DrawingLibrary "Drawing"
User Defined types and methods for basic drawing structure. Consolidated from the earlier libraries - DrawingTypes and DrawingMethods
method get_price(this, bar)
get line price based on bar
Namespace types: Line
Parameters:
this (Line) : (series Line) Line object.
bar (int) : (series/int) bar at which line price need to be calculated
Returns: line price at given bar.
method init(this)
Namespace types: PolyLine
Parameters:
this (PolyLine)
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Point object to string representation
Namespace types: chart.point
Parameters:
this (chart.point) : DrawingTypes/Point object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Point
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/LineProperties object to string representation
Namespace types: LineProperties
Parameters:
this (LineProperties) : DrawingTypes/LineProperties object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/LineProperties
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Line object to string representation
Namespace types: Line
Parameters:
this (Line) : DrawingTypes/Line object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Line
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/LabelProperties object to string representation
Namespace types: LabelProperties
Parameters:
this (LabelProperties) : DrawingTypes/LabelProperties object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/LabelProperties
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Label object to string representation
Namespace types: Label
Parameters:
this (Label) : DrawingTypes/Label object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Label
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Linefill object to string representation
Namespace types: Linefill
Parameters:
this (Linefill) : DrawingTypes/Linefill object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Linefill
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/BoxProperties object to string representation
Namespace types: BoxProperties
Parameters:
this (BoxProperties) : DrawingTypes/BoxProperties object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/BoxProperties
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/BoxText object to string representation
Namespace types: BoxText
Parameters:
this (BoxText) : DrawingTypes/BoxText object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/BoxText
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts DrawingTypes/Box object to string representation
Namespace types: Box
Parameters:
this (Box) : DrawingTypes/Box object
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (array) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of DrawingTypes/Box
method delete(this)
Deletes line from DrawingTypes/Line object
Namespace types: Line
Parameters:
this (Line) : DrawingTypes/Line object
Returns: Line object deleted
method delete(this)
Deletes label from DrawingTypes/Label object
Namespace types: Label
Parameters:
this (Label) : DrawingTypes/Label object
Returns: Label object deleted
method delete(this)
Deletes Linefill from DrawingTypes/Linefill object
Namespace types: Linefill
Parameters:
this (Linefill) : DrawingTypes/Linefill object
Returns: Linefill object deleted
method delete(this)
Deletes box from DrawingTypes/Box object
Namespace types: Box
Parameters:
this (Box) : DrawingTypes/Box object
Returns: DrawingTypes/Box object deleted
method delete(this)
Deletes lines from array of DrawingTypes/Line objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Line objects
Returns: Array of DrawingTypes/Line objects
method delete(this)
Deletes labels from array of DrawingTypes/Label objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
method delete(this)
Deletes linefill from array of DrawingTypes/Linefill objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Linefill objects
Returns: Array of DrawingTypes/Linefill objects
method delete(this)
Deletes boxes from array of DrawingTypes/Box objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Box objects
Returns: Array of DrawingTypes/Box objects
method clear(this)
clear items from array of DrawingTypes/Line while deleting underlying objects
Namespace types: array
Parameters:
this (array) : array
Returns: void
method clear(this)
clear items from array of DrawingTypes/Label while deleting underlying objects
Namespace types: array
Parameters:
this (array) : array
Returns: void
method clear(this)
clear items from array of DrawingTypes/Linefill while deleting underlying objects
Namespace types: array
Parameters:
this (array) : array
Returns: void
method clear(this)
clear items from array of DrawingTypes/Box while deleting underlying objects
Namespace types: array
Parameters:
this (array) : array
Returns: void
method draw(this)
Creates line from DrawingTypes/Line object
Namespace types: Line
Parameters:
this (Line) : DrawingTypes/Line object
Returns: line created from DrawingTypes/Line object
method draw(this)
Creates lines from array of DrawingTypes/Line objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Line objects
Returns: Array of DrawingTypes/Line objects
method draw(this)
Creates label from DrawingTypes/Label object
Namespace types: Label
Parameters:
this (Label) : DrawingTypes/Label object
Returns: label created from DrawingTypes/Label object
method draw(this)
Creates labels from array of DrawingTypes/Label objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
method draw(this)
Creates linefill object from DrawingTypes/Linefill
Namespace types: Linefill
Parameters:
this (Linefill) : DrawingTypes/Linefill objects
Returns: linefill object created
method draw(this)
Creates linefill objects from array of DrawingTypes/Linefill objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Linefill objects
Returns: Array of DrawingTypes/Linefill used for creating linefills
method draw(this)
Creates box from DrawingTypes/Box object
Namespace types: Box
Parameters:
this (Box) : DrawingTypes/Box object
Returns: box created from DrawingTypes/Box object
method draw(this)
Creates labels from array of DrawingTypes/Label objects
Namespace types: array
Parameters:
this (array) : Array of DrawingTypes/Label objects
Returns: Array of DrawingTypes/Label objects
method createLabel(this, lblText, tooltip, properties)
Creates DrawingTypes/Label object from DrawingTypes/Point
Namespace types: chart.point
Parameters:
this (chart.point) : DrawingTypes/Point object
lblText (string) : Label text
tooltip (string) : Tooltip text. Default is na
properties (LabelProperties) : DrawingTypes/LabelProperties object. Default is na - meaning default values are used.
Returns: DrawingTypes/Label object
method createLine(this, other, properties)
Creates DrawingTypes/Line object from one DrawingTypes/Point to other
Namespace types: chart.point
Parameters:
this (chart.point) : First DrawingTypes/Point object
other (chart.point) : Second DrawingTypes/Point object
properties (LineProperties) : DrawingTypes/LineProperties object. Default set to na - meaning default values are used.
Returns: DrawingTypes/Line object
method createLinefill(this, other, fillColor, transparency)
Creates DrawingTypes/Linefill object from DrawingTypes/Line object to other DrawingTypes/Line object
Namespace types: Line
Parameters:
this (Line) : First DrawingTypes/Line object
other (Line) : Other DrawingTypes/Line object
fillColor (color) : fill color of linefill. Default is color.blue
transparency (int) : fill transparency for linefill. Default is 80
Returns: Array of DrawingTypes/Linefill object
method createBox(this, other, properties, textProperties)
Creates DrawingTypes/Box object from one DrawingTypes/Point to other
Namespace types: chart.point
Parameters:
this (chart.point) : First DrawingTypes/Point object
other (chart.point) : Second DrawingTypes/Point object
properties (BoxProperties) : DrawingTypes/BoxProperties object. Default set to na - meaning default values are used.
textProperties (BoxText) : DrawingTypes/BoxText object. Default is na - meaning no text will be drawn
Returns: DrawingTypes/Box object
method createBox(this, properties, textProperties)
Creates DrawingTypes/Box object from DrawingTypes/Line as diagonal line
Namespace types: Line
Parameters:
this (Line) : Diagonal DrawingTypes/PoLineint object
properties (BoxProperties) : DrawingTypes/BoxProperties object. Default set to na - meaning default values are used.
textProperties (BoxText) : DrawingTypes/BoxText object. Default is na - meaning no text will be drawn
Returns: DrawingTypes/Box object
LineProperties
Properties of line object
Fields:
xloc (series string) : X Reference - can be either xloc.bar_index or xloc.bar_time. Default is xloc.bar_index
extend (series string) : Property which sets line to extend towards either right or left or both. Valid values are extend.right, extend.left, extend.both, extend.none. Default is extend.none
color (series color) : Line color
style (series string) : Line style, valid values are line.style_solid, line.style_dashed, line.style_dotted, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both. Default is line.style_solid
width (series int) : Line width. Default is 1
Line
Line object created from points
Fields:
start (chart.point) : Starting point of the line
end (chart.point) : Ending point of the line
properties (LineProperties) : LineProperties object which defines the style of line
object (series line) : Derived line object
LabelProperties
Properties of label object
Fields:
xloc (series string) : X Reference - can be either xloc.bar_index or xloc.bar_time. Default is xloc.bar_index
yloc (series string) : Y reference - can be yloc.price, yloc.abovebar, yloc.belowbar. Default is yloc.price
color (series color) : Label fill color
style (series string) : Label style as defined in Tradingview Documentation. Default is label.style_none
textcolor (series color) : text color. Default is color.black
size (series string) : Label text size. Default is size.normal. Other values are size.auto, size.tiny, size.small, size.normal, size.large, size.huge
textalign (series string) : Label text alignment. Default if text.align_center. Other allowed values - text.align_right, text.align_left, text.align_top, text.align_bottom
text_font_family (series string) : The font family of the text. Default value is font.family_default. Other available option is font.family_monospace
Label
Label object
Fields:
point (chart.point) : Point where label is drawn
lblText (series string) : label text
tooltip (series string) : Tooltip text. Default is na
properties (LabelProperties) : LabelProperties object
object (series label) : Pine label object
Linefill
Linefill object
Fields:
line1 (Line) : First line to create linefill
line2 (Line) : Second line to create linefill
fillColor (series color) : Fill color
transparency (series int) : Fill transparency range from 0 to 100
object (series linefill) : linefill object created from wrapper
BoxProperties
BoxProperties object
Fields:
border_color (series color) : Box border color. Default is color.blue
bgcolor (series color) : box background color
border_width (series int) : Box border width. Default is 1
border_style (series string) : Box border style. Default is line.style_solid
extend (series string) : Extend property of box. default is extend.none
xloc (series string) : defines if drawing needs to be done based on bar index or time. default is xloc.bar_index
BoxText
Box Text properties.
Fields:
boxText (series string) : Text to be printed on the box
text_size (series string) : Text size. Default is size.auto
text_color (series color) : Box text color. Default is color.yellow.
text_halign (series string) : horizontal align style - default is text.align_center
text_valign (series string) : vertical align style - default is text.align_center
text_wrap (series string) : text wrap style - default is text.wrap_auto
text_font_family (series string) : Text font. Default is
Box
Box object
Fields:
p1 (chart.point) : Diagonal point one
p2 (chart.point) : Diagonal point two
properties (BoxProperties) : Box properties
textProperties (BoxText) : Box text properties
object (series box) : Box object created
PolyLineProperties
Fields:
curved (series bool)
closed (series bool)
xloc (series string)
lineColor (series color)
fillColor (series color)
lineStyle (series string)
lineWidth (series int)
PolyLine
Fields:
points (array)
properties (PolyLineProperties)
object (series polyline)
Cari dalam skrip untuk "curve"
Multiple Naked LevelsPURPOSE OF THE INDICATOR
This indicator autogenerates and displays naked levels and gaps of multiple types collected into one simple and easy to use indicator.
VALUE PROPOSITION OF THE INDICATOR AND HOW IT IS ORIGINAL AND USEFUL
1) CONVENIENCE : The purpose of this indicator is to offer traders with one coherent and robust indicator providing useful, valuable, and often used levels - in one place.
2) CLUSTERS OF CONFLUENCES : With this indicator it is easy to identify levels and zones on the chart with multiple confluences increasing the likelihood of a potential reversal zone.
THE TYPES OF LEVELS AND GAPS INCLUDED IN THE INDICATOR
The types of levels include the following:
1) PIVOT levels (Daily/Weekly/Monthly) depicted in the chart as: dnPIV, wnPIV, mnPIV.
2) POC (Point of Control) levels (Daily/Weekly/Monthly) depicted in the chart as: dnPoC, wnPoC, mnPoC.
3) VAH/VAL STD 1 levels (Value Area High/Low with 1 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH1/dnVAL1, wnVAH1/wnVAL1, mnVAH1/mnVAL1
4) VAH/VAL STD 2 levels (Value Area High/Low with 2 std) (Daily/Weekly/Monthly) depicted in the chart as: dnVAH2/dnVAL2, wnVAH2/wnVAL2, mnVAH1/mnVAL2
5) FAIR VALUE GAPS (Daily/Weekly/Monthly) depicted in the chart as: dnFVG, wnFVG, mnFVG.
