Price Cross Time Custom Range Interactive█ OVERVIEW
This indicator was a time-based indicator and intended as educational purpose only based on pine script v5 functions for ta.cross() , ta.crossover() and ta.crossunder() .
I realised that there is some overlap price with the cross functions, hence I integrate them into Custom Range Interactive with value variance and overlap displayed into table.
This was my submission for Pinefest #1 , I decided to share this as public, I may accidentally delete this as long as i keep as private.
█ INSPIRATION
Inspired by design, code and usage of CAGR. Basic usage of custom range / interactive, pretty much explained here . Credits to TradingView.
█ FEATURES
1. Custom Range Interactive
2. Label can be resize and change color.
3. Label show tooltip for price and time.
4. Label can be offset to improve readability.
5. Table can show price variance when any cross is true.
6. Table can show overlap if found crosss is overlap either with crossover and crossunder.
7. Table text color automatically change based on chart background (light / dark mode).
8. Source 2 is drawn as straight line, while Source 1 will draw as label either above line for crossover, below line for crossunder and marked 'X' if crossing with Source 2's line.
9. Cross 'X' label can be offset to improve readability.
10. Both Source 1 and Source 2 can select Open, Close, High and Low, which can be displayed into table.
█ LIMITATIONS
1. Table is limited to intraday timeframe only as time format is not accurate for daily timeframe and above. Example daily timeframe will give result less 1 day from actual date.
2. I did not include other sources such external source or any built in sources such as hl2, hlc3, ohlc4 and hlcc4.
█ CODE EXPLAINATION
I pretty much create custom function with method which returns tuple value.
method crossVariant(float price = na, chart.point ref = na) =>
cross = ta.cross( price, ref.price)
over = ta.crossover( price, ref.price)
under = ta.crossunder(price, ref.price)
Unfortunately, I unable make the labels into array which i plan to return string value by getting the text value from array label, hence i use label.all and add incremental int value as reference.
series label labelCross = na, labelCross.delete()
var int num = 0
if over
num += 1
labelCross := label.new()
if under
num += 1
labelCross := label.new()
if cross
num += 1
labelCross := label.new()
I realised cross value can be overlap with crossover and crossunder, hence I add bool to enable force overlap and add additional bools.
series label labelCross = na, labelCross.delete()
var int num = 0
if forceOverlap
if over
num += 1
labelCross := label.new()
if under
num += 1
labelCross := label.new()
if cross
num += 1
labelCross := label.new()
else
if cross and over
num += 1
labelCross := label.new()
if cross and under
num += 1
labelCross := label.new()
if cross and not over and not under
num += 1
labelCross := label.new()
█ USAGE / EXAMPLES
Cari skrip untuk "N+credit最新动态"
Triple Moving Averages (Gradient, Alarm & Multi TF)Triple Moving Averages
Features:
- 7 Different MA's (RMA, SMA, EMA, 'WMA', HMA, DEMA, EMA)
- Gradient coloring
- Multi timeframe
- Crossover alarm's and alarm delay function
- Forecasting (By removing the last bar in the MA period)
Moving Average to easely identify the trend and trend strength.
Gradient coloring and personal color preferences can be made.
Alert Delay System
When timing is essentially, this helps you get the alarm just in time.
Use it with the triggers ONLY ONCE PER BAR or ONLY ONCE. Then the alarm comes before the close, but you don't have to worry about it triggering just seconds after bar open :)
Default = 15m Recomended for 1h chart
Alarm's
Get the alarms before it's actually crossing or when it crosses
*This is not a selfmade indicator but simply merging from several indicators and added alert delay function and multi timeframe support
// Credits
- BigBitsIO Script : Scripting Tutorial 6 Triple Many Moving Averages Forecasting
- PineCoders Script : Color Gradient Framework PineCoders
NormInvTargetSeekerNormInvTargetSeeker
The NormInvTargetSeeker is a trading tool designed to aid traders in identifying and capitalizing on Distribution and Accumulation zones, highlighting specific price levels that could serve as targets for future price movements. Although the indicator itself is not multi-timeframe, an effective trading strategy might involve signal validation across multiple timeframes.
🔶 USAGE
The indicator identifies Distribution and Accumulation zones, providing potential targets for future price moves.
Traders are encouraged to use these zones as profit targets or potential reversal points.
Confluence Zones
These zones are identified as regions where various factors or levels converge, signaling an increased probability of price reaction.
They can be used to reinforce signals or identify levels where price might encounter significant resistance or support.
🔹 Trading Strategy
First, identify a signal on your primary trading timeframe.
Manually check higher timeframes to ensure the signal aligns with them.
Use the identified zones, whether Distribution or Accumulation, as target zones for your trades.
🔶 Order Blocks
The NormInvTargetSeeker identifies "Order Blocks" by examining a specified number of consecutive candles with a specific condition: the current candle must completely engulf the previous candle. This means that both the high and low of the current candle are higher and lower, respectively, than the high and low of the previous candle, signifying a dominant move in the direction of the current candle.
🔹 Trading Strategy
Target Confirmation: Order Blocks can serve to confirm target points, providing additional validation for identified levels.
Market Insight: They offer crucial insights into whether "big hands" or institutional players are positioned as buyers or sellers in the market.
Traders can use Order Blocks as a means to validate targets or key price levels, observing if the price reacts significantly upon reaching these blocks.
They can also provide insights into the general market direction or underlying market strength by identifying where the major market players are placing their orders.
🔶 SETTINGS
The indicator allows users to adjust various parameters to customize the display and logic of the tool to fit their needs.
🔹 Display Settings
Users can customize the colors and displays of various zones and labels to match their preferences.
🔶 LICENSE AND CREDITS
This work is licensed under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). More information here: creativecommons.org
This indicator utilizes a TypeScript implementation of the Normal Inverse function as a reference, which can be found here : github.com
Special thanks to the authors of the referenced code for providing a foundation upon which this indicator was built.
🔶 UPDATES
Current Version: 1.0.0
For future updates, please check the comment section.
🔶 CONTACT
For any questions or suggestions, please feel free to contact @RickSimpson on TradingView.
[AIO] Multi Collection Moving Averages 140 MA TypesAll In One Multi Collection Moving Averages.
