SST Table NewData Table for Update GTT Orders in Stocks....
Updated GTT Order details for SST , also added Relative Strength of Stock compared with NIFTY Index for 55 Days (3 Months) period.
RS line plotted on chart… taken reference of close price of day candle… just a bigger picture of actual RS indicator plotted on chart itself... RS line in red color means below zero line (negative) and green color means above zero line (positive).
Added code for checking RS value on chart for any previous day.
Cari dalam skrip untuk " TABLE "
US Stock Market Sectors Overview Table [By MUQWISHI]US Market Overview Table will identify the bullish and bearish sectors of a day by tracking the SPDR sectors funds.
It's possible to add a ticker symbol for correlation compared to each sector.
Overview Indicator
Valuation TableHey folks, I hope you are all doing well!
This is an indicator that you can use to help you to evaluate companies. There are a few things I added to the valuation table that I personally use and I will explain what they are.
I added Joel Greenblatt's ROC% because it takes Earnings before Interest and Taxes to reflect more closely what the company earns from its operations, while including the cost of depreciation/amortization of assets. A high double digit figure often means that the company has a defensible edge versus its competitors (e.g. a strong brand or a unique product). It's good for relative valuation (comparing two companies in the same industry).
I also added Donald Yacktman's forward rate of return. Yacktman defines forward rate of return as the normalized free cash flow yield plus real growth plus inflation . Unlike the Earnings Yield %, the Forward Rate of Return uses the normalized Free Cash Flow of the past seven years, and considers growth. The forward rate of return can be thought of as the return that investors buying the stock today can expect from it in the future. Yacktman’s Forward Rate of Return may or may not be a useful metric. However, it does present new ways to see and think about stocks we may want to buy.
I added a box called "real price" and that is from Peter Lynch's book, "One Up on Wall Street," where he talked about how the real price of the stock is really the current price - Net Cash Per Share.
I would also personally pair this script with TradingView's built in financial indicators that shows the revenue growth, net income, etc.
Note: the script only works on the weekly timeframe and it will take some time to load because it has a lot of data.
ATR Table (SMA)ATR table for select time frames.
Using Simple Moving Average (SMA) to get ATR.
MA periods is based on numbers suggested by Saeed Khakestar (Trigger Price Action)
You can change them in code
5m => 12
15m => 16
1H => 24
4H => 42
1D => 30
1W => 52
RSI is calculated the same way
Price Range TableThe table shows the ranking of the price as a percentage relative to the past candles.
100 ~ highest price of the time frame
0 ~ lowest price of the time frame
Simple RSI tableThis is a simple RSI table for traders that don't want the graph, only the current value.
Location, thresholds, and colors are all adjustable.
TableUtilsLibrary "TableUtils"
Collection of table utility functions
getTablePositionByLabel(tablePosition)
Return the position for the table by given label. Useful if you want to control the position of the table with a pine script input selector that use a more human friendly labels
Parameters:
tablePosition (string) : (string) Label of the table position. Possible values are: "Top left", "Top right", "Bottom left", "Bottom right", "Middle left", "Middle right"
Returns: the position for the table by given label. Useful if you want to control the position of the table with a pine script input selector that use a more human friendly labels
TableColorThemeLibrary "TableColorTheme"
TODO: This library provides the color for the table.
monokai(name) theme: Provides the colors of monokai.
Parameters:
name : TODO: The name of the color group.
Returns: TODO: Returns an array of colors.
kolormark.com
monokaipro(name) theme: Provides the colors of monokai pro.
Parameters:
name : TODO: The name of the color group.
Returns: TODO: Returns an array of colors.
theme(name) theme This function provides the color for the table.
Parameters:
name : TODO: The name of the color group.
Returns: TODO: Returns an array of colors.
TableRSI and Ichimoku Strength Table
This indicator displays whole-number RSI values (1h, 4h, 1d, 3d, 1w) and Ichimoku strengths (Conversion Line, Base Line, Cloud, Lagging Span) in a customizable table. Toggle between horizontal (9x2) or vertical (2x10) layouts, with adjustable position (e.g., Top Right), text size (Tiny to Large), and colors (border, header, text, RSI: >70 red, <30 green, 30-70 yellow; Ichimoku: >50 green, <50 red). Ichimoku components are plotted on the chart. It offers a clear view of momentum and trend strength for traders.