6) CME GAPS (Daily) depicted in the chart as: dnCME.
7) EQUILIBRIUM levels (Daily/Weekly/Monthly) depicted in the chart as dnEQ, wnEQ, mnEQ.
HOW-TO ACTIVATE LEVEL TYPES AND TIMEFRAMES AND HOW-TO USE THE INDICATOR
You can simply choose which of the levels to be activated and displayed by clicking on the desired radio button in the settings menu.
You can locate the settings menu by clicking into the Object Tree window, left-click on the Multiple Naked Levels and select Settings.
You will then get a menu of different level types and timeframes. Click the checkboxes for the level types and timeframes that you want to display on the chart.
You can then go into the chart and check out which naked levels that have appeared. You can then use those levels as part of your technical analysis.
The levels displayed on the chart can serve as additional confluences or as part of your overall technical analysis and indicators.
In order to back-test the impact of the different naked levels you can also enable tapped levels to be depicted on the chart. Do this by toggling the 'Show tapped levels' checkbox.
Keep in mind however that Trading View can not shom more than 500 lines and text boxes so the indocator will not be able to give you the complete history back to the start for long duration assets.
In order to clean up the charts a little bit there are two additional settings that can be used in the Settings menu:
- Selecting the price range (%) from the current price to be included in the chart. The default is 25%. That means that all levels below or above 20% will not be displayed. You can set this level yourself from 0 up to 100%.
- Selecting the minimum gap size to include on the chart. The default is 1%. That means that all gaps/ranges below 1% in price difference will not be displayed on the chart. You can set the minimum gap size yourself.
BASIC DESCRIPTION OF THE INNER WORKINGS OF THE INDICTATOR
The way the indicator works is that it calculates and identifies all levels from the list of levels type and timeframes above. The indicator then adds this level to a list of untapped levels.
Then for each bar after, it checks if the level has been tapped. If the level has been tapped or a gap/range completely filled, this level is removed from the list so that the levels displayed in the end are only naked/untapped levels.
Below is a descrition of each of the level types and how it is caluclated (algorithm):
PIVOT
Daily, Weekly and Monthly levels in trading refer to significant price points that traders monitor within the context of a single trading day. These levels can provide insights into market behavior and help traders make informed decisions regarding entry and exit points.
Traders often use D/W/M levels to set entry and exit points for trades. For example, entering long positions near support (daily close) or selling near resistance (daily close).
Daily levels are used to set stop-loss orders. Placing stops just below the daily close for long positions or above the daily close for short positions can help manage risk.
The relationship between price movement and daily levels provides insights into market sentiment. For instance, if the price fails to break above the daily high, it may signify bearish sentiment, while a strong breakout can indicate bullish sentiment.
The way these levels are calculated in this indicator is based on finding pivots in the chart on D/W/M timeframe. The level is then set to previous D/W/M close = current D/W/M open.
In addition, when price is going up previous D/W/M open must be smaller than previous D/W/M close and current D/W/M close must be smaller than the current D/W/M open. When price is going down the opposite.
POINT OF CONTROL
The Point of Control (POC) is a key concept in volume profile analysis, which is commonly used in trading.
It represents the price level at which the highest volume of trading occurred during a specific period.
The POC is derived from the volume traded at various price levels over a defined time frame. In this indicator the timeframes are Daily, Weekly, and Montly.
It identifies the price level where the most trades took place, indicating strong interest and activity from traders at that price.
The POC often acts as a significant support or resistance level. If the price approaches the POC from above, it may act as a support level, while if approached from below, it can serve as a resistance level. Traders monitor the POC to gauge potential reversals or breakouts.
The way the POC is calculated in this indicator is by an approximation by analysing intrabars for the respective timeperiod (D/W/M), assigning the volume for each intrabar into the price-bins that the intrabar covers and finally identifying the bin with the highest aggregated volume.
The POC is the price in the middle of this bin.
The indicator uses a sample space for intrabars on the Daily timeframe of 15 minutes, 35 minutes for the Weekly timeframe, and 140 minutes for the Monthly timeframe.
The indicator has predefined the size of the bins to 0.2% of the price at the range low. That implies that the precision of the calulated POC og VAH/VAL is within 0.2%.
This reduction of precision is a tradeoff for performance and speed of the indicator.
This also implies that the bigger the difference from range high prices to range low prices the more bins the algorithm will iterate over. This is typically the case when calculating the monthly volume profile levels and especially high volatility assets such as alt coins.
Sometimes the number of iterations becomes too big for Trading View to handle. In these cases the bin size will be increased even more to reduce the number of iterations.
In such cases the bin size might increase by a factor of 2-3 decreasing the accuracy of the Volume Profile levels.
Anyway, since these Volume Profile levels are approximations and since precision is traded for performance the user should consider the Volume profile levels(POC, VAH, VAL) as zones rather than pin point accurate levels.
VALUE AREA HIGH/LOW STD1/STD2
The Value Area High (VAH) and Value Area Low (VAL) are important concepts in volume profile analysis, helping traders understand price levels where the majority of trading activity occurs for a given period.
The Value Area High/Low is the upper/lower boundary of the value area, representing the highest price level at which a certain percentage of the total trading volume occurred within a specified period.
The VAH/VAL indicates the price point above/below which the majority of trading activity is considered less valuable. It can serve as a potential resistance/support level, as prices above/below this level may experience selling/buying pressure from traders who view the price as overvalued/undervalued
In this indicator the timeframes are Daily, Weekly, and Monthly. This indicator provides two boundaries that can be selected in the menu.
The first boundary is 70% of the total volume (=1 standard deviation from mean). The second boundary is 95% of the total volume (=2 standard deviation from mean).
The way VAH/VAL is calculated is based on the same algorithm as for the POC.
However instead of identifying the bin with the highest volume, we start from range low and sum up the volume for each bin until the aggregated volume = 30%/70% for VAL1/VAH1 and aggregated volume = 5%/95% for VAL2/VAH2.
Then we simply set the VAL/VAH equal to the low of the respective bin.
FAIR VALUE GAPS
Fair Value Gaps (FVG) is a concept primarily used in technical analysis and price action trading, particularly within the context of futures and forex markets. They refer to areas on a price chart where there is a noticeable lack of trading activity, often highlighted by a significant price movement away from a previous level without trading occurring in between.
FVGs represent price levels where the market has moved significantly without any meaningful trading occurring. This can be seen as a "gap" on the price chart, where the price jumps from one level to another, often due to a rapid market reaction to news, events, or other factors.
These gaps typically appear when prices rise or fall quickly, creating a space on the chart where no transactions have taken place. For example, if a stock opens sharply higher and there are no trades at the prices in between the two levels, it creates a gap. The areas within these gaps can be areas of liquidity that the market may return to “fill” later on.
FVGs highlight inefficiencies in pricing and can indicate areas where the market may correct itself. When the market moves rapidly, it may leave behind price levels that traders eventually revisit to establish fair value.
Traders often watch for these gaps as potential reversal or continuation points. Many traders believe that price will eventually “fill” the gap, meaning it will return to those price levels, providing potential entry or exit points.
This indicator calculate FVGs on three different timeframes, Daily, Weekly and Montly.
In this indicator the FVGs are identified by looking for a three-candle pattern on a chart, signalling a discrete imbalance in order volume that prompts a quick price adjustment. These gaps reflect moments where the market sentiment strongly leans towards buying or selling yet lacks the opposite orders to maintain price stability.
The indicator sets the gap to the difference from the high of the first bar to the low of the third bar when price is moving up or from the low of the first bar to the high of the third bar when price is moving down.
CME GAPS (BTC only)
CME gaps refer to price discrepancies that can occur in charts for futures contracts traded on the Chicago Mercantile Exchange (CME). These gaps typically arise from the fact that many futures markets, including those on the CME, operate nearly 24 hours a day but may have significant price movements during periods when the market is closed.
CME gaps occur when there is a difference between the closing price of a futures contract on one trading day and the opening price on the following trading day. This difference can create a "gap" on the price chart.
Opening Gaps: These usually happen when the market opens significantly higher or lower than the previous day's close, often influenced by news, economic data releases, or other market events occurring during non-trading hours.
Gaps can result from reactions to major announcements or developments, such as earnings reports, geopolitical events, or changes in economic indicators, leading to rapid price movements.
The importance of CME Gaps in Trading is the potential for Filling Gaps: Many traders believe that prices often "fill" gaps, meaning that prices may return to the gap area to establish fair value.
This can create potential trading opportunities based on the expectation of gap filling. Gaps can act as significant support or resistance levels. Traders monitor these levels to identify potential reversal points in price action.
The way the gap is identified in this indicator is by checking if current open is higher than previous bar close when price is moving up or if current open is lower than previous day close when price is moving down.
EQUILIBRIUM
Equilibrium in finance and trading refers to a state where supply and demand in a market balance each other, resulting in stable prices. It is a key concept in various economic and trading contexts. Here’s a concise description:
Market Equilibrium occurs when the quantity of a good or service supplied equals the quantity demanded at a specific price level. At this point, there is no inherent pressure for the price to change, as buyers and sellers are in agreement.
Equilibrium Price is the price at which the market is in equilibrium. It reflects the point where the supply curve intersects the demand curve on a graph. At the equilibrium price, the market clears, meaning there are no surplus goods or shortages.
In this indicator the equilibrium level is calculated simply by finding the midpoint of the Daily, Weekly, and Montly candles respectively.
NOTES
1) Performance. The algorithms are quite resource intensive and the time it takes the indicator to calculate all the levels could be 5 seconds or more, depending on the number of bars in the chart and especially if Montly Volume Profile levels are selected (POC, VAH or VAL).
2) Levels displayed vs the selected chart timeframe. On a timeframe smaller than the daily TF - both Daily, Weekly, and Monthly levels will be displayed. On a timeframe bigger than the daily TF but smaller than the weekly TF - the Weekly and Monthly levels will be display but not the Daily levels. On a timeframe bigger than the weekly TF but smaller than the monthly TF - only the Monthly levels will be displayed. Not Daily and Weekly.
CREDITS
The core algorithm for calculating the POC levels is based on the indicator "Naked Intrabar POC" developed by rumpypumpydumpy (https:www.tradingview.com/u/rumpypumpydumpy/).
The "Naked intrabar POC" indicator calculates the POC on the current chart timeframe.
This indicator (Multiple Naked Levels) adds two new features:
1) It calculates the POC on three specific timeframes, the Daily, Weekly, and Monthly timeframes - not only the current chart timeframe.
2) It adds functionaly by calculating the VAL and VAH of the volume profile on the Daily, Weekly, Monthly timeframes .
All Harmonic Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws and sends alerts for all of the harmonic patterns in my public library as they occur. The patterns included are as follows:
• Bearish 5-0
• Bullish 5-0
• Bearish ABCD
• Bullish ABCD
• Bearish Alternate Bat
• Bullish Alternate Bat
• Bearish Bat
• Bullish Bat
• Bearish Butterfly
• Bullish Butterfly
• Bearish Cassiopeia A
• Bullish Cassiopeia A
• Bearish Cassiopeia B
• Bullish Cassiopeia B
• Bearish Cassiopeia C
• Bullish Cassiopeia C
• Bearish Crab
• Bullish Crab
• Bearish Deep Crab
• Bullish Deep Crab
• Bearish Cypher
• Bullish Cypher
• Bearish Gartley
• Bullish Gartley
• Bearish Shark
• Bullish Shark
• Bearish Three-Drive
• Bullish Three-Drive
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. The first swing high or swing low will set the course for the sequence of wave cycles that follow; for example a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Figure 1.
Retracement and Extension Ratios
Retracement and extension ratios are calculated by dividing the current range by the preceding range and multiplying the answer by 100. Retracement ratios are those that are equal to or below 100% of the preceding range and extension ratios are those that are above 100% of the preceding range.