Since signing up 2 years ago, I have been collecting various Сollections.
I decided to get it into a decent shape and make it one of the biggest collections on TV, and maybe the entire internet.
And now I'm sharing my collection with you.
140 Different Types of Moving Averages are waiting for you.
Specifically :
"
AARMA | Adaptive Autonomous Recursive Moving Average
ADMA | Adjusted Moving Average
ADXMA | Average Directional Moving Average
ADXVMA | Average Directional Volatility Moving Average
AHMA | Ahrens Moving Average
ALF | Ehler Adaptive Laguerre Filter
ALMA | Arnaud Legoux Moving Average
ALSMA | Adaptive Least Squares
ALXMA | Alexander Moving Average
AMA | Adaptive Moving Average
ARI | Unknown
ARSI | Adaptive RSI Moving Average
AUF | Auto Filter
AUTL | Auto-Line
BAMA | Bryant Adaptive Moving Average
BFMA | Blackman Filter Moving Average
CMA | Corrected Moving Average
CORMA | Correlation Moving Average
COVEMA | Coefficient of Variation Weighted Exponential Moving Average
COVNA | Coefficient of Variation Weighted Moving Average
CTI | Coral Trend Indicator
DEC | Ehlers Simple Decycler
DEMA | Double EMA Moving Average
DEVS | Ehlers - Deviation Scaled Moving Average
DONEMA | Donchian Extremum Moving Average
DONMA | Donchian Moving Average
DSEMA | Double Smoothed Exponential Moving Average
DSWF | Damped Sine Wave Weighted Filter
DWMA | Double Weighted Moving Average
E2PBF | Ehlers 2-Pole Butterworth Filter
E2SSF | Ehlers 2-Pole Super Smoother Filter
E3PBF | Ehlers 3-Pole Butterworth Filter
E3SSF | Ehlers 3-Pole Super Smoother Filter
EDMA | Exponentially Deviating Moving Average (MZ EDMA)
EDSMA | Ehlers Dynamic Smoothed Moving Average
EEO | Ehlers Modified Elliptic Filter Optimum
EFRAMA | Ehlers Modified Fractal Adaptive Moving Average
EHMA | Exponential Hull Moving Average
EIT | Ehlers Instantaneous Trendline
ELF | Ehler Laguerre filter
EMA | Exponential Moving Average
EMARSI | EMARSI
EPF | Edge Preserving Filter
EPMA | End Point Moving Average
EREA | Ehlers Reverse Exponential Moving Average
ESSF | Ehlers Super Smoother Filter 2-pole
ETMA | Exponential Triangular Moving Average
EVMA | Elastic Volume Weighted Moving Average
FAMA | Following Adaptive Moving Average
FEMA | Fast Exponential Moving Average
FIBWMA | Fibonacci Weighted Moving Average
FLSMA | Fisher Least Squares Moving Average
FRAMA | Ehlers - Fractal Adaptive Moving Average
FX | Fibonacci X Level
GAUS | Ehlers - Gaussian Filter
GHL | Gann High Low
GMA | Gaussian Moving Average
GMMA | Geometric Mean Moving Average
HCF | Hybrid Convolution Filter
HEMA | Holt Exponential Moving Average
HKAMA | Hilbert based Kaufman Adaptive Moving Average
HMA | Harmonic Moving Average
HSMA | Hirashima Sugita Moving Average
HULL | Hull Moving Average
HULLT | Hull Triple Moving Average
HWMA | Henderson Weighted Moving Average
IE2 | Early T3 by Tim Tilson
IIRF | Infinite Impulse Response Filter
ILRS | Integral of Linear Regression Slope
JMA | Jurik Moving Average
KA | Unknown
KAMA | Kaufman Adaptive Moving Average & Apirine Adaptive MA
KIJUN | KIJUN
KIJUN2 | Kijun v2
LAG | Ehlers - Laguerre Filter
LCLSMA | 1LC-LSMA (1 line code lsma with 3 functions)
LEMA | Leader Exponential Moving Average
LLMA | Low-Lag Moving Average
LMA | Leo Moving Average
LP | Unknown
LRL | Linear Regression Line
LSMA | Least Squares Moving Average / Linear Regression Curve
LTB | Unknown
LWMA | Linear Weighted Moving Average
MAMA | MAMA - MESA Adaptive Moving Average
MAVW | Mavilim Weighted Moving Average
MCGD | McGinley Dynamic Moving Average
MF | Modular Filter
MID | Median Moving Average / Percentile Nearest Rank
MNMA | McNicholl Moving Average
MTMA | Unknown
MVSMA | Minimum Variance SMA
NLMA | Non-lag Moving Average
NWMA | Dürschner 3rd Generation Moving Average (New WMA)
PKF | Parametric Kalman Filter
PWMA | Parabolic Weighted Moving Average
QEMA | Quadruple Exponential Moving Average
QMA | Quick Moving Average
REMA | Regularized Exponential Moving Average
REPMA | Repulsion Moving Average
RGEMA | Range Exponential Moving Average
RMA | Welles Wilders Smoothing Moving Average
RMF | Recursive Median Filter
RMTA | Recursive Moving Trend Average
RSMA | Relative Strength Moving Average - based on RSI
RSRMA | Right Sided Ricker MA
RWMA | Regressively Weighted Moving Average
SAMA | Slope Adaptive Moving Average
SFMA | Smoother Filter Moving Average
SMA | Simple Moving Average
SSB | Senkou Span B
SSF | Ehlers - Super Smoother Filter P2
SSMA | Super Smooth Moving Average
STMA | Unknown
SWMA | Self-Weighted Moving Average
SW_MA | Sine-Weighted Moving Average
TEMA | Triple Exponential Moving Average
THMA | Triple Exponential Hull Moving Average
TL | Unknown
TMA | Triangular Moving Average
TPBF | Three-pole Ehlers Butterworth
TRAMA | Trend Regularity Adaptive Moving Average
TSF | True Strength Force
TT3 | Tilson (3rd Degree) Moving Average
VAMA | Volatility Adjusted Moving Average
VAMAF | Volume Adjusted Moving Average Function
VAR | Vector Autoregression Moving Average
VBMA | Variable Moving Average
VHMA | Vertical Horizontal Moving Average
VIDYA | Variable Index Dynamic Average
VMA | Volume Moving Average
VSO | Unknown
VWMA | Volume Weighted Moving Average
WCD | Unknown
WMA | Weighted Moving Average
XEMA | Optimized Exponential Moving Average
ZEMA | Zero Lag Moving Average
ZLDEMA | Zero-Lag Double Exponential Moving Average
ZLEMA | Ehlers - Zero Lag Exponential Moving Average
ZLTEMA | Zero-Lag Triple Exponential Moving Average
ZSMA | Zero-Lag Simple Moving Average
"
Don't forget that you can use any Moving Average not only for the chart but also for any of your indicators without affecting the code as in my example.
