + label visibility are optional.
🧠 At a Glance
Component Purpose Key Visuals
DTR vs ATR Measures volatility expansion One-cell colored table
SMA Divergence Detects price momentum shifts Columns + EMA line + bands
RVOL Analysis Highlights unusual trading volume Colored table + Δ column + candle colors + label
✅ Result
You get a single on-chart tool that:
Quantifies volatility, momentum, and volume context together.
Highlights strong activity days (ATR & RVOL) in color.
Shows whether current candle’s volume is rising or falling vs the previous.
Perfect for spotting breakouts, reversals, or exhaustion moves without switching indicators.