Fibonacci Retracement and Extension Ratios
The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers, starting with 0 and 1. For example 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, and so on. Ultimately, we could go on forever but the first few numbers in the sequence are as follows: 0 , 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.
The extension ratios are calculated by dividing each number in the sequence by the number preceding it. For example 0/1 = 0, 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.6666..., 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.6153..., 34/21 = 1.6190..., 55/34 = 1.6176..., 89/55 = 1.6181..., 144/89 = 1.6179..., and so on. The retracement ratios are calculated by inverting this process and dividing each number in the sequence by the number proceeding it. For example 0/1 = 0, 1/1 = 1, 1/2 = 0.5, 2/3 = 0.666..., 3/5 = 0.6, 5/8 = 0.625, 8/13 = 0.6153..., 13/21 = 0.6190..., 21/34 = 0.6176..., 34/55 = 0.6181..., 55/89 = 0.6179..., 89/144 = 0.6180..., and so on.
Fibonacci ranges are typically drawn from left to right, with retracement levels representing ratios inside of the current range and extension levels representing ratios extended outside of the current range. If the current wave cycle ends on a swing low, the Fibonacci range is drawn from peak to trough. If the current wave cycle ends on a swing high the Fibonacci range is drawn from trough to peak.
Measurement Tolerances
Tolerance refers to the allowable variation or deviation from a specific value or dimension. It is the range within which a particular measurement is considered to be acceptable or accurate. I have applied this concept in my pattern detection logic and have set default tolerances where applicable, as perfect patterns are, needless to say, very rare.
Chart Patterns
Generally speaking price charts are nothing more than a series of swing highs and swing lows. When demand outweighs supply over a period of time prices swing higher and when supply outweighs demand over a period of time prices swing lower. These swing highs and swing lows can form patterns that offer insight into the prevailing supply and demand dynamics at play at the relevant moment in time.
‘Let us assume… that you the reader, are not a member of that mysterious inner circle known to the boardrooms as “the insiders”… But it is fairly certain that there are not nearly so many “insiders” as amateur trader supposes and… It is even more certain that insiders can be wrong… Any success they have, however, can be accomplished only by buying and selling… hey can do neither without altering the delicate poise of supply and demand that governs prices. Whatever they do is sooner or later reflected on the charts where you… can detect it. Or detect, at least, the way in which the supply-demand equation is being affected… So, you do not need to be an insider to ride with them frequently… prices move in trends. Some of those trends are straight, some are curved; some are brief and some are long and continued… produced in a series of action and reaction waves of great uniformity. Sooner or later, these trends change direction; they may reverse (as from up to down), or they may be interrupted by some sort of sideways movement and then, after a time, proceed again in their former direction… when a price trend is in the process of reversal… a characteristic area or pattern takes shape on the chart, which becomes recognisable as a reversal formation… Needless to say, the first and most important task of the technical chart analyst is to learn to know the important reversal formations and to judge what they may signify in terms of trading opportunities’ (Edwards & Magee, 1948).
This is as true today as it was when Edwards and Magee were writing in the first half of the last Century, study your patterns and make judgements for yourself about what their implications truly are on the markets and timeframes you are interested in trading.
Over the years, traders have come to discover a multitude of chart and candlestick patterns that are supposed to pertain information on future price movements. However, it is never so clear cut in practice and patterns that where once considered to be reversal patterns are now considered to be continuation patterns and vice versa. Bullish patterns can have bearish implications and bearish patterns can have bullish implications. As such, I would highly encourage you to do your own backtesting.
There is no denying that chart patterns exist, but their implications will vary from market to market and timeframe to timeframe. So it is down to you as an individual to study them and make decisions about how they may be used in a strategic sense.
Harmonic Patterns
The concept of harmonic patterns in trading was first introduced by H.M. Gartley in his book "Profits in the Stock Market", published in 1935. Gartley observed that markets have a tendency to move in repetitive patterns, and he identified several specific patterns that he believed could be used to predict future price movements. The bullish and bearish Gartley patterns are the oldest recognized harmonic patterns in trading and all the other harmonic patterns are modifications of the original Gartley patterns. Gartley patterns are fundamentally composed of 5 points, or 4 waves.
Since then, many other traders and analysts have built upon Gartley's work and developed their own variations of harmonic patterns. One such contributor is Larry Pesavento, who developed his own methods for measuring harmonic patterns using Fibonacci ratios. Pesavento has written several books on the subject of harmonic patterns and Fibonacci ratios in trading. Another notable contributor to harmonic patterns is Scott Carney, who developed his own approach to harmonic trading in the late 1990s and also popularised the use of Fibonacci ratios to measure harmonic patterns. Carney expanded on Gartley's work and also introduced several new harmonic patterns, such as the Shark pattern and the 5-0 pattern.
█ INPUTS
• Change pattern and label colours
• Show or hide patterns individually
• Adjust pattern tolerances
• Set or remove alerts for individual patterns
█ NOTES
You can test the patterns with your own strategies manually by applying the indicator to your chart while in bar replay mode and playing through the history. You could also automate this process with PineScript by using the conditions from my swing and pattern libraries as entry conditions in the strategy tester or your own custom made strategy screener.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
█ SOURCES
Edwards, R., & Magee, J. (1948) Technical Analysis of Stock Trends (10th edn). Reprint, Boca Raton, Florida: Taylor and Francis Group, CRC Press: 2013.
All Chart Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws and sends alerts for all of the chart patterns in my public library as they occur. The patterns included are as follows:
• Ascending Broadening
• Broadening
• Descending Broadening
• Double Bottom
• Double Top
• Triple Bottom
• Triple Top
• Bearish Elliot Wave
• Bullish Elliot Wave
• Bearish Alternate Flag
• Bullish Alternate Flag
• Bearish Flag
• Bullish Flag
• Bearish Ascending Head and Shoulders
• Bullish Ascending Head and Shoulders
• Bearish Descending Head and Shoulders
• Bullish Descending Head and Shoulders
• Bearish Head and Shoulders
• Bullish Head and Shoulders
• Bearish Pennant
• Bullish Pennant
• Ascending Wedge
• Descending Wedge
• Wedge
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Retracement and Extension Ratios
Retracement and extension ratios are calculated by dividing the current range by the preceding range and multiplying the answer by 100. Retracement ratios are those that are equal to or below 100% of the preceding range and extension ratios are those that are above 100% of the preceding range.
Measurement Tolerances
Tolerance refers to the allowable variation or deviation from a specific value or dimension. It is the range within which a particular measurement is considered to be acceptable or accurate. I have applied this concept in my pattern detection logic and have set default tolerances where applicable, as perfect patterns are, needless to say, very rare.
Chart Patterns
Generally speaking price charts are nothing more than a series of swing highs and swing lows. When demand outweighs supply over a period of time prices swing higher and when supply outweighs demand over a period of time prices swing lower. These swing highs and swing lows can form patterns that offer insight into the prevailing supply and demand dynamics at play at the relevant moment in time.
‘Let us assume… that you the reader, are not a member of that mysterious inner circle known to the boardrooms as “the insiders”… But it is fairly certain that there are not nearly so many “insiders” as amateur trader supposes and… It is even more certain that insiders can be wrong… Any success they have, however, can be accomplished only by buying and selling… hey can do neither without altering the delicate poise of supply and demand that governs prices. Whatever they do is sooner or later reflected on the charts where you… can detect it. Or detect, at least, the way in which the supply-demand equation is being affected… So, you do not need to be an insider to ride with them frequently… prices move in trends. Some of those trends are straight, some are curved; some are brief and some are long and continued… produced in a series of action and reaction waves of great uniformity. Sooner or later, these trends change direction; they may reverse (as from up to down), or they may be interrupted by some sort of sideways movement and then, after a time, proceed again in their former direction… when a price trend is in the process of reversal… a characteristic area or pattern takes shape on the chart, which becomes recognisable as a reversal formation… Needless to say, the first and most important task of the technical chart analyst is to learn to know the important reversal formations and to judge what they may signify in terms of trading opportunities’ (Edwards & Magee, 1948).
This is as true today as it was when Edwards and Magee were writing in the first half of the last Century, study your patterns and make judgements for yourself about what their implications truly are on the markets and timeframes you are interested in trading.
Over the years, traders have come to discover a multitude of chart and candlestick patterns that are supposed to pertain information on future price movements. However, it is never so clear cut in practice and patterns that where once considered to be reversal patterns are now considered to be continuation patterns and vice versa. Bullish patterns can have bearish implications and bearish patterns can have bullish implications. As such, I would highly encourage you to do your own backtesting.
There is no denying that chart patterns exist, but their implications will vary from market to market and timeframe to timeframe. So it is down to you as an individual to study them and make decisions about how they may be used in a strategic sense.
█ INPUTS
• Change pattern and label colours
• Show or hide patterns individually
• Adjust pattern ratios and tolerances
• Set or remove alerts for individual patterns
█ NOTES
I have decided to rename some of my previously published patterns based on the way in which the pattern completes. If the pattern completes on a swing high then the pattern is considered bearish, if the pattern completes on a swing low then it is considered bullish. This may seem confusing but it makes sense when you come to backtesting the patterns and want to use the most recent peak or trough prices as stop losses. Patterns that can complete on both a swing high and swing low are for such reasons treated as neutral, namely all broadening and wedge variations. I trust that it is quite self-evident that double and triple bottom patterns are considered bullish while double and triple top patterns are considered bearish, so I did not feel the need to rename those.
The patterns that have been renamed and what they have been renamed to, are as follows:
• Ascending Elliot Waves to Bearish Elliot Waves
• Descending Elliot Waves to Bullish Elliot Waves
• Ascending Head and Shoulders to Bearish Ascending Head and Shoulders
• Descending Head and Shoulders to Bearish Descending Head and Shoulders
• Head and Shoulders to Bearish Head and Shoulders
• Ascending Inverse Head and Shoulders to Bullish Ascending Head and Shoulders
• Descending Inverse Head and Shoulders to Bullish Descending Head and Shoulders
• Inverse Head and Shoulders to Bullish Head and Shoulders
You can test the patterns with your own strategies manually by applying the indicator to your chart while in bar replay mode and playing through the history. You could also automate this process with PineScript by using the conditions from my swing and pattern libraries as entry conditions in the strategy tester or your own custom made strategy screener.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
█ SOURCES
Edwards, R., & Magee, J. (1948) Technical Analysis of Stock Trends (10th edn). Reprint, Boca Raton, Florida: Taylor and Francis Group, CRC Press: 2013.
Nasan Moving Average with ForecastThe "Nasan Moving Average with Forecast" indicator is a technical analysis forecasting tool that combines the principles of historical data analysis and random walk theory. It calculates a customized moving average (Nasan Moving Average) by integrating price data and statistical measures and projects future price points by generating forecast values within calculated volatility bounds, creating a dynamic and insightful visualization of potential market movements. This indicator to blend past market behavior with probabilistic future trends to enhance forecasting.
Input Parameters:
len: Differencing length (default 21, Use a minimum of 5 and for lower time frames less than 15 min use values between 300 -3000)
len1: Correction Factor Length 1 (default 21, this determines the length of the MA you want , eg. 10 MA, 50 MA, 100 MA, )
len2: Correction Factor Length 2 (default 9, this works best if it is ~ </=1/2 of len1 )
len3: Smoothing Length (default 5, I would not change this and only use if I want to introduce lag where you want to use it for cross over strategies).
forecast_points: Number of points to forecast (default 30).
m: Multiplier for standard deviation (default 2.5).
bl: Block length for calculating max/min values (default 100).
use_calculated_max_min: Boolean to decide whether to use calculated max/min values.
Nasan Moving Average Calculation:
Calculates the simple moving average (mean) and standard deviation (sd) of the typical price (hlc3).
Computes intermediate variables (a, b, c, etc.) based on log transformation and cumulative sum.