But remember that some MAs are not designed to work with anything other than a chart.
All MA and Code lists are sorted strictly alphabetically by short name (A-Z).
Each MA has its own number (ID) by which you can display the Moving Average you need.
Next to the ID selection there are tooltips with short names and their numbers. Use them.
The panel below will help you to read the Name of the selected MA.
Because of the size of the collection I think this is the optimal and most convenient use. Correct me if this is not the case.
Unknown - Some MAs I collected so long ago that I lost the full real name and couldn't find the authors. If you recognize them, please let me know.
I have deliberately simplified all MAs to input just Source and Length.
Because the collection is so large, it would be quite inconvenient and difficult to customize all MA functions (multipliers, offset, etc.).
If you need or like any MA you will still have to take it from my collection for your code.
I tried to leave the basic MA settings inside function in first strings.
I have tried to list most of the authors, but since the bulk of the collection was created a long time ago and was not intended for public publication I could not find all of them.
Some of the features were created from scratch or may have been slightly modified, so please be careful.
If you would like to improve this collection, please write to me in PM.
Also Credits, Likes, Awards, Loves and Thanks to :
@alexgrover
@allanster
@andre_007
@auroagwei
@blackcat1402
@bsharpe
@cheatcountry
@CrackingCryptocurrency
@Duyck
@ErwinBeckers
@everget
@glaz
@gotbeatz26107
@HPotter
@io72signals
@JacobAmos
@JoshuaMcGowan
@KivancOzbilgic
@LazyBear
@loxx
@LuxAlgo
@MightyZinger
@nemozny
@NGBaltic
@peacefulLizard50262
@RicardoSantos
@StalexBot
@ThiagoSchmitz
@TradingView
— 𝐀𝐧𝐝 𝐎𝐭𝐡𝐞𝐫𝐬 !
So just a Big Thank You to everyone who has ever and anywhere shared their codes.
Zigzag Chart Points█ OVERVIEW
This indicator displays zigzag based on high and low using latest pine script version 5 , chart.point which using time, index and price as parameters.
Pretty much a strip down using latest pine script function, without any use of library .
This allow pine script user to have an idea of simplified and cleaner code for zigzag.
█ CREDITS
LonesomeTheBlue
█ FEATURES
1. Label can be show / hide including text can be resized.
2. Hover to label, can see tooltip will show price and time.
3. Tooltip will show date and time for hourly timeframe and below while show date only for day timeframe and above.
█ NOTES
1. I admit that chart.point just made the code much more cleaner and save more time. I previously using user-defined type(UDT) which quite hassle.
2. I have no plan to extend this indicator or include alert just I thinking to explore log.error() and runtime.error() , which I may probably release in other publications.
█ HOW TO USE'
Pretty much similar inside mentioned references, which previously I created.
█ REFERENCES
1. Zigzag Array Experimental
2. Simple Zigzag UDT
3. Zig Zag Ratio Simplified
4. Cyclic RSI High Low With Noise Filter
5. Auto AB=CD 1 to 1 Ratio Experimental
Market Performance TableThe Market Performance Table displays the performance of multiple tickers (up to 5) in a table format. The tickers can be customized by selecting them through the indicator settings.
The indicator calculates various metrics for each ticker, including the 1-day change percentage, whether the price is above the 50, 20, and 10-day simple moving averages (SMA), as well as the relative strength compared to the 10/20 SMA and 20/50 SMA crossovers. It also calculates the price deviation from the 50-day SMA.
The table is displayed on the chart and can be positioned in different locations.
Credits for the idea to @Alex_PrimeTrading ;)
True Range Moving Average Deviation🔶 Overview
The True Range Moving Average Deviation Indicator (TRMAD) is a technical analysis tool that combines elements of price deviation, volatility, and overbought/oversold conditions.
🔶 Key Components
Current price (Close) : most recent closing price of the asset.
Moving Average (MA) : represents a smoothed trendline of the asset's closing prices over a specified period. By default, TRMAD uses the Simple Moving Average (SMA) with a 20-period setting.
Average True Range (ATR) : reflects the average price range between the high and low over a given time frame. By default, TRMAD uses a 14-period ATR setting with a Simple Moving Average (SMA) calculation. ATR quantifies the historical price volatility of the asset, which is crucial for normalizing the price deviation.
🔶 Calculation
(Close - MA) / ATR
🔶 Interpretation
When TRMAD is above +3 ATR , it is often considered an indication that the asset may be overbought, suggesting a potential reversal or correction to the downside.
When TRMAD is below -3 ATR , it is often considered an indication that the asset may be oversold, suggesting a potential reversal or bounce to the upside.
TRMAD values around 0 ATR may indicate a balanced market condition.
🔶 Usage
🔹 Overbought and Oversold Conditions:
TRMAD can help identify overbought and oversold conditions. When TRMAD reaches or exceeds certain user-defined thresholds (e.g., +3 ATR or -3 ATR), it can signal that the asset is in an extreme condition.
Traders can use these extreme conditions to adjust their positions or look for potential reversal opportunities.
🔹 Divergence Analysis:
Traders often analyze divergences between the TRMAD indicator and price movements. For example, if the price is making higher highs while TRMAD is making lower highs (bearish divergence), it could indicate a potential trend reversal.
🔹 Trend Confirmation:
TRMAD can be used in conjunction with other technical indicators to confirm trends. For example, if TRMAD is consistently positive during an uptrend, it can provide confirmation of the trend's strength.