Table: EMA SurveillanceThis script will show information of interest about Moving Averages from the selected timeframe.
The idea is to provide data from higher timeframes (Daily preferably).
The information provided includes:
• selected length and calculation
• a relative position of the close to the average (above, below, and how much)
• how many periods passed since the moving average has been tested - any break counts as a test, it doesn't have to close on the opposite side
Global Settings:
• Timeframe of the moving averages
• Choose to see simple words such as "Above" / "Below" OR the specific percentage OR how much percentage % it moved from the moving average?
• EMA or SMA
Moving Average Settings:
• Up to 6 different lengths
• You can deactivate the averages you don't need
I hope it will be useful. Good luck!
Tables: A Simple NoteA simple note to remind you of what you would otherwise forget. I don't think it needs further explanation.
Comes with three rows each can be enabled independently of others. Can be resized.
Table Volume MultiframeDescription
The Table Volume Multiframe indicator displays volume information across multiple timeframes in a convenient table format. Users can customize the table's position, size, and the specific timeframes to be displayed. This indicator helps traders analyze volume trends and divergences across different timeframes, providing a comprehensive view of market activity. The table shows the total volume, buy percentage, sell percentage, and a countdown timer for the next bar close for each selected timeframe. The countdown function updates consistently to provide real-time information.
Features
- Customizable table position and size
- Selectable timeframes
- Displays volume, buy percentage, sell percentage
- Countdown timer for next bar close
- Real-time updates
[TABLE] Moving Average Stage Indicator Table📈 MA Stage Indicator Table
🧠 Overview:
This script analyzes market phases based on moving average (MA) crossovers, classifying them into 6 distinct stages and displaying statistical summaries for each.
🔍 Key Features:
• Classifies market condition into Stage 1 to Stage 6 based on the relationship between MA1 (short), MA2 (mid), and MA3 (long)
• Provides detailed stats for each stage:
• Average Duration
• Average Width (MA distance)
• Slope (Angle) - High / Low / Average
• Shows current stage details in real-time
• Supports custom date range filtering
• Choose MA type: SMA or EMA
• Optional background coloring for stages
• Clean summary table displayed on the chart
Multi Ticker Price TableTable showing the current price of up to 7 tickers
- Tickers are user choice
- Table background is customizable
- User has the choice to turn the Daily % column off
Table rsi multiframes(by Lc_M)- Simultaneous display of RSI values on cells corresponding to each selected timeframe, organized in an intuitive table, adjustable in size and position.
- Color indicator on each cell that presents RSI values within the overbought and oversold levels. example: if the user wants to set the O.S/O.B levels to 20 - 80, the colored cells will only appear at "RSI" => 80 and "RSI" <= 20.
- Free configuration of graphic times, lengths and O.B/O.S, according to user standards
Autotable█ OVERVIEW
The library allows to automatically draw a table based on a string or float matrix (or both) controlling all of the parameters of the table (including merging cells) with parameter matrices (like, e.g. matrix of cell colors).
All things you would normally do with table.new() and table.cell() are now possible using respective parameters of library's main function, autotable() (as explained further below).
Headers can be supplied as arrays.
Merging of the cells is controlled with a special matrix of "L" and "U" values which instruct a cell to merged with the cell to the left or upwards (please see examples in the script and in this description).
█ USAGE EXAMPLES
The simplest and most straightforward:
mxF = matrix.new(3,3, 3.14)
mxF.autotable(bgcolor = color.rgb(249, 209, 29)) // displays float matrix as a table in the top right corner with defalult settings
mxS = matrix.new(3,3,"PI")
// displays string matrix as a table in the top right corner with defalult settings
mxS.autotable(Ypos = "bottom", Xpos = "right", bgcolor = #b4d400)
// displays matrix displaying a string value over a float value in each cell
mxS.autotable(mxF, Ypos = "middle", Xpos = "center", bgcolor = color.gray, text_color = #86f62a)
Draws this:
Tables with headers:
if barstate.islast
mxF = matrix.new(3,3, 3.14)
mxS = matrix.new(3,3,"PI")
arColHeaders = array.from("Col1", "Col2", "Col3")
arRowHeaders = array.from("Row1", "Row2", "Row3")
// float matrix with col headers
mxF.autotable(
bgcolor = #fdfd6b
, arColHeaders = arColHeaders
)
// string matrix with row headers
mxS.autotable(arRowHeaders = arRowHeaders, Ypos = "bottom", Xpos = "right", bgcolor = #b4d400)
// string/float matrix with both row and column headers
mxS.autotable(mxF
, Ypos = "middle", Xpos = "center"
, arRowHeaders = arRowHeaders
, arColHeaders = arColHeaders
, cornerBgClr = #707070, cornerTitle = "Corner\ncell", cornerTxtClr = #ffdc13
, bgcolor = color.gray, text_color = #86f62a
)
Draws this:
█ FUNCTIONS
One main function is autotable() which has only one required argument mxValS, a string matrix.