Applies weighted moving averages (wma) to these intermediate variables to smooth them and derive the final value c6.
Plots c6 as the Nasan Moving Average if the bar is confirmed. To learn more see Nasan Moving Average.
Forecast Points Calculation:
Calculates maximum (max_val) and minimum (min_val) values for the forecast, either using a fixed value or based on standard deviation and a multiplier.
Initializes an array to store forecast values and creates polyline objects for plotting.
If the current bar is one of the last three bars and confirmed:
Clears and reinitializes the polyline.
Initializes the first forecast value from the cumulative sum c.
Generates subsequent forecast values using a random value within the range .
Updates the forecast array and plots the forecast points as an orange curved polyline.
Plotting Max/Min Values:
Plots max_val and min_val as green and red lines, respectively, to indicate the bounds of the forecast range.
Components of the Forecasting Model
Historical Dependence:
Nasan Moving Average Calculation: The script calculates a custom moving average (c6) that incorporates historical price data (hlc3), standard deviations (sd), and weighted moving averages (wma). This part of the code processes historical data to create a smoothed representation of the price trend.
Max/Min Value Calculation: The maximum (max_val) and minimum (min_val) values for the forecast can be calculated based on the historical standard deviation of a transformed variable b over a block length (bl). This introduces historical volatility into the bounds for the forecast.
Random Walk Model:
Random Value Generation: Within the forecast points calculation, a random value (random_val) is generated for each forecast point within the range . This random value introduces stochasticity into the model, characteristic of a random walk process.
Cumulative Sum for Forecasting: The script uses a cumulative sum (prev_f + random_val) to generate the next forecast point (next_f). This is a typical approach in random walk models where each new point is based on the previous point plus some random noise.
Explanation of the Forecast Model
Random Walk Characteristics: Each new forecast point is generated by adding a random value to the previous point, making the model a random walk with drift, where the drift is influenced by historical correction factors (c1, c4).
Historical and Statistical Dependence: The bounds of the random values and the initial conditions are derived from historical data, ensuring that the forecast respects historical volatility and trends.
The forecasting model in the script is a hybrid approach: It uses a random walk to generate future points, characterized by adding random values to the previous forecasted value.
The historical and statistical dependence is incorporated through initial conditions, scaling factors, and bounds derived from historical price data and its statistical properties.
This combination ensures that the forecasts are not purely stochastic but are grounded in historical price behavior, making the model more robust and potentially more accurate in reflecting market conditions.
Drawing toolThis indicator is a simple drawing tool without changing the code!
You need:
1. activate the display of coordinates (Show coordinate input)
You will see a 17 by 17 table with indexes of intersection points, in the format: (x,y)
2. activate the Enable custom drawing input
3. enter the sequence of points that you want to connect into the Coordinate for drawing input in the format: (x,y);(x,y)....
4. select line color and fill color
5. if necessary, activate Curved and Closed
In addition, you can look at some examples
Danger Signals from The Trading MindwheelThe " Danger Signals " indicator, a collaborative creation from the minds at Amphibian Trading and MARA Wealth, serves as your vigilant lookout in the volatile world of stock trading. Drawing from the wisdom encapsulated in "The Trading Mindwheel" and the successful methodologies of legends like William O'Neil and Mark Minervini, this tool is engineered to safeguard your trading journey.
Core Features:
Real-Time Alerts: Identify critical danger signals as they emerge in the market. Whether it's a single day of heightened risk or a pattern forming, stay informed with specific danger signals and a tally of signals for comprehensive decision-making support. The indicator looks for over 30 different signals ranging from simple closing ranges to more complex signals like blow off action.
Tailored Insights with Portfolio Heat Integration: Pair with the "Portfolio Heat" indicator to customize danger signals based on your current positions, entry points, and stops. This personalized approach ensures that the insights are directly relevant to your trading strategy. Certain signals can have different meanings based on where your trade is at in its lifecycle. Blow off action at the beginning of a trend can be viewed as strength, while after an extended run could signal an opportunity to lock in profits.
Forward-Looking Analysis: Leverage the 'Potential Danger Signals' feature to assess future risks. Enter hypothetical price levels to understand potential market reactions before they unfold, enabling proactive trade management.
The indicator offers two different modes of 'Potential Danger Signals', Worst Case or Immediate. Worst Case allows the user to input any price and see what signals would fire based on price reaching that level, while the Immediate mode looks for potential Danger Signals that could happen on the next bar.
This is achieved by adding and subtracting the average daily range to the current bars close while also forecasting the next values of moving averages, vwaps, risk multiples and the relative strength line to see if a Danger Signal would trigger.
User Customization: Flexibility is at your fingertips with toggle options for each danger signal. Tailor the indicator to match your unique trading style and risk tolerance. No two traders are the same, that is why each signal is able to be turned on or off to match your trading personality.
Versatile Application: Ideal for growth stock traders, momentum swing traders, and adherents of the CANSLIM methodology. Whether you're a novice or a seasoned investor, this tool aligns with strategies influenced by trading giants.
Validation and Utility:
Inspired by the trade management principles of Michael Lamothe, the " Danger Signals " indicator is more than just a tool; it's a reflection of tested strategies that highlight the importance of risk management. Through rigorous validation, including the insights from "The Trading Mindwheel," this indicator helps traders navigate the complexities of the market with an informed, strategic approach.
Whether you're contemplating a new position or evaluating an existing one, the " Danger Signals " indicator is designed to provide the clarity needed to avoid potential pitfalls and capitalize on opportunities with confidence. Embrace a smarter way to trade, where awareness and preparation open the door to success.
Let's dive into each of the components of this indicator.
Volume: Volume refers to the number of shares or contracts traded in a security or an entire market during a given period. It is a measure of the total trading activity and liquidity, indicating the overall interest in a stock or market.
Price Action: the analysis of historical prices to inform trading decisions, without the use of technical indicators. It focuses on the movement of prices to identify patterns, trends, and potential reversal points in the market.
Relative Strength Line: The RS line is a popular tool used to compare the performance of a stock, typically calculated as the ratio of the stock's price to a benchmark index's price. It helps identify outperformers and underperformers relative to the market or a specific sector. The RS value is calculated by dividing the close price of the chosen stock by the close price of the comparative symbol (SPX by default).
Average True Range (ATR): ATR is a market volatility indicator used to show the average range prices swing over a specified period. It is calculated by taking the moving average of the true ranges of a stock for a specific period. The true range for a period is the greatest of the following three values:
The difference between the current high and the current low.
The absolute value of the current high minus the previous close.
The absolute value of the current low minus the previous close.
Average Daily Range (ADR): ADR is a measure used in trading to capture the average range between the high and low prices of an asset over a specified number of past trading days. Unlike the Average True Range (ATR), which accounts for gaps in the price from one day to the next, the Average Daily Range focuses solely on the trading range within each day and averages it out.
Anchored VWAP: AVWAP gives the average price of an asset, weighted by volume, starting from a specific anchor point. This provides traders with a dynamic average price considering both price and volume from a specific start point, offering insights into the market's direction and potential support or resistance levels.
Moving Averages: Moving Averages smooth out price data by creating a constantly updated average price over a specific period of time. It helps traders identify trends by flattening out the fluctuations in price data.
Stochastic: A stochastic oscillator is a momentum indicator used in technical analysis that compares a particular closing price of an asset to a range of its prices over a certain period of time. The theory behind the stochastic oscillator is that in a market trending upwards, prices will tend to close near their high, and in a market trending downwards, prices close near their low.
While each of these components offer unique insights into market behavior, providing sell signals under specific conditions, the power of combining these different signals lies in their ability to confirm each other's signals. This in turn reduces false positives and provides a more reliable basis for trading decisions
These signals can be recognized at any time, however the indicators power is in it's ability to take into account where a trade is in terms of your entry price and stop.
If a trade just started, it hasn’t earned much leeway. Kind of like a new employee that shows up late on the first day of work. It’s less forgivable than say the person who has been there for a while, has done well, is on time, and then one day comes in late.
Contextual Sensitivity:
For instance, a high volume sell-off coupled with a bearish price action pattern significantly strengthens the sell signal. When the price closes below an Anchored VWAP or a critical moving average in this context, it reaffirms the bearish sentiment, suggesting that the momentum is likely to continue downwards.
By considering the relative strength line (RS) alongside volume and price action, the indicator can differentiate between a normal retracement in a strong uptrend and a when a stock starts to become a laggard.
The integration of ATR and ADR provides a dynamic framework that adjusts to the market's volatility. A sudden increase in ATR or a character change detected through comparing short-term and long-term ADR can alert traders to emerging trends or reversals.
The "Danger Signals" indicator exemplifies the power of integrating diverse technical indicators to create a more sophisticated, responsive, and adaptable trading tool. This approach not only amplifies the individual strengths of each indicator but also mitigates their weaknesses.
Portfolio Heat Indicator can be found by clicking on the image below
Danger Signals Included
Price Closes Near Low - Daily Closing Range of 30% or Less
Price Closes Near Weekly Low - Weekly Closing Range of 30% or Less
Price Closes Near Daily Low on Heavy Volume - Daily Closing Range of 30% or Less on Heaviest Volume of the Last 5 Days
Price Closes Near Weekly Low on Heavy Volume - Weekly Closing Range of 30% or Less on Heaviest Volume of the Last 5 Weeks
Price Closes Below Moving Average - Price Closes Below One of 5 Selected Moving Averages
Price Closes Below Swing Low - Price Closes Below Most Recent Swing Low
Price Closes Below 1.5 ATR - Price Closes Below Trailing ATR Stop Based on Highest High of Last 10 Days
Price Closes Below AVWAP - Price Closes Below Selected Anchored VWAP (Anchors include: High of base, Low of base, Highest volume of base, Custom date)
Price Shows Aggressive Selling - Current Bars High is Greater Than Previous Day's High and Closes Near the Lows on Heaviest Volume of the Last 5 Days
Outside Reversal Bar - Price Makes a New High and Closes Near the Lows, Lower Than the Previous Bar's Low
Price Shows Signs of Stalling - Heavy Volume with a Close of Less than 1%
3 Consecutive Days of Lower Lows - 3 Days of Lower Lows
Close Lower than 3 Previous Lows - Close is Less than 3 Previous Lows
Character Change - ADR of Last Shorter Length is Larger than ADR of Longer Length
Fast Stochastic Crosses Below Slow Stochastic - Fast Stochastic Crosses Below Slow Stochastic
Fast & Slow Stochastic Curved Down - Both Stochastic Lines Close Lower than Previous Day for 2 Consecutive Days
Lower Lows & Lower Highs Intraday - Lower High and Lower Low on 30 Minute Timeframe
Moving Average Crossunder - Selected MA Crosses Below Other Selected MA
RS Starts Curving Down - Relative Strength Line Closes Lower than Previous Day for 2 Consecutive Days
RS Turns Negative Short Term - RS Closes Below RS of 7 Days Ago
RS Underperforms Price - Relative Strength Line Not at Highs, While Price Is
Moving Average Begins to Flatten Out - First Day MA Doesn't Close Higher
Price Moves Higher on Lighter Volume - Price Makes a New High on Light Volume and 15 Day Average Volume is Less than 50 Day Average
Price Hits % Target - Price Moves Set % Higher from Entry Price
Price Hits R Multiple - Price hits (Entry - Stop Multiplied by Setting) and Added to Entry
Price Hits Overhead Resistance - Price Crosses a Swing High from a Monthly Timeframe Chart from at Least 1 Year Ago
Price Hits Fib Level - Price Crosses a Fib Extension Drawn From Base High to Low
Price Hits a Psychological Level - Price Crosses a Multiple of 0 or 5
Heavy Volume After Significant Move - Above Average and Heaviest Volume of the Last 5 Days 35 Bars or More from Breakout
Moving Averages Begin to Slope Downward - Moving Averages Fall for 2 Consecutive Days
Blow Off Action - Highest Volume, Largest Spread, Multiple Gaps in a Row 35 Bars or More Post Breakout
Late Buying Frenzy - ANTS 35 Bars or More Post Breakout
Exhaustion Gap - Gap Up 5% or Higher with Price 125% or More Above 200sma
Interest Rate DifferentialInterest Rate Differential Indicator
Description:
This Pine Script indicator displays the interest rate spread between two countries, illustrating the differential in 10-year bond yields (or other maturities on the curve). By default, it compares the 10-year bond yield of Germany (DE10Y) with that of the United States (US10Y), for EUR/USD pair analysis. Change the yields to compare other pairs. The spread between the rates of the curve of two countries provides traders and analysts with insights into the carry cost and interest rate dynamics between these economies. The indicator is crucial for assessing the relative strength of the bond market and the economic outlook (including inflation expectations and risk premium) of the selected countries, aiding in trade decisions and market analysis.