Positive TRMAD : When TRMAD is positive but hasn't reached the overbought threshold (e.g., +3 ATR), it suggests that there is some bullish momentum, but traders may exercise caution and look for other confirming signals before considering a long position.
Negative TRMAD : When TRMAD is negative but hasn't reached the oversold threshold (e.g., -3 ATR), it suggests some bearish sentiment, but traders may want to seek additional confirmation before considering a short position.
🔹 Risk Management:
Traders can use TRMAD as part of their risk management strategy. For instance, if TRMAD suggests that an asset is overbought, a trader might consider tightening their stop-loss orders to manage potential downside risk.
🔶 Credits
The idea about this indicator came from Fabio Figueiredo (Vlad)
[TTI] MarketSmith & IBD Style Model Stock Quarters 📜 ––––HISTORY & CREDITS––––
The MarketSmith & IBD Style Model Stock Quarters another Utility indicator is an original creation by TintinTrading inspired by Investor's Business Daily and William O'Neil style of presenting information. While going through the Model Stocks that IBD has been publishing, I realized that I wanted to see the exam same Quarterly presentation on the time axis in order to compare William O'Neil notes better with my own notes from Tradingview. The script is simple and could help you if you study the CANSLIM methodology.
🦄 –––UNIQUENESS–––
The distinctiveness of this indicator lies in its ability to visually delineate stock quarters directly on the price chart. It serves as a handy tool for traders who adopt a quarterly review of stock performance, in line with MarketSmith and IBD's analysis frameworks.
🛠️ ––––WHAT IT DOES––––
Quarter Marking : Draws a black line at the beginning of each financial quarter (January, April, July, and October).
Quarter Labeling : Places a label at the close of the last month in a quarter, indicating the upcoming quarter with its abbreviation and the last two digits of the year.
💡 ––––HOW TO USE IT––––
👉Installation: Add the indicator to your TradingView chart by searching for " MarketSmith & IBD Style Model Stock Quarters" in the indicator library.
👉Add to New Pane and squash the Pane Length: I add the indicator to a new pane under the price and volume charts and squash the height of the pane so that it looks exactly like the MarketSmith visuals.
👉Visual Cues:
Look for the black lines marking the start of a new quarter.
Observe the labels indicating the upcoming quarter and year, positioned at the close of the last month in a quarter.
👉Interpretation: Use these quarterly markers to align your trading strategies with quarterly performance metrics or to conduct seasonal analysis.
👉Settings: The indicator does not require any user-defined settings, making it straightforward to use.
[TTI] Price confirmation indicator📜 ––––HISTORY & CREDITS––––
The Price Confirmation Indicator is an innovative tool developed by TintinTrading to help his students learn to interpret Price + Volume moves. It is designed to provide traders with a visual cue for price movement confirmation based on both price direction and trading volume. I got the idea from watching Daivd Ryan, how he explains that he looks at volume first before looking at the price of a stock.
🦄 –––UNIQUENESS–––
What sets this indicator apart is its dual analysis approach and easy interpretation: it not only evaluates price movements but also takes trading volume into account. The indicator's color-coded bars are dynamically adjusted based on the volume difference from a 50-day Simple Moving Average (SMA) of the volume. This offers traders an intuitive way to gauge both the market's direction and its strength.
🛠️ ––––WHAT IT DOES––––
The Price Confirmation Indicator performs the following functions:
👉Price Movement: Determines whether each trading day is an 'Up Day' or a 'Down Day' based on the closing price.
👉Volume Analysis: Calculates the 50-day SMA of trading volume and identifies the volume difference in percentage terms.
👉Transparency Adjustment: Dynamically adjusts the transparency of colored bars based on the volume difference.
👉Bar Coloring: Colors the bars blue for 'Up Days' and purple for 'Down Days', with the transparency indicating the strength of the volume.
Transparency Tresholds:
Full color (no transparency 0%) - Volume is greater than 40% compared to the 50DSMA Volume
Strong color (little transparency 20%) - Volume is between 20% and 40% greater than the 50DSMA Volume
Noticable color (moderate transparency 40%) - Volume is between 0% and 20% greater than the 50DSMA Volume
Negligable color (strong transparency 60%) - Volume is light and is less than 50DSMA Volume with less than 20% lower.
Weak color (very strong transparency 80%) - Volume is below 50DSMA, with between 40% and 20% lower.
Very weak color (max transparency 90%) - Volume is below 50DSMA, with between -40% and -80% lower.
Alarming weak color (color is orange) - Volume is noticably light - this generally signals velocity contraction before a breakout.
💡 ––––HOW TO USE IT––––
Installation: Search for " Price Confirmation Indicator" in TradingView’s indicator library and add it to your chart.
Settings:
Price Up Color: Customize the color for 'Up Days'.
Price Down Color: Customize the color for 'Down Days'.
Interpretation:
Blue bars signify 'Up Days', and their transparency indicates the strength of the volume.
Purple bars represent 'Down Days', with transparency again indicating volume strength.
Orange bars signify extremely low volume days.
Volume Transparency: The less transparent the bar, the stronger the volume, aiding in confirming the price direction.
The indicator is a great tool for newer traders to get in the habit of reading Price & Volume together!
[TTI] Closing Range Indicator📜 ––––HISTORY & CREDITS––––
This Pine Script Utility indicator, titled " Closing Range Indicator," is designed and developed by TintinTrading but inspired by the teaching of Investor's Business Daily (IBD) and William O'Neil. It aims to help traders identify the closing range of a given timeframe, either daily or weekly.
🦄 –––UNIQUENESS–––
The unique feature of this indicator lies in its ability to simulate a functionality of Closing Range calculation based on hovering of the mouse over the close. It employs a conditional display that allows the user to set the indicator as 'invisible' without removing it from the chart and hence provides a numerical closing range value when hovering over the indicator.
🛠️ ––––WHAT IT DOES––––
The Closing Range Indicator calculates the closing range of a trading bar in terms of percentages. It computes the difference between the closing price and the low price of the bar, and then divides it by the range of the bar.
A stock that closes on the high would display 100%
A stock that closes on the low would display 0%
Generally, the higher the percentage the more bullish the close but there are exceptions to this rule.