Please see below the description of all of the function parameters:
The table:
tbl (table) (Optional) If supplied, this table will be deleted.
The data:
mxValS (matrix ) (Required) Cell text values
mxValF (matrix) (Optional) Numerical part of cell text values. Is concatenated to the mxValS values via `string_float_separator` string (default "\n")
Table properties, have same effect as in table.new() :
defaultBgColor (color) (Optional) bgcolor to be used if mxBgColor is not supplied
Ypos (string) (Optional) "top", "bottom" or "center"
Xpos (string) (Optional) "left", "right", or "center"
frame_color (color) (Optional) frame_color like in table.new()
frame_width (int) (Optional) frame_width like in table.new()
border_color (color) (Optional) border_color like in table.new()
border_width (int) (Optional) border_width like in table.new()
force_overlay (simple bool) (Optional) If true draws table on main pane.
Cell parameters, have same effect as in table.cell() ):
mxBgColor (matrix) (Optional) like bgcolor argument in table.cell()
mxTextColor (matrix) (Optional) like text_color argument in table.cell()
mxTt (matrix) (Optional) like tooltip argument in table.cell()
mxWidth (matrix) (Optional) like width argument in table.cell()
mxHeight (matrix) (Optional) like height argument in table.cell()
mxHalign (matrix) (Optional) like text_halign argument in table.cell()
mxValign (matrix) (Optional) like text_valign argument in table.cell()
mxTextSize (matrix) (Optional) like text_size argument in table.cell()
mxFontFamily (matrix) (Optional) like text_font_family argument in table.cell()
Other table properties:
tableWidth (float) (Optional) Overrides table width if cell widths are non zero. E.g. if there are four columns and cell widths are 20 (either as set via cellW or via mxWidth) then if tableWidth is set to e.g. 50 then cell widths will be 50 * (20 / 80), where 80 is 20*4 = total width of all cells. Works simialar for widths set via mxWidth - determines max sum of widths across all cloumns of mxWidth and adjusts cell widths proportionally to it. If cell widths are 0 (i.e. auto-adjust) tableWidth has no effect.
tableHeight (float) (Optional) Overrides table height if cell heights are non zero. E.g. if there are four rows and cell heights are 20 (either as set via cellH or via mxHeight) then if tableHeigh is set to e.g. 50 then cell heights will be 50 * (20 / 80), where 80 is 20*4 = total height of all cells. Works simialar for heights set via mxHeight - determines max sum of heights across all cloumns of mxHeight and adjusts cell heights proportionally to it. If cell heights are 0 (i.e. auto-adjust) tableHeight has no effect.
defaultTxtColor (color) (Optional) text_color to be used if mxTextColor is not supplied
text_size (string) (Optional) text_size to be used if mxTextSize is not supplied
font_family (string) (Optional) cell text_font_family value to be used if a value in mxFontFamily is no supplied
cellW (float) (Optional) cell width to be used if a value in mxWidth is no supplied
cellH (float) (Optional) cell height to be used if a value in mxHeight is no supplied
halign (string) (Optional) cell text_halign value to be used if a value in mxHalign is no supplied
valign (string) (Optional) cell text_valign value to be used if a value in mxValign is no supplied
Headers parameters:
arColTitles (array) (Optional) Array of column titles. If not na a header row is added.
arRowTitles (array) (Optional) Array of row titles. If not na a header column is added.
cornerTitle (string) (Optional) If both row and column titles are supplied allows to set the value of the corner cell.
colTitlesBgColor (color) (Optional) bgcolor for header row
colTitlesTxtColor (color) (Optional) text_color for header row
rowTitlesBgColor (color) (Optional) bgcolor for header column
rowTitlesTxtColor (color) (Optional) text_color for header column
cornerBgClr (color) (Optional) bgcolor for the corner cell
cornerTxtClr (color) (Optional) text_color for the corner cell
Cell merge parameters:
mxMerge (matrix) (Optional) A matrix determining how cells will be merged. "L" - cell merges to the left, "U" - upwards.
mergeAllColTitles (bool) (Optional) Allows to print a table title instead of column headers, merging all header row cells and leaving just the value of the first cell. For more flexible options use matrix arguments leaving header/row arguments na.
mergeAllRowTitles (bool) (Optional) Allows to print one text value merging all header row cells and leaving just the value of the first cell. For more flexible options use matrix arguments leaving header/row arguments na.