Tradução para Português Brasileiro
Título: Indicador de Diferencial de Juros (DE10Y-US10Y)
Descrição:
Este indicador em Pine Script exibe o spread de juros entre dois países, mostrando o diferencial de yields dos títulos de 10 anos (ou de outro vencimento na curva). Por padrão, ele compara o rendimento do título de 10 anos da Alemanha (DE10Y) com o dos Estados Unidos (US10Y), para análise do par EUR/USD. Mude os yields para outros pares. O spread entre as taxas do curva entre 2 países proporciona aos traders e analistas uma visão do custo de carrego e da dinâmica das taxas de juros entre estas economias. O indicador é fundamental para avaliar a força relativa do mercado de títulos e a perspectiva econômica (assim como expectativa de inflação e prêmio de risco) entre os países dos yields selecionados, auxiliando em decisões de trade e análise de mercado.
Fourier Smoothed Hybrid Volume Spread AnalysisIndicator id:
USER;91bdff47320b4284a375f428f683b21e
(only relevant to those that use API requests)
MEANINGFUL DESCRIPTION:
The Fourier Smoothed Hybrid Volume Spread Analysis (FSHVSA) indicator is an innovative trading tool designed to fuse volume analysis with trend detection capabilities, offering traders a comprehensive view of market dynamics.
This indicator stands apart by integrating the principles of the Discrete Fourier Transform (DFT) and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity.
This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise.
The core functionality of the FSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes.
Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points.
It returns 0 when MA of the histogram and EMA of the Price Spread are not align.
HOW TO USE THE INDICATOR:
The FSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0.
ORIGINALITY & USEFULNESS:
The FSHVSA is unique because it applies DFT for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is the meaning of price spread?
In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset.
We are going to use Open-Close spread.
What is Volume spread analysis?
Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction.
What does this mean?
We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend.
What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread ?
It results in a neutral, not trending price action.
Thus the indicator returns 0.
In the next Image you can see that trend is negative on 4h, neutral on 12h and neutral on 1D. That means trend is negative .
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Euler approximation of a spread are taken from aprox library.
Key Features:
Noise Reduction leverages Euler's White noise capabilities for effective Volume smoothing, providing a cleaner and more accurate representation of market dynamics.
Choose between the innovative Double Discrete Fourier Transform (DTF32) and Regular Open & Close price series.
Mathematical equations presented in Pinescript:
Fourier of the real (x axis) discrete:
x_0 = array.get(x, 0) + array.get(x, 1) + array.get(x, 2)
x_1 = array.get(x, 0) + array.get(x, 1) * math.cos( -2 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -2 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -4 * math.pi * _dir / 3 )
x_2 = array.get(x, 0) + array.get(x, 1) * math.cos( -4 * math.pi * _dir / 3 ) - array.get(y, 1) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(x, 2) * math.cos( -8 * math.pi * _dir / 3 ) - array.get(y, 2) * math.sin( -8 * math.pi * _dir / 3 )
Fourier of the imaginary (y axis) discrete:
y_0 = array.get(x, 0) + array.get(x, 1) + array.get(x, 2)
y_1 = array.get(x, 0) + array.get(x, 1) * math.sin( -2 * math.pi * _dir / 3 ) + array.get(y, 1) * math.cos( -2 * math.pi * _dir / 3 ) + array.get(x, 2) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(y, 2) * math.cos( -4 * math.pi * _dir / 3 )
y_2 = array.get(x, 0) + array.get(x, 1) * math.sin( -4 * math.pi * _dir / 3 ) + array.get(y, 1) * math.cos( -4 * math.pi * _dir / 3 ) + array.get(x, 2) * math.sin( -8 * math.pi * _dir / 3 ) + array.get(y, 2) * math.cos( -8 * math.pi * _dir / 3 )
Euler's Smooth with Discrete Furrier approximated Volume.
a = math.sqrt(2) * math.pi / _devided
b = math.cos(math.sqrt(2) * 180 / _devided)
c2 = 2 * math.pow(a, 2) * b
c3 = math.pow(a, 4)
c1 = 1 - 2 * math.pow(a, 2) * math.cos(b) + math.pow(a, 4)
filt := na(filt ) ? 0 : c1 * (w + nz(w )) / 2.0 + c2 * nz(filt ) + c3 * nz(filt )
Usecase:
First option:
Leverage the script to identify Bullish and Bearish trends, shown with green and red triangle.
Combine Different Timeframes to accurately determine market trend.
Second option:
Pull the data with API sockets to automate your trading journey.
plot(close, title="ClosePrice", display=display.status_line)
plot(open, title="OpenPrice", display=display.status_line)
plot(greencon ? 1 : redcon ? -1 : 0, title="position", display=display.status_line)
Use ClosePrice, OpenPrice and "position" titles to easily read and backtest your strategy utilising more than 1 Time Frame.
Indicator id:
USER;91bdff47320b4284a375f428f683b21e
(only relevant to those that use API requests)
Price and Volume Stochastic Divergence [MW]Introduction
This indicator creates signals of interest for entering and exiting long and short positions on equities. It primarily uses up and down trends defined by the change in cumulative volume with some filtering provided by a short period exponential moving average (9 EMA by default).
Settings
Moving Average Period : The moving average over which the cumulative volume delta is calculated. Default: 14
Short Period EMA : The EMA used to represent price action, and is used to generate the EMA Delta line. Default: 27 (3*3*3)
Long Period EMA : The second EMA used to calculate the EMA Delta line. Default: 108 (2*2*3*3*3)
Stochastic K Value : The value used for stochastic curve smoothing. Default: 3
Dot Size : The diameter of the larger indicator. Default: 10
Dot Transparency : The transparency level of the outer ring of the primary BUY/SELL signal. Default: 50 (0 is opaque, 100 is transparent)
Band Distance from 0 to 100 : The upper and lower band distance. Default: 20
Calculations
The cumulative volume delta (CVD) is calculated using candle bodies and wicks. For a red candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks, while Selling Volume is calculated multiplying the volume by the spread percentage of the average of the top and bottom wicks - in addition to the spread percentage of the candle body.
For a green candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks - plus the spread percentage of the candle body - while Selling Volume is calculated using only the spread percentage average of the top and bottom wicks.
Once we have the CVD, we can then perform a stochastic calculation of the CVD value.
stochastic calculation = (current value - lowest value in period) / (highest value in period - lowest value in period)
We’ll do the same stochastic calculation for the short term EMA (27 EMA default) as well as for the difference between the short term and long term EMA.
When the stochastic CVD value is rising from zero and the short term EMA stochastic value equals 100, then it’s a major bullish signal. When the stochastic CVD value is falling from 100 and the short term EMA stochastic value equals 0, then it’s a major bearish signal.
Sometimes, after a bullish or bearish signal, the stochastic CVD will reverse direction triggering a new opposing signal.
How to Interpret
The CVD indicates when there is either more buying than selling or vice versa. A value over 50 for the stochastic CVD curve represents more buying taking place. A value below 50 represents more selling. One might intuitively believe that when there is more buying volume than selling volume that the price would follow suit. This is not always the case.
Most of the time buying volume will precede consistent price movement upwards, and selling volume will precede consistent price movement downwards. When this divergence occurs, the indicator generates a signal. When this divergence begins to fail, and buying or selling volume reverses, then another signal is generated indicating that the buying/selling impulse is headed back into the direction of price action.
These interactions are visually represented on the chart with the coral line that represents CVD, and the yellow line that represents the EMA, or the average price. When the coral line goes up and the yellow line stays down, that’s the BUY signal. When the coral line goes down and the yellow line stays up, that’s the sell signal. When the coral line switches direction, the chart generates another signal showing that volume is moving in a direction that supports the price.
The orange line represents the stochastic representation of the difference between the short EMA (27 by default) and the long EMA (108 by default). EMA differences is a method that can be used to define a trend. When a short term EMA is above a longer term EMA, that may represent a bullish trend. When it is below, that may represent a bearish trend. When all 3 lines are rising or falling in the same direction at the same time, it tends to indicate a movement that has the potential to continue.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
This indicator can be paired with the MW Volume Impulse indicator if it is desired to see the actual buying and selling cumulative volume deltas. Also, in many cases, the BUY and SELL signals tend to correspond with Keltner Bands (ATR Bands) becoming extended. Lastly, volume weighted average price (VWAP) along with other macro events can impact price and negate signals. To view VWAP lines, you may choose to use the Multi VWAP or Multi VWAP for Gaps indicator to help ensure that the signals you see in this indicator are not being affected by VWAP lines.
ZenTrend Price CyclesZenTrend attempts to plot the cycles that occur as the price cycles between the top and bottom of long- and short-term price linear regression channels.
The indicator observes a fast (35-period) and a slow (100-period) linear regression channel and plots their slopes on an oscillator. When the slope of the fast channel crosses above or below the slope of the slow channel, a signal is plotted.
The red line is the slope of the fast channel; blue is the slope of the slow channel
A green dot and background indicates the slope of recent price action has crossed above the slope of long-term price action.
A red dot and background indicates the slope of recent price action has crossed below the slope of long-term price action.
A gray dot indicates the slope of recent price action is slowing. The difference between the long- and short-term slopes is narrowing.
Here are things I look for when observing price cycles
Where does the cross occur? Crosses high above or below the 'zero line' indicate a more extreme change in price channel slopes.
Flat line: crosses that occur while the lines are flat often indicate chop.
"Curve" of the line - a cross that occurs as the slope lines are starting to curve up/down indicates a sharper and more extreme change in price channel slope.
Volume Profile Histogram [SS]I usually (and by usually, I mean the past year xD) release a significant indicator as my Christmas gift to the community on Christmas Eve. Last year, it was the Z-Score buy and sell signal; this year, it's something a little more conventional. So here is this year’s gift—hope you like it! 🎁
Seems like everyone has their take on Volume Profiles (aka SVP or VSP). I decided to create one, and in true Steversteves fashion, you can expect to find all the goodies that come with most of my stuff, including a volume profile presented in a bell-curve/histogram style (chart above) and statistical frequency tables showing the cases by ranges:
And it wouldn't be a true Steversteves indicator without some kind of ATR thing:
So, what does it do?
At the end of the day, it is a form of an SVP indicator. However, it is meant to operate on a larger scale, sorting volume in a traditional bell-curve style. In addition to displaying volume, it breaks down buying vs. selling volume. Selling volume is classified as such when the open is greater than close, while buying is when close is greater than open. This breakdown allows you to see the distribution, by price range, of where selling and buying occur.
This permits the indicator to provide 2 Points of Control (POCs). A POC is defined as an area of high volume activity. Because buying and selling volumes are broken down into two, we can identify areas with high selling and areas with high buying. Sometimes they coincide, sometimes they differ.
If we look at SQQQ, for example:
We can see that the bearish point of control is one point below the bullish POC. This is interesting because it essentially shows where people may be "panic selling" or setting their stop-outs. If SQQQ drops below 18.8, then it's likely to trigger panic selling, as indicated by the histogram.