The indicator can operate on two timeframes:
Daily : Computes the closing range based on the daily high, low, and closing prices.
Weekly : Computes the closing range based on the weekly high, low, and closing prices. If you enable the weekly it will show the weekly close on all daily timeframes. Meaning that if the week Closing range is 54.15% on Friday, it will show the value 54.15% for all days prior to Friday from the same week.
The indicator places a label at the close of each bar, with the label's tooltip showing the calculated closing range percentage. I generally hide the label and just reference the tooltip calculation with a a hoover on top of the bar.
💡 ––––HOW TO USE IT––––
Installation: Add the indicator to your TradingView chart by searching for " Closing Range Indicator" in the indicator library.
Reorder: Reorder the indicator so that it sits as the first indicator (even above the price) on the Pane. This will make sure that you always trigger the tooltip functionality.
Go to Settings:
Timeframe: Choose between daily ('D') and weekly ('W') timeframes from the settings.
Visibility: Enable the 'Make Invisible' option if you want the indicator to be hidden.
Interpretation:
A higher percentage indicates that the closing price is closer to the high of the range, signaling bullish sentiment.
A lower percentage indicates bearish sentiment.
Tooltip: Hover over the label to view the closing range in percentage terms.
Default Strategy Template© CN_FX-999
Coded By Christian Nataliano
First Coded In 14/06/2023
Last Edited In 22/06/2023
This Is A Default Strategy Template That Can Make Your Strategy Scripts More Organized With The Benefit Of Having The Same Layouts & Not Needing To Copy Over The Common Codes Such As Displaying Backtest Results, Opening & Closing Trades, Pine Connector Capabilities And A Clean User Input Interface. This Is A Blank Strategy Script So Feel Free To Use It As Your Default Template For Your Future Strategies.
Credits To Some Of The Custom Code In The Scripts To © ZenAndTheArtOfTrading, Especially The Table Data Plotting
Simple Ultimate Oscillator█ OVERVIEW
This indicator as an educational and showcase the usage of user-defined types (UDT) or objects for Ultimate Oscillator.
█ CREDITS
TradingView
█ FEATURES
1. Color of plot is based on contrast color of chart background.
2. Plot fill of overbought and oversold.
3. Support Multi Timeframe.
Simple Ichimoku Kinko Hyo Cloud█ OVERVIEW
This indicator as an educational and showcase the usage of user-defined types or objects (UDT) for Ichimoku Kinko Hyo or Ichimoku Cloud.
█ CREDITS
TradingView
AIR Supertrend (Average Interpercentile Range)Supertrend (ST) is a popular stop loss and trend identification script. The simplicity of seeing a clean trend on a chart makes it attractive, yet it is restricted by only allowing the source, length and multiplier to be adjusted, & these tend to have a limited effect on the properties of the identified trend.
There is a wide variety of interesting ST scripts on TradingView that give the user more control, but none to my knowledge, based on measuring the statistical dispersion of Average Interpercentile Range (AIR).
Two more levels of control:
Normally, ATR Average True Range is used to calculate the range in ST. ATR is initially calculated using RMA to smooth out True Range. This script gives the user the option of changing the MA to some more interesting varieties & modifying their parameters.
The default range setting when you load the indicator on a chart will be AIR.
The real strength of the indicator, however, and the reason I am publishing it, is to release AIR. Play round with the percentile range setting. Lowering it will allow you to stay longer in a trade in a volatile market. Raising it will make it tighter.
For comparison, you can switch back the range setting to ATR and load up RMA to see how the original, classic ST plots.
Alerts are included in this version. Alway use a stop loss.
DISCLAIMER: None of this is financial advice.
Credits to these authors, whose hard work inspired parts of this script:
@ KivancOzbilgic - SuperTrend
@ KioseffTrading - Tillson T3 MA
@ cheatcountry - Hann Window Smoothing
@ mutantdog - Interquartile Range function in his 'Blaze' script
T3 JMA KAMA VWMAEnhancing Trading Performance with T3 JMA KAMA VWMA Indicator
Introduction
In the dynamic world of trading, staying ahead of market trends and capitalizing on volume-driven opportunities can greatly influence trading performance. To address this, we have developed the T3 JMA KAMA VWMA Indicator, an innovative tool that modifies the traditional Volume Weighted Moving Average (VWMA) formula to increase responsiveness and exploit high-volume market conditions for optimal position entry. This article delves into the idea behind this modification and how it can benefit traders seeking to gain an edge in the market.
The Idea Behind the Modification
The core concept behind modifying the VWMA formula is to leverage more responsive moving averages (MAs) that align with high-volume market activity. Traditional VWMA utilizes the Simple Moving Average (SMA) as the basis for calculating the weighted average. While the SMA is effective in providing a smoothed perspective of price movements, it may lack the desired responsiveness to capitalize on short-term volume-driven opportunities.
To address this limitation, our T3 JMA KAMA VWMA Indicator incorporates three advanced moving averages: T3, JMA, and KAMA. These MAs offer enhanced responsiveness, allowing traders to react swiftly to changing market conditions influenced by volume.
T3 (T3 New and T3 Normal):
The T3 moving average, one of the components of our indicator, applies a proprietary algorithm that provides smoother and more responsive trend signals. By utilizing T3, we ensure that the VWMA calculation aligns with the dynamic nature of high-volume markets, enabling traders to capture price movements accurately.
JMA (Jurik Moving Average):
The JMA component further enhances the indicator's responsiveness by incorporating phase shifting and power adjustment. This adaptive approach ensures that the moving average remains sensitive to changes in volume and price dynamics. As a result, traders can identify turning points and anticipate potential trend reversals, precisely timing their position entries.
KAMA (Kaufman's Adaptive Moving Average):
KAMA is an adaptive moving average designed to dynamically adjust its sensitivity based on market conditions. By incorporating KAMA into our VWMA modification, we ensure that the moving average adapts to varying volume levels and captures the essence of volume-driven price movements. Traders can confidently enter positions during periods of high trading volume, aligning their strategies with market activity.
Benefits and Usage
The modified T3 JMA KAMA VWMA Indicator offers several advantages to traders looking to exploit high-volume market conditions for position entry:
Increased Responsiveness: By incorporating more responsive moving averages, the indicator enables traders to react quickly to changes in volume and capture short-term opportunities more effectively.