Conversely, we can observe that traders tend to position long between $18 and $24. The POC is noted in the stats table and also displayed on the chart. Bullish POC is shown in purple, bearish in yellow. These, of course, can be toggled off.
The Frequency Table:
The frequency table shows how many observations were obtained in each price range. The histogram illustrates the cumulative volume traded, while the frequency simply counts how many cases occurred over the lookback period.
ATR Range Analytics by Volume:
The indicator also has the ability to display range analytics by volume. When you toggle on the range analytics by volume option, a range chart will appear:
www.tradingview.com
The range chart goes from the minimum recorded volume to the maximum recorded volume in the period, showing the average range and direction associated with this volume. This is crucial to pay attention to because not all stocks behave the same way.
For example, in the chart above (AMD), we can see that low volume produces a general bearish bias, and high volume produces a general bullish bias. However, if we look at the range analytics for SPY:
Low volume has the inverse effect. Low volume is associated with a more bullish bias, and high volume indicates a more bearish bias. In the ATR chart, the threshold volume to transition from bullish bias to bearish bias is approximately > 78,607,268 traded shares.
The Stats Table:
The stats table can be toggled on or off. It simply displays the POCs and the time range for the VSP. The default time range is 1 trading year (252 days), assuming you are on the daily timeframe. However, you can use this on any timeframe.
The percentages displayed in the histogram is the cumulative percent of buying and selling volume independently. So when you see the percentage on the selling histogram, its the percent of cumulative selling only. Same for the buying.
And that's the indicator! I hope you enjoy it. Let me know your thoughts. I hope you all have safe holidays, a Merry Christmas for you North Americans, and a Happy Christmas for you UKers, and whatever else you celebrate/care about and do! Safe trades, everyone, and enjoy your holidays! 🎁🎄🎄🎄⭐⭐⭐ 🕎 🕎 🕎
savitzkyGolay, KAMA, HPOverview
This trading indicator integrates three distinct analytical tools: the Savitzky-Golay Filter, Kaufman Adaptive Moving Average (KAMA), and Hodrick-Prescott (HP) Filter. It is designed to provide a comprehensive analysis of market trends and potential trading signals.
Components
Hodrick-Prescott (HP) Filter
Purpose: Smooths out the price data to identify the underlying trend.
Parameters: Lambda: Controls the smoothness. Range: 50 to 1600.
Impact of Parameters:
Increasing Lambda: This makes the trend line more responsive to short-term market fluctuations, suitable for short-term analysis. A higher Lambda value decreases the degree of smoothing, making the trend line follow recent market movements more closely.
Decreasing Lambda: A lower Lambda value makes the trend line smoother and less responsive to short-term market fluctuations, ideal for longer-term trend analysis. Decreasing Lambda increases the degree of smoothing, thereby filtering out minor market movements and focusing more on the long-term trend.
Kaufman Adaptive Moving Average (KAMA):
Purpose: An adaptive moving average that adjusts to price volatility.
Parameters: Length, Fast Length, Slow Length: Define the sensitivity and adaptiveness of KAMA.
Impact of Parameters:
Adjusting Length affects the base period for efficiency ratio, altering the overall sensitivity.
Fast Length and Slow Length control the speed of KAMA’s adaptation. A smaller Fast Length makes KAMA more sensitive to price changes, while a larger Slow Length makes it less sensitive.
Savitzky-Golay Filter:
Purpose: Smooths the price data using polynomial regression.
Parameters: Window Size: Determines the size of the moving window (7, 9, 11, 15, 21).
Impact of Parameters:
A larger Window Size results in a smoother curve, which is more effective for identifying long-term trends but can delay reaction to recent market changes.
A smaller Window Size makes the curve more responsive to short-term price movements, suitable for short-term trading strategies.
General Impact of Parameters
Adjusting these parameters can significantly alter the signals generated by the indicator. Users should fine-tune these settings based on their trading style, the characteristics of the traded asset, and market conditions to optimize the indicator's performance.
Signal Logic
Buy Signal: The trend from the HP filter is below both the KAMA and the Savitzky-Golay SMA, and none of these indicators are flat.
Sell Signal: The trend from the HP filter is above both the KAMA and the Savitzky-Golay SMA, and none of these indicators are flat.
Usage
Due to the combination of smoothing algorithms and adaptability, this indicator is highly effective at identifying emerging trends for both initiating long and short positions.
IMPORTANT : Although the code and user settings incorporate measures to limit false signals due to lateral (sideways) movement, they do not completely eliminate such occurrences. Users are strongly advised to avoid signals that emerge during simultaneous lateral movements of all three indicators.
Despite the indicator's success in historical data analysis using its signals alone, it is highly recommended to use this code in combination with other indicators, patterns, and zones. This is particularly important for determining exit points from positions, which can significantly enhance trading results.
Limitations and Recommendations
The indicator has shown excellent performance on the weekly time frame (TF) with the following settings:
Savitzky-Golay (SG): 11
Hodrick-Prescott (HP): 100
Kaufman Adaptive Moving Average (KAMA): 20, 2, 30
For the monthly TF, the recommended settings are:
SG: 15
HP: 100
KAMA: 30, 2, 35
Note: The monthly TF is quite variable. With these settings, there may be fewer signals, but they tend to be more relevant for long-term investors. Based on a sample of 40 different stocks from various countries and sectors, most exhibited an average trade return in the thousands of percent.
It's important to note that while these settings have been successful in past performance, market conditions vary and past performance is not indicative of future results. Users are encouraged to experiment with these settings and adjust them according to their individual needs and market analysis.
As this is my first developed trading indicator, I am very open to and appreciative of any suggestions or comments. Your feedback is invaluable in helping me refine and improve this tool. Please feel free to share your experiences, insights, or any recommendations you may have.
OI Visible Range Ladder [Kioseff Trading]Hello!
This Script “OI Visible Range Ladder” calculates open interest profiles for the visible range alongside an OI ladder for the visible period!
Features
OI Profile Anchored to Visible Range
OI Ladder Anchored to Visible Range
Standard POC and Value Area Lines, in Addition to Separated POCs and Value Area Lines for each category of OI x Price
Configurable Value Area Targets
Curved Profiles
Up to 9999 Profile Rows per Visible Range
Stylistic Options for Profiles
Up to 9999 volume profile levels (Price levels) can be calculated for each profile, thanks to the new polyline feature, allowing for less aggregation / more precision of open interest at price.
The image above shows primary functionality!
Green profiles = Up OI / Up Price
Yellow profiles = Down OI / Up Price
Purple profiles = Up OI / Down Price
Red profiles = Down OI / Down Price
The image above shows POCs for each OI x Price category!
Profiles can be anchored on the left side for a more traditional look.
The indicator is robust enough to calculate on “small price periods”, or for a price period spanning your entire chart fully zoomed out!
That’s about it :D
This indicator is Part of a series titled “Bull vs. Bear” - a suite of profile-like indicators.
Thanks for checking this out!
If you have any suggestions please feel free to share!
Bull Vs Bear Visible Range VP [Kioseff Trading]Hello!
This Script “Bull vs Bear Visible Range VP” Calculates Bull & Bear Volume Profiles for the Visible Range Alongside a Delta Ladder for the Visible Period!
Features
Volume Profile Anchored to Visible Range
Delta Ladder Anchored to Visible Range
Bull vs Bear Profiles!
Standard Poc and Value Area Lines, in Addition to Separated POCs and Value Area Lines for Bull Profiles and Bear Profiles
Configurable Value Area Target
Curved Profiles
Up to 9999 Profile Rows per Visible Range
Stylistic Options for Profiles
This Script Generates Bull vs. Bear Volume Profiles for the Visible Range!
Up to 9999 Volume Profile Levels (Price Levels) Can Be Calculated for Each Profile, Thanks to the New Polyline Feature, Allowing For Less Aggregation / More Precision of Volume at Price and Volume Delta.
Bull vs Bear Profiles
The Image Above Shows Primary Functionality!
Green Profiles = Buying Volume
Red Profiles = Selling Volume
Bullish & Bearish Pocs for the Visible Range Are Displayable!
Profiles Can Be Anchored on the Left Side for a More Traditional Look.
The indicator is robust enough to calculate on "small price periods", or for a price period spanning your entire chart fully zoomed out!
That’s About It :D
This Indicator Is Part of a Series Titled “Bull vs. Bear” - A Suite of Profile-Like Indicators I Will Be Releasing Over Coming Days. Thanks for Checking This Out!
If You Have Any Suggestions Please Feel Free to Share!
Zig-Zag Open Interest Footprint [Kioseff Trading]Hello!
This script "Zig Zag Open Interest Footprint" calculates open interest x price values for zig zag trends!
Features
Open interest footprints anchored to zig zag trends
Summed OI x price level footprints
Total OI (for each category) for the entire trend shown
Standard POC lines, in addition to separated POC lines for each category of open interest x price possibility
Up to 9999 profile rows per zigzag trend
Stylistic options for profiles
Configurable zig zag - footprints generated for small to large trends
The zigzag indicator is configurable as normal; minor and major trend volume footprints are calculable. This indicator can be thought of as "Open Interest Footprint for Trends''.
Up to 9999 open interest levels (price levels) can be calculated for each profile, thanks to the new polyline feature, allowing for less aggregation / more precision of open interest at price.
Zig Zag OI Footprints
The image above shows primary functionality!
Green = Higher OI + Higher Price
Yellow = Lower OI + Higher Price
Purple = Higher OI + Lower Price
Red = Lower OI + Lower Price
Profiles are generated for each trend identified by the zigzag indicator.
The image above shows the indicator calculating open interest x price for specific price blocks on the footprint. Aggregate open interest for the identified trend is displayed over the profile!
Neon highlighted values correspond to the highest open interest change for the category. This is a configurable option :D
The image above shows POC lines for each category of open interest x price!
Additionally, you can select to show a single POV for footprint - the single level the greatest amount of OI change occurred.
The indicator is robust enough to calculate on "long zig zags" and "short zig zags"; curved profiles can also be used!
The image above shows key levels, each OI footprint, and summed OI values for the current trend!
That's about it :D
This indicator is part of a series titled "Bull vs. Bear" - a suite of profile-like indicators I will be releasing over the coming days. Thanks for checking this out!
If you have any suggestions please feel free to share!
Zig-Zag Volume Profile (Bull vs. Bear) [Kioseff Trading]Hello!
Thank you @Pinecoders and @TradingView for putting polylines in production and making this viable!!
This script "Zig Zag Volume Profile" implements the polyline feature for Pine Script!
Features
Volume Profile anchored to zig zag trends
Bull vs Bear profiles!
Delta x price level
Standard POC and value area lines, in addition to separated POCs and value area lines for bull profiles and bear profiles
Up to 9999 profile rows per zigzag trend
Stylistic options for profiles
Configurable zig zag - profiles generated for small to large trends
Polylines!
This script generates Bull vs. Bear volume profiles for zig zag trends!
The zigzag indicator is configurable as normal; minor and major trend volume profiles are calculable. This indicator can be thought of as "Volume Profile/Delta for Trends''.
Up to 9999 volume profile levels (price levels) can be calculated for each profile, thanks to the new polyline feature, allowing for less aggregation / more precision of volume at price and volume delta.
Zig Zag Bull Vs Bear Profiles
The image above shows primary functionality!
Green profiles = buying volume
Red profiles = selling volume
Profiles are generated for each trend identified by the zigzag indicator.
The image above shows the indicator calculating volume delta for specific price blocks on the profile. Aggregate volume delta for the identified trend is displayed over the profile!
The image above shows Bull Profile POC lines and value area lines. Bear Profile POC lines and value area lines are also shown!
All colors and transparencies are configurable to the user's liking :D
Additionally, you can select to have the profiles drawn on contrasting sides. Bull Profile on left and Bear Profile on right.
For a more traditional look - you can select to draw the Bull & Bear profiles on the same x-point.