Enhanced Entry Timing: The modified VWMA aligns with high-volume periods, allowing traders to enter positions precisely during price movements influenced by significant trading activity.
Improved Accuracy: The combination of T3, JMA, and KAMA within the VWMA formula enhances the accuracy of trend identification, reversals, and overall market analysis.
Comprehensive Market Insights: The T3 JMA KAMA VWMA Indicator provides a holistic view of market conditions by considering both price and volume dynamics. This comprehensive perspective helps traders make informed decisions.
Analysis and Interpretation
The modified VWMA formula with T3, JMA, and KAMA offers traders a valuable tool for analyzing volume-driven market conditions. By incorporating these advanced moving averages into the VWMA calculation, the indicator becomes more responsive to changes in volume, potentially providing deeper insights into price movements.
When analyzing the modified VWMA, it is essential to consider the following points:
Identifying High-Volume Periods:
The modified VWMA is designed to capture price movements during high-volume periods. Traders can use this indicator to identify potential market trends and determine whether significant trading activity is driving price action. By focusing on these periods, traders may gain a better understanding of the market sentiment and adjust their strategies accordingly.
Confirmation of Trend Strength:
The modified VWMA can serve as a confirmation tool for assessing the strength of a trend. When the VWMA line aligns with the overall trend direction, it suggests that the current price movement is supported by volume. This confirmation can provide traders with additional confidence in their analysis and help them make more informed trading decisions.
Potential Entry and Exit Points:
One of the primary purposes of the modified VWMA is to assist traders in identifying potential entry and exit points. By capturing volume-driven price movements, the indicator can highlight areas where market participants are actively participating, indicating potential opportunities for opening or closing positions. Traders can use this information in conjunction with other technical analysis tools to develop comprehensive trading strategies.
Interpretation of Angle and Gradient:
The modified VWMA incorporates an angle calculation and color gradient to further enhance interpretation. The angle of the VWMA line represents the slope of the indicator, providing insights into the momentum of price movements. A steep angle indicates strong momentum, while a shallow angle suggests a slowdown. The color gradient helps visualize this angle, with green indicating bullish momentum and purple indicating bearish momentum.
Conclusion
By modifying the VWMA formula to incorporate the T3, JMA, and KAMA moving averages, the T3 JMA KAMA VWMA Indicator offers traders an innovative tool to exploit high-volume market conditions for optimal position entry. This modification enhances responsiveness, improves timing, and provides comprehensive market insights.
Enjoy checking it out!
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Credits to:
◾ @cheatcountry – Hann Window Smoothing
◾ @loxx – T3
◾ @everget – JMA
Draw Line For High Low Custom Range Interactive█ OVERVIEW
This indicator is an educational indicator to make pine coders easier to how to use interactive inputs with User-Defined Type (UDT) especially when dealing input.time.
█ NOTES
This indicator is not perfect but it is a good starting point or template to start develop custom range interactive indicator.
█ INSPIRATIONS
ABC 123 Harmonic Ratio Custom Range Interactive
XABCD Harmonic Pattern Custom Range Interactive
PriceTimeInteractive
█ CREDITS
CAGR Custom Range
Pine scripts are now interactive
█ FEATURES
1. High Low points are determined based on points selected.
2. Line will be drawn after points are correctly arranged.
3. Label show error once wrong point is selected, move the point as instructed in example.
█ EXAMPLES / USAGE
L&S Volatility IndexOverview
L&S Volatility Index is a tool designed to helps traders identify overpriced or underpriced moments in the market and adjust their trading strategies accordingly.
Calculations
This tool calculates how far the price is from the 21-period simple moving average as a ratio of the average historical volatility calculated over the last 21 candles.
How It Works
A L&S Volatility Index with a value greater than 30% may indicate that the asset is overpriced or underpriced relative to its average price.
How To Use
If the L&S Volatility Index > 30, the asset is overpriced or underpriced. This means that there is a good probability of initiating a mean reversion.
If the L&S Volatility Index < 30, the asset is in a fair price region. This means that it is acceptable to buy or sell in that price region.
Where To Use
Mean Reversion Strategy
Breakout Strategy
What Makes it Original
There is already an indicator that use a normalized calculation and a different approach to calculate historical volatility, whereas this script calculation is non-normalized and historical volatility is calculated using Don Fishback's formula. All calculations are used as originally described.
Credits
The L&S Volatility Index indicator was originally written by L&S Educação Financeira.
Historical Volatility calculation is based on the book "Odds: The Key to 90% Winners" written by Don Fishback.
Chandelier Exit ZLSMA StrategyIntroducing a Powerful Trading Indicator: Chandelier Exit with ZLSMA
If you're a trader, you know the importance of having the right tools and indicators to make informed decisions. That's why we're excited to introduce a powerful new trading indicator that combines the Chandelier Exit and ZLSMA: two widely-used and effective indicators for technical analysis.
The Chandelier Exit (CE) is a popular trailing stop-loss indicator developed by Chuck LeBeau. It's designed to follow the price trend of a security and provide an exit signal when the price crosses below the CE line. The CE line is based on the Average True Range (ATR), which is a measure of volatility. This means that the CE line adjusts to the volatility of the security, making it a reliable indicator for trailing stop-losses.
The ZLEMA (Zero Lag Exponential Moving Average) is a type of exponential moving average that's designed to reduce lag and improve signal accuracy. The ZLSMA takes into account not only the current price but also past prices, using a weighted formula to calculate the moving average. This makes it a smoother indicator than traditional moving averages, and less prone to giving false signals.
When combined, the CE and ZLSMA create a powerful indicator that can help traders identify trend changes and make more informed trading decisions. The CE provides the trailing stop-loss signal, while the ZLSMA provides a smoother trend line to help identify potential entry and exit points.
In our indicator, the CE and ZLSMA are plotted together on the chart, making it easy to see both the trailing stop-loss and the trend line at the same time. The CE line is displayed as a dotted line, while the ZLSMA line is displayed as a solid line.
Using this indicator, traders can set their stop-loss levels based on the CE line, while also using the ZLSMA line to identify potential entry and exit points. The combination of these two indicators can help traders reduce their risk and improve their trading performance.