The indicator is robust enough to calculate on "long zig zags" and "short zig zags"; curved profiles can also be used!
The image above exemplifies usage of the indicator!
Bull & Bear volume profiles are calculated for trends on the 30-second timeframe.
The image above shows a more "utilitarian" presentation of the profiles. Once more, line and linefill colors/transparencies are all customizable; the indicator can look however you would like it to!
The image above shows key levels, the Bull vs. Bear profile, and volume delta for the current trend!
That's about it :D
This indicator is part of a series titled "Bull vs. Bear" - a suite of profile-like indicators I will be releasing over coming days. Thanks for checking this out!
Of course, a big thank you to @RicardoSantos for his MathOperator library that I use in every script.
If you have any suggestions please feel free to share!
ZWAP (ZigZag Anchored VWAP) [Kioseff Trading]Hello!
Quick script showcasing the new polyline function for Pine Script!
Features
Up to 100 high/low pivot points auto anchored VWAP
Visible range auto anchored VWAP
Curved ZigZag (Adjustable!)
With the new polyline function, auto-anchored VWAP at specific price points is more viable.
When using line.new() only 500 lines can exist on the chart concurrently and, since VWAP is calculated on every update, a "proper" VWAP drawn using line.new() can extend 500 bars at most, to which no additional VWAP lines can be drawn after.
Of course, when using the plot() function a VWAP line will draw on every bar; however, this method isn't highly compatible with auto-anchoring VWAP lines.
However!
A polyline, from beginning to end irrespective of the number of coordinates used, constitutes 1 polyline; 100 can exist simultaneously with 10,000 xy coordinates per line.
The image above shows an attempt to draw the same auto-anchored VWAP lines using the line.new() function. Not an ideal outcome!
The image above shows the same attempt using the polyline.new() function!
Very nice (:
The image above shows the indicator auto anchoring to zig zag turning points.
Subsequent to a new anchoring, VWAP is calculated for the following bars - up to the current bar.
Thank you for checking this out; if you have any ideas to spice it up feel free to comment!
ROCkin RSIROCkin RSI Indicator
Overview
The "ROCkin RSI" indicator combines the traditional Relative Strength Index (RSI) with an innovative approach using the Rate of Change (ROC) to offer a new way to visualize and interpret market momentum. By averaging the slope of the RSI over time and allowing for different types of moving averages, this indicator aims to help traders identify trending and reversal patterns more efficiently.
Features
RSI Calculations: The core of the indicator is based on the standard Relative Strength Index, an oscillator that measures the speed and change of price movements. The RSI oscillates between 0 and 100 and is usually used to identify overbought or oversold conditions.
Rate of Change of Price (ROC): Instead of simply plotting the RSI, this indicator calculates the Rate of Change of the closing price, essentially looking at how steep the RSI curve is over a user-defined period.
Smoothing: To reduce noise and make the curve smoother, the slope of the RSI is averaged over a given number of periods, which can either be a Simple Moving Average (SMA) or an Exponential Moving Average (EMA).
Column Plots: The smoothed RSI slope is plotted as columns, where the color of the columns (red or green) indicates whether the slope is positive or negative.
Optional RSI Moving Average: The indicator also offers an optional feature to plot a moving average of the smoothed RSI slope, aiding in trend identification.
Inputs
RSI Periods: The number of periods used to calculate the RSI.
Slope Periods: The number of periods used for calculating the Rate of Change.
Average Periods: The number of periods used for smoothing the RSI slope.
Type of Average: Choose between EMA (Exponential Moving Average) and SMA (Simple Moving Average) for smoothing.
Show RSI Moving Average: Toggle this to either show or hide the moving average of the smoothed RSI slope.
Moving Average Period: The period used for calculating the RSI Moving Average.
Moving Average Type: Choose between EMA and SMA for the RSI Moving Average.
How to Interpret
Positive Slope (Red Columns): Indicates upward momentum in the RSI, which may imply a bullish trend.
Negative Slope (Green Columns): Indicates downward momentum in the RSI, suggesting a possible bearish trend.
RSI Moving Average: Acts as a signal line to confirm the trend. When the smoothed RSI slope is above its moving average, it confirms the bullish trend, and when it's below, it confirms the bearish trend.
Practical Use
Entry/Exit Signals: Consider entering a long position when the columns of the green histogram cross above the moving average. Conversely, consider entering a short position when the columns cross under when red. The higher the columns the more likely the trade will be a good one.
Fine-Tuning and Optimization
It's crucial to understand that the default settings might not be optimal for all trading scenarios. The effectiveness of the ROCkin RSI indicator can vary based on the asset you're trading, the market conditions, and your trading style. Therefore, it's highly recommended to play with the settings and study the historical performance on the chart to grasp how the indicator behaves.
By experimenting with different periods for RSI, the Rate of Change, and the moving averages, you can tailor the indicator to better suit your needs. Studying how the indicator would have performed in the past can help you understand its potential strengths and weaknesses. Once you've got a feel for how it operates, you can then optimize the settings to align with your trading strategy and risk tolerance.
Alxuse Supertrend 4EMA Buy and Sell for tutorialAll abilities of Supertrend, moreover :
Drawing 4 EMA band & the ability to change values, change colors, turn on/off show.
Sends Signal Sell and Buy in multi timeframe.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Supertrend with a simple EMA Filter can improve the performance of the signals during a strong trend.
For detecting the continuation of the downward and upward trend we can use 4 EMA colors.
In the upward trend , the EMA lines are in order of green, blue, red, yellow from bottom to top.
In the downward trend, the EMA lines are in order of yellow, red, blue, green from bottom to top.
How it works:
x1 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA3, MA4)
x2 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA2, MA3)
x3 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA1, MA2)
y1 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA3, MA4)
y2 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA2, MA3)
y3 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA1, MA2)
Red triangle = x1 or x2 or x3
Green triangle = y1 or y2 or y3
Long = BUY signal and followed by a Green triangle
Exit Long = SELL signal
Short = SELL signal and followed by a Red triangle
Exit Short = BUY signal
It is also possible to get help from the Stochastic RSI and MACD indicators for confirmation.
For receiving a signal with these two conditions or more conditions, i am making a video tutorial that I will release soon.
Supertrend
Definition
Supertrend is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility. It can be used to detect changes in trend direction and to position stops.
The basics
The Supertrend is a trend-following indicator. It is overlaid on the main chart and their plots indicate the current trend. A Supertrend can be used with varying periods (daily, weekly, intraday etc.) and on varying instruments.
The Supertrend has several inputs that you can adjust to match your trading strategy. Adjusting these settings allows you to make the indicator more or less sensitive to price changes.
For the Supertrend inputs, you can adjust atrLength and multiplier:
the atrLength setting is the lookback length for the ATR calculation;
multiplier is what the ATR is multiplied by to offset the bands from price.
When the price falls below the indicator curve, it turns red and indicates a downtrend. Conversely, when the price rises above the curve, the indicator turns green and indicates an uptrend. After each close above or below Supertrend, a new trend appears.
Summary
The Supertrend helps you make the right trading decisions. However, there are times when it generates false signals. Therefore, it is best to use the right combination of several indicators. Like any other indicator, Supertrend works best when used with other indicators such as MACD, Parabolic SAR, or RSI.
Exponential Moving Average
Definition
The Exponential Moving Average (EMA) is a specific type of moving average that points towards the importance of the most recent data and information from the market. The Exponential Moving Average is just like it’s name says - it’s exponential, weighting the most recent prices more than the less recent prices. The EMA can be compared and contrasted with the simple moving average.
Similar to other moving averages, the EMA is a technical indicator that produces buy and sell signals based on data that shows evidence of divergence and crossovers from general and historical averages. Additionally, the EMA tries to amplify the importance that the most recent data points play in a calculation.
It is common to use more than one EMA length at once, to provide more in-depth and focused data. For example, by choosing 10-day and 200-day moving averages, a trader is able to determine more from the results in a long-term trade, than a trader who is only analyzing one EMA length.
It’s best to use the EMA when for trending markets, as it shows uptrends and downtrends when a market is strong and weak, respectively. An experienced trader will know to look both at the line the EMA projects, as well as the rate of change that comes from each bar as it moves to the next data point. Analyzing these points and data streams correctly will help the trader determine when they should buy, sell, or switch investments from bearish to bullish or vice versa.
Short-term averages, on the other hand, is a different story when analyzing Exponential Moving Average data. It is most common for traders to quote and utilize 12- and 26-day EMAs in the short-term. This is because they are used to create specific indicators. Look into Moving Average Convergence Divergence (MACD) for more information. Similarly, the 50- and 200-day moving averages are most common for analyzing long-term trends.
Moving averages can be very useful for traders using technical analysis for profit. It is important to identify and realize, however, their shortcomings, as all moving averages tend to suffer from recurring lag. It is difficult to modify the moving average to work in your favor at times, often having the preferred time to enter or exit the market pass before the moving average even shows changes in the trend or price movement for that matter.
All of this is true, however, the EMA strives to make this easier for traders. The EMA is unique because it places more emphasis on the most recent data. Therefore, price movement and trend reversals or changes are closely monitored, allowing for the EMA to react quicker than other moving averages.
Limitations
Although using the Exponential Moving Average has a lot of advantages when analyzing market trends, it is also uncertain whether or not the use of most recent data points truly affects technical and market analysis. In addition, the EMA relies on historical data as its basis for operating and because news, events, and other information can change rapidly the indicator can misinterpret this information by weighting the current prices higher than when the event actually occurred.
Summary
The Exponential Moving Average (EMA) is a moving average and technical indicator that reflects and projects the most recent data and information from the market to a trader and relies on a base of historical data. It is one of many different types of moving averages and has an easily calculable formula.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
Paytience DistributionPaytience Distribution Indicator User Guide
Overview:
The Paytience Distribution indicator is designed to visualize the distribution of any chosen data source. By default, it visualizes the distribution of a built-in Relative Strength Index (RSI). This guide provides details on its functionality and settings.
Distribution Explanation:
A distribution in statistics and data analysis represents the way values or a set of data are spread out or distributed over a range. The distribution can show where values are concentrated, values are absent or infrequent, or any other patterns. Visualizing distributions helps users understand underlying patterns and tendencies in the data.
Settings and Parameters:
Main Settings:
Window Size
- Description: This dictates the amount of data used to calculate the distribution.
- Options: A whole number (integer).
- Tooltip: A window size of 0 means it uses all the available data.
Scale
- Description: Adjusts the height of the distribution visualization.
- Options: Any integer between 20 and 499.
Round Source
- Description: Rounds the chosen data source to a specified number of decimal places.
- Options: Any whole number (integer).
Minimum Value
- Description: Specifies the minimum value you wish to account for in the distribution.
- Options: Any integer from 0 to 100.
- Tooltip: 0 being the lowest and 100 being the highest.
Smoothing
- Description: Applies a smoothing function to the distribution visualization to simplify its appearance.
- Options: Any integer between 1 and 20.
Include 0
- Description: Dictates whether zero should be included in the distribution visualization.
- Options: True (include) or False (exclude).
Standard Deviation
- Description: Enables the visualization of standard deviation, which measures the amount of variation or dispersion in the chosen data set.
- Tooltip: This is best suited for a source that has a vaguely Gaussian (bell-curved) distribution.
- Options: True (enable) or False (disable).
Color Options
- High Color and Low Color: Specifies colors for high and low data points.
- Standard Deviation Color: Designates a color for the standard deviation lines.
Example Settings:
Example Usage RSI
- Description: Enables the use of RSI as the data source.
- Options: True (enable) or False (disable).
RSI Length
- Description: Determines the period over which the RSI is calculated.
- Options: Any integer greater than 1.
Using an External Source:
To visualize the distribution of an external source:
Select the "Move to" option in the dropdown menu for the Paytience Distribution indicator on your chart.
Set it to the existing panel where your external data source is placed.
Navigate to "Pin to Scale" and pin the indicator to the same scale as your external source.
Indicator Logic and Functions:
Sinc Function: Used in signal processing, the sinc function ensures the elimination of aliasing effects.
Sinc Filter: A filtering mechanism which uses sinc function to provide estimates on the data.
Weighted Mean & Standard Deviation: These are statistical measures used to capture the central tendency and variability in the data, respectively.
Output and Visualization:
The indicator visualizes the distribution as a series of colored boxes, with the intensity of the color indicating the frequency of the data points in that range. Additionally, lines representing the standard deviation from the mean can be displayed if the "Standard Deviation" setting is enabled.
The example RSI, if enabled, is plotted along with its common threshold lines at 70 (upper) and 30 (lower).
Understanding the Paytience Distribution Indicator
1. What is a Distribution?
A distribution represents the spread of data points across different values, showing how frequently each value occurs. For instance, if you're looking at a stock's closing prices over a month, you may find that the stock closed most frequently around $100, occasionally around $105, and rarely around $110. Graphically visualizing this distribution can help you see the central tendencies, variability, and shape of your data distribution. This visualization can be essential in determining key trading points, understanding volatility, and getting an overview of the market sentiment.
2. The Rounding Mechanism
Every asset and dataset is unique. Some assets, especially cryptocurrencies or forex pairs, might have values that go up to many decimal places. Rounding these values is essential to generate a more readable and manageable distribution.
Why is Rounding Needed? If every unique value from a high-precision dataset was treated distinctly, the resulting distribution would be sparse and less informative. By rounding off, the values are grouped, making the distribution more consolidated and understandable.
Adjusting Rounding: The `Round Source` input allows users to determine the number of decimal places they'd like to consider. If you're working with an asset with many decimal places, adjust this setting to get a meaningful distribution. If the rounding is set too low for high precision assets, the distribution could lose its utility.
3. Standard Deviation and Oscillators
Standard deviation is a measure of the amount of variation or dispersion of a set of values. In the context of this indicator:
Use with Oscillators: When using oscillators like RSI, the standard deviation can provide insights into the oscillator's range. This means you can determine how much the oscillator typically deviates from its average value.
Setting Bounds: By understanding this deviation, traders can better set reasonable upper and lower bounds, identifying overbought or oversold conditions in relation to the oscillator's historical behavior.
4. Resampling
Resampling is the process of adjusting the time frame or value buckets of your data. In the context of this indicator, resampling ensures that the distribution is manageable and visually informative.
Resample Size vs. Window Size: The `Resample Resolution` dictates the number of bins or buckets the distribution will be divided into. On the other hand, the `Window Size` determines how much of the recent data will be considered. It's crucial to ensure that the resample size is smaller than the window size, or else the distribution will not accurately reflect the data's behavior.
Why Use Resampling? Especially for price-based sources, setting the window size around 500 (instead of 0) ensures that the distribution doesn't become too overloaded with data. When set to 0, the window size uses all available data, which may not always provide an actionable insight.
5. Uneven Sample Bins and Gaps
You might notice that the width of sample bins in the distribution is not uniform, and there can be gaps.
Reason for Uneven Widths: This happens because the indicator uses a 'resampled' distribution. The width represents the range of values in each bin, which might not be constant across bins. Some value ranges might have more data points, while others might have fewer.
Gaps in Distribution: Sometimes, there might be no data points in certain value ranges, leading to gaps in the distribution. These gaps are not flaws but indicate ranges where no values were observed.
In conclusion, the Paytience Distribution indicator offers a robust mechanism to visualize the distribution of data from various sources. By understanding its intricacies, users can make better-informed trading decisions based on the distribution and behavior of their chosen data source.
Standardized MACD Heikin-Ashi TransformedThe Standardized MACD Heikin-Ashi Transformed (St. MACD) is an advanced indicator designed to overcome the limitations of the traditional MACD. It offers a more robust and standardized measure of momentum, making it comparable across different timeframes and securities. By incorporating the Heikin-Ashi transformation, the St. MACD provides a smoother visualization of trends and potential reversals, enhancing its utility for traders seeking a clearer view of the underlying market direction.
Methodology:
The calculation of St. MACD begins with the traditional MACD, which computes the difference between two exponential moving averages (EMAs) of the price. To address the issue of non-comparability across assets, the St. MACD normalizes its values using the exponential average of the price's height. This normalization process ensures that the indicator's readings are not influenced by the absolute price levels, allowing for objective and quantitatively defined comparisons of momentum strength.
Furthermore, St. MACD utilizes the Heikin-Ashi transformation, which involves deriving candles from the price data. These Heikin-Ashi candles provide a smoother representation of trends and help filter out noise in the market. A predictive curve of Heikin-Ashi candles within the St. MACD turns blue or red, indicating the prevailing trend direction. This feature enables traders to easily identify trend shifts and make better informed trading decisions.
Advantages:
St. MACD offers several key advantages over the traditional MACD-
Standardization: By normalizing the indicator's values, St. MACD becomes comparable across different assets and timeframes. This makes it a valuable tool for traders analyzing various markets and seeking consistent momentum measurements.
Heikin-Ashi Transformation: The integration of the Heikin-Ashi transformation smoothes out the indicator's fluctuations and enhances trend visibility. Traders can more easily identify trends and potential reversal points, improving their market analysis.
Quantifiable Momentum: St. MACD's key levels represent the strength of momentum, providing traders with a quantifiable framework to gauge the intensity of market movements. This feature helps identify periods of increased or decreased momentum.
Utility:
The St. MACD indicator offers versatile utility for traders-
Trend Identification: Traders can use the color-coded predictive curve of Heikin-Ashi candles to swiftly determine the prevailing trend direction. This aids in identifying potential entry and exit points in the market.
Reversal Signals: Colored extremes within the St. MACD signal potential price reversals, alerting traders to potential turning points in the market. This assists in making timely decisions during market inflection points.
Overbought/Oversold Conditions: The histogram version of St. MACD can be used in conjunction with the bands to detect short-term overbought or oversold market conditions, allowing traders to adjust their strategies accordingly.
In conclusion, this tool addresses the limitations of the traditional MACD by providing a standardized and comparable momentum indicator. Its incorporation of the Heikin-Ashi transformation enhances trend visibility and assists traders in making more informed decisions. With its quantifiable momentum measurements and various utility features, the St. MACD is a valuable tool for traders seeking a clearer and more objective view of market trends and reversals.
Key Features:
Display Modes: MACD, Histogram or Hybrid
Reversion Triangles by adjustable thresholds
Bar Coloring Methods: MidLine, Candles, Signal Cross, Extremities, Reversions
Example Charts:
-Traditional limitations-
-Comparisons across time and securities-
-Showcase-
See Also:
-Other Heikin-Ashi Transforms-
MA Slope : New Method1 . Introduction
Hello, traders.
This indicator is designed to measure the slope of a moving average line.
I imagine many of you who use Pine Script have struggled with this; measuring the slope of a moving average line can be quite challenging.
Firstly, this is because while the x-axis is fixed to the 'number of candles', the price scale on the y-axis can be adjusted freely.
Secondly, while the concept of differentiation could simplify the measurement process, the resulting value will differ from the conventional derivative we are familiar with since 'delta x' is fixed to '1'.
Consequently, I've put a lot of thought into how to configure the x-axis and y-axis in order to measure a slope that aligns with our perception of 'slope'.
After some reflection, I, like many others, realized that many people measure the slope based on the pivot of the moving average line.
This indicator is the product of that reflection.
2. Description
A. Setting
First, select the moving average line for which you want to check the slope. While SMA is commonly used, T3 is set as the default because it best visualizes the slope.
If you check 'Show MA Slope Average Pivot Range?' in the input window, it displays the average of the recent 30 slope pivot highs and pivot lows.
In other words, it shows 'On average, this level of slope was produced in the recent 30 waves.'
B. Usage
A cross from 0 in the slope indicates a 'reversal in the slope of the curve', which is the most crucial value when observing the slope.
Thus, fundamentally, it's important to look at the points where the slope becomes "0". Furthermore, when the slope starts to curve after rising, it signifies a change in acceleration, suggesting an imminent slope reversal.
(Note that acceleration was omitted from the indicator representation due to its tendency to overly complicate the data.)
While a shorter length of the moving average line may provide more useful slope data for actual trading, a less smooth moving average line may cross around 0 too often, making it less useful.
Therefore, it's crucial to adjust the 'Smoothing Length' in the input values to find a value that you believe is appropriate.
3. Conclusion
I always contemplate how to find a value in Pine Script that is similar to the perceived slope.
I made this script thinking that it might be a novel approach, but there are still many areas that need improvement.
If you have any innovative ideas about the slope, please feel free to provide feedback anytime.
Thank you.
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1. 서론
트레이더 여러분 안녕하세요. 이 지표는 이동평균선의 기울기를 측정하는 지표입니다.
아마 파인스크립트를 다루는 많은 분들이 같은 고민을 하셨을 것 같은데, 이동평균선의 기울기를 측정하는 것은 매우 어렵습니다.
그 이유로 첫번째는 x축은 '캔들 갯수'로 고정되어있는 반면, y축의 가격 스케일은 유동적으로 바꿀 수 있기 때문입니다.
두번째로는, 미분 개념을 이용하면 훨씬 수월하게 구할 수 있을테지만, 델타x가 '1'로 고정되어있기 때문에 우리가 알고있는 미분과 다른 값이 나옵니다.
따라서 x축과 y축을 어떻게 하면 실제 우리가 인식하는 '기울기'에 가깝도록 구성할 수 있을지에 대해 고민해보았습니다.
고민해본 결과 저 역시 그러하고, 많은 사람들이 이동평균선의 피벗을 기준으로 기울기를 측정한다는 사실을 알게되었습니다.
이 지표는 그 고민의 결과물입니다.
2. 내용 설명
A. 셋팅
먼저, 기울기를 확인하고싶은 이동평균선을 선택해주세요.
일반적으로 SMA를 많이 보시겠지만, T3가 기울기로 표현할 때 가장 아름다운 모습이 나오기 때문에 기본 설정을 T3로 설정했습니다.
Input창에 있는 'Show MA Slope Average Pivot Range?'를 체크하면, 최근 30개의 기울기 피벗 하이와 피벗 로우의 평균을 보여줍니다.
즉, '평균적으로, 최근 30개의 파동에서는 이 정도의 기울기가 만들어졌다'라는 것을 보여줍니다
B. 사용법
기울기가 0에서 크로스 된다는 것은, "곡선의 기울기가 반전"된다는 것이기에 기울기를 봄에 있어서 가장 중요한 값입니다. 따라서 가장 기본적으로는, 기울기가 "0"이 되는 곳을 보는 것이 중요하고
또 기울기가 올라갔다 꺾이기 시작할 때는, 가속도가 바뀌고 있다는 뜻이므로, 곧 기울기가 반전될 것을 의미합니다.
(다만 가속도를 지표로 표현하기엔, 너무나도 데이터가 지저분해져서 생략하였습니다)
이동평균선의 길이를 짧게 할수록 더 실제 트레이딩에 유용한 기울기 데이터를 얻을 수 있으나,
부드럽지 못한 이동평균선은 기울기가 0 근처에서 크로스 되는 모습이 지나치게 많이 나올 것이기에 유용하지 않을 수 있습니다.
따라서, input값에 있는 'Smoothing Length'를 조절해가면서 자신이 생각하기에 맞는 값을 고르는 것이 중요합니다.
3. 맺음말
파인스크립트에서 어떻게하면 실제 인식하는 기울기와 유사한 값을 찾을 수 있을까를 항상 고민합니다. 나름 새로운 접근방법이라 생각해서 이렇게 스크립트로 만들었으나, 여전히 아쉬운 부분이 많이 존재합니다.
기울기에 대한 좋은 아이디어가 있다면 언제든 피드백 해주세요.
감사합니다.