In conclusion, the Chandelier Exit with ZLSMA is a powerful trading indicator that combines two effective technical analysis tools. By using this indicator, traders can identify trend changes, set stop-loss levels, and make more informed trading decisions. Try it out for yourself and see how it can improve your trading performance.
Warning: The results in the backtest are from a repainting strategy. Don't take them seriously. You need to do a dry live test in order to test it for its useability.
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Here is a description of each input field in the provided source code:
length: An integer input used as the period for the ATR (Average True Range) calculation. Default value is 1.
mult: A float input used as a multiplier for the ATR value. Default value is 2.
showLabels: A boolean input that determines whether to display buy/sell labels on the chart. Default value is false.
isSignalLabelEnabled: A boolean input that determines whether to display signal labels on the chart. Default value is true.
useClose: A boolean input that determines whether to use the close price for extrema calculations. Default value is true.
zcolorchange: A boolean input that determines whether to enable rising/decreasing highlighting for the ZLSMA (Zero-Lag Exponential Moving Average) line. Default value is false.
zlsmaLength: An integer input used as the length for the ZLSMA calculation. Default value is 50.
offset: An integer input used as an offset for the ZLSMA calculation. Default value is 0.
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Ty for checking this out and good luck on your trading journey! Likes and comments are appreciated. 👍
--
Credits to:
▪ @everget – Chandelier Exit (CE)
▪ @netweaver2022 – ZLSMA
Bollinger Bands - Breakout StrategyThe Bollinger Bands - Breakout Strategy is a trend-following optimized for short-term trading in the crypto market. This strategy employs the Bollinger Bands, a widely recognized technical indicator, as its primary instrument for pinpointing potential trades. It is capable of executing both long and short positions, depending on whether the market is in a spot or futures, and is particularly effective in trending markets.
The strategy boasts a high degree of configurability, allowing users to set the Bollinger Bands period and deviation, trend filter, volatility filter, trade direction filter, rate of change filter, and date filter. Furthermore, it offers options for Take Profit, Stop Loss, and Trailing Stop for both long and short positions, ensuring a comprehensive risk management approach. The inclusion of a maximum intraday loss feature adds another layer of protection, making this strategy a valuable tool for traders seeking a professional and adaptable trading system.
Name : Bollinger Bands - Breakout Strategy
Category : Trend Follower based on Bollinger Bands
Operating mode : Long and Short on Futures or Long on Spot
Trade duration : Intraday
Timeframe : 2H, 3H, 4H, 5H
Market : Crypto
Suggested usage : Trending Markets
Entry : When the price crosses above or below the Bollinger Bands
Exit : Opposite Cross or Profit target, Trailing stop or Stop loss
Configuration :
- Bollinger Bands period and deviation
- Trend Filter
- Volatility Filter
- Trade direction filter
- Rate of Change filter
- Date Filter (for backtesting purposes)
- Take Profit, Stop Loss and Trailing Stop for long and short positions
- Risk Management: Max Intraday Loss
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: BTCUSDT.P
⁃ Timeframe: 4H
⁃ Fee: 0.025%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2019-09-19 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits :
- LucF of Pine Coders for f_security function to avoid repainting using security.
- QuantNomad for Monthly Table.
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Joel Greenblatt Magic FormulaJoel Greenblatt Magic Formula. I always wanted to make this.
The Indicator shows 3 values.
ROC,EY,SUM.
ROC= Return On Capital.
EY=Earnings Yield
SUM= Addition of Two.
Formula:
ROC=EBIT / (Net Working Capital + Net Fixed Assets).
EY = EBIT / Enterprise value
Enterprise Value=(Market value of equity + Net Interest-bearing debt)
To implement the strategy, investors start by identifying a universe of stocks, typically large-cap or mid-cap companies that trade on a major stock exchange. Next, they rank the stocks based on their ROC and EY. The companies with the best combination of these two metrics are considered the best investments (based on this ranking).
For example, a stock that ranks 10th on EY and 99th on ROIC gets a value of 109. The two ranks are simply added together and all stocks are ranked on the sum of the two ranks. The stocks with the lowest values are best.
All credits to "The Little Book That Beats The Market" by Joel Greenblatt
The Magic Formula strategy is a stock selection method popularized by Joel Greenblatt’s book The Little Book That Beats the Market.
It involves ranking companies based on Two factors:
A high return on capital and A high Earnings Yield.
The companies with the best combination of these two metrics are considered the best investments. The strategy aims to find undervalued companies with strong financials that have the potential for high returns over the long term.
Yesterday’s High Breakout - Trend Following StrategyYesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of NULS, a 9% Take-Profit and a 3% Stop-Loss were set, with an activated trailing-stop percentage. To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name : Yesterday's High Breakout - Trend Follower Strategy
Author : @tumiza999
Category : Trend Follower, Breakout of Yesterday's High.
Operating mode : Spot or Futures (only long).
Trade duration : Intraday.
Timeframe : 30M, 1H, 2H, 4H
Market : Crypto
Suggested usage : Short-term trading, when the market is in trend and it is showing high volatility.
Entry : When there is a breakout of Yesterday's High.
Exit : Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration :
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: NULSUSDT
⁃ Timeframe: 2H
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits : LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Sniffer
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Overview
A vast majority of modern data analysis & modelling techniques rely upon the idea of hidden patterns, wether it is some type of visualisation tool or some form of a complex machine learning algorithm, the one thing that they have in common is the belief, that patterns tell us what’s hidden behind plain numbers. The same philosophy has been adopted by many traders & investors worldwide, there’s an entire school of thought that operates purely based on chart patterns. This is where Sniffer comes in, it is a tool designed to simplify & quantify the job of pattern recognition on any given price chart, by combining various factors & techniques that generate high-quality results.
This tool analyses bars selected by the user, and highlights bar clusters on the chart that exhibit similar behaviour across multiple dimensions. It can detect a single candle pattern like hammers or dojis, or it can handle multiple candles like morning/evening stars or double tops/bottoms, and many more. In fact, the tool is completely independent of such specific candle formations, instead, it works on the idea of vector similarity and generates a degree of similarity for every single combination of candles. Only the top-n matches are highlighted, users get to choose which patterns they want to analyse and to what degree, by customising the feature-space.
Background
In the world of trading, a common use-case is to scan a price chart for some specific candlestick formations & price structures, and then the chart is further analysed in reference to these events. Traders are often trying to answer questions like, when was the last time price showed similar behaviour, what are the instances similar to what price is doing right now, what happens when price forms a pattern like this, what were some of other indicators doing when this happened last(RSI, CCI, ADX etc), and many other abstract ideas to have a stronger confluence or to confirm a bias.Having such a context can be vital in making better informed decisions, but doing this manually on a chart that has thousands of candles can have many disadvantages. It’s tedious, human errors are rather likely, and even if it’s done with pin-point accuracy, chances are that we’ll miss out on many pieces of information. This is the thought that gave birth to Sniffer .
Sniffer tries to provide a general solution for pattern-based analysis by deploying vector-similarity computation techniques, that cover the full-breadth of a price chart and generate a list of top-n matches based on the criteria selected by the user. Most of these techniques come from the data science space, where vector similarity is often implemented to solve classification & clustering problems. Sniffer uses same principles of vector comparison, and computes a degree of similarity for every single candle formation within the selected range, and as a result generates a similarity matrix that captures how similar or dissimilar a set of candles is to the input set selected by the user.
How It Works
A brief overview of how the tool is implemented:
- Every bar is processed, and a set of features are mapped to it.
- Bars selected by the user are captured, and saved for later use.
- Once the all the bars have been processed, candles are back-tracked and degree of similarity is computed for every single bar(max-limit is 5000 bars).
- Degree of similarity is computed by comparing attributes like price range, candle breadth & volume etc.
- Similarity matrix is sorted and top-n results are highlighted on the chart through boxes of different colors.
A brief overview of the features space for bars:
- Range: Difference between high & low
- Body: Difference between close & open
- Volume: Traded volume for that candle
- Head: Upper wick for green candles & lower wick for red candles
- Tail: Lower wick for green candles & upper wick for red candles
- BTR: Body to Range ratio
- HTR: Head to Range ratio
- TTR: Tail to Range ratio
- HTB: Head to Body ratio
- TTB: Tail to Body ratio
- ROC: Rate of change for HL2 for four different periods
- RSI: Relative Strength Index
- CCI: Commodity Channel Index
- Stochastic: Stochastic Index
- ADX: DMI+, DMI- & ADX
A brief overview of how degree of similarity is calculated:
- Each bar set is compared to the inout bar set within the selected feature space
- Features are represented as vectors, and distance between the vectors is calculated
- Shorter the distance, greater the similarity
- Different distance calculation methods are available to choose from, such as Cosine, Euclidean, Lorentzian, Manhattan, & Pearson
- Each method is likely to generate slightly different results, users are expected to select the method & the feature space that best fits their use-case
How To Use It
- Usage of this tool is relatively straightforward, users can add this indicator to their chart and similar clusters will be highlighted automatically
- Users need to select a time range that will be treated as input, and bars within that range become the input formation for similarity calculations
- Boxes will be draw around the clusters that fit the matching criteria
- Boxes are color-coded, green color boxes represent the top one-third of the top-n matches, yellow boxes represent the middle third, red boxes are for bottom third, and white box represents user-input
- Boxes colors will be adjusted as you adjust input parameters, such as number of matches or look-back period
User Settings
Users can configure the following options:
- Select the time-range to set input bars
- Select the look-back period, number of candles to backtrack for similarity search
- Select the number of top-n matches to show on the chart
- Select the method for similarity calculation
- Adjust the feature space, this enables addition of custom features, such as pattern recognition, technical indicators, rate of change etc
- Toggle verbosity, shows degree of similarity as a percentage value inside the box
Top Features
- Pattern Agnostic: Designed to work with variable number of candles & complex patterns
- Customisable Feature Space: Users get to add custom features to each bar
- Comprehensive Comparison: Generates a degree of similarity for all possible combinations
Final Note
- Similarity matches will be shown only within last 4500 bars.
- In theory, it is possible to compute similarity for any size candle formations, indicator has been tested with formations of 50+ candles, but it is recommended to select smaller range for faster & cleaner results.
- As you move to smaller time frames, selected time range will provide a larger number of candles as input, which can produce undesired results, it is advised to adjust your selection when you change time frames. Seeking suggestions on how to directly receive bars as user input, instead of time range.
- At times, users may see array index out of bound error when setting up this indicator, this generally happens when the input range is not properly configured. So, it should disappear after you select the input range, still trying to figure out where it is coming from, suggestions are welcome.
Credits
- @HeWhoMustNotBeNamed for publishing such a handy PineScript Logger, it certainly made the job a lot easier.
Regression Channel Alternative MTF V2█ OVERVIEW
This indicator is a predecessor to Regression Channel Alternative MTF , which is coded based on latest update of type, object and method.
█ IMPORTANT NOTES
This indicator is NOT true Multi Timeframe (MTF) but considered as Alternative MTF which calculate 100 bars for Primary MTF, can be refer from provided line helper.
The timeframe scenarios are defined based on Position, Swing and Intraday Trader.
Suppported Timeframe : W, D, 60, 15, 5 and 1.
Channel drawn based on regression calculation.
Angle channel is NOT supported.
█ INSPIRATIONS
These timeframe scenarios are defined based on Harmonic Trading : Volume Three written by Scott M Carney.
By applying channel on each timeframe, MW or ABCD patterns can be easily identified manually.
This can also be applied on other chart patterns.
█ CREDITS
Scott M Carney, Harmonic Trading : Volume Three (Reaction vs. Reversal)
█ TIMEFRAME EXPLAINED
Higher / Distal : The (next) longer or larger comparative timeframe after primary pattern has been identified.
Primary / Clear : Timeframe that possess the clearest pattern structure.
Lower / Proximate : The (next) shorter timeframe after primary pattern has been identified.
Lowest : Check primary timeframe as main reference.
█ FEATURES
Color is determined by trend or timeframe.
Some color is depends on chart contrast color.
Color is determined by trend or timeframe.
█ EXAMPLE OF USAGE / EXPLAINATION