Format:
string_float_separator (string) (Optional) A string used to separate string and float parts of cell values (mxValS and mxValF). Default is "\n"
format (string) (Optional) format string like in str.format() used to format numerical values
nz (string) (Optional) Determines how na numerical values are displayed.
The only other available function is autotable(string,... ) with a string parameter instead of string and float matrices which draws a one cell table.
█ SAMPLE USE
E.g., CSVParser library demo uses Autotable's for generating complex tables with merged cells.
█ CREDITS
The library was inspired by @kaigouthro's matrixautotable . A true master. Many thanks to him for his creative, beautiful and very helpful libraries.
easytableLibrary "easytable"
Create tables easily, with minimal code
▦ FEATURES ▦
█ Create tables █ JSON To Table █ Change Colors █ Array to Rows/Columns █ Pre-Styles █ Change Text Size █ Delete Rows/Columns █ Blink Cells
indentify_table_id() Identifies all tables ID number in each cell(0,0).
get_table_by_id(id_number) Get table object by ID number.
Parameters:
id_number : (int) ID number of the table to fetch.
Returns: table.
change_cells_color(table_object, cells_color, start_column, end_column, start_row, end_row) Change cells background colors.
Parameters:
table_object : (table) table object to be changed.
cells_color : (color) Cells color.
start_column : (int) Start column.
end_column : (int) End column.
start_row : (int) Start Row.
end_row : (int) End Row to change.
Returns: Void.
change_cells_text_color(table_object, text_color, start_column, end_column, start_row, end_row) Change cells text colors.
Parameters:
table_object : (table) table object to be changed.
text_color : (color) Text color.
start_column : (int) Start column.
end_column : (int) End column.
start_row : (int) Start Row.
end_row : (int) End Row.
Returns: Void.
change_all_table_text_color(table_object, text_color, table_column_size, table_row_size) Change All table text color.
Parameters:
table_object : (table) table object to be changed.
text_color : (color) Text color.
table_column_size : (int) Size of the table columns.
table_row_size : (int) Size of the table rows.
Returns: Void.
change_table_size(table_object, n_of_columns, n_of_rows, tbl_size) Change table size.
Parameters:
table_object : (table) table object to be changed.
n_of_columns : (int) Size of the table columns.
n_of_rows : (int) Size of the table rows.
tbl_size : (string) size of the table.
Returns: Void.
change_cells_text_size(text_size, start_column, end_column, start_row, end_row, table_id) Change table cells text size .
Parameters:
text_size : (string) Text size.
start_column : (int) Start column.
end_column : (int)(optional) End column.
start_row : (int)(optional) Start Row.
end_row : (int)(optional) End Row.
table_id : (int)(optional) Number of the ID of the table.
Returns: Void.
table_delete_row(table_object, table_column_size, start_row, end_row) Delete specified rows from table.
Parameters:
table_object : (table) table object to be changed.
table_column_size : (int) Table columns max size.
start_row : (int) Start row to delete.
end_row : (int)(optional) End row to delete (optional — Assumes start_row value).
Returns: Void.
table_delete_column(table_object, table_row_size, start_column, end_column) Delete specified columns from table.
Parameters:
table_object : (table) table object to be changed.
table_row_size : (int) Table rows max size.
start_column : (int) Start column to delete.
end_column : (int)(optional) End column to delete (optional — Assumes start_column value).
Returns: Void.
array_to_table_column_auto(column_to_insert, array_to_insert, table_id) Insert string array to table column without passing table object.
Parameters:
column_to_insert : (int) Column to be inserted.
array_to_insert : (string array) Start column to delete.
table_id : (int)(optional) Number of the ID of the table.
Returns: Void.
array_to_table_row_auto(row_to_insert, array_to_insert, table_id) Insert string array to table row without passing table object.
Parameters:
row_to_insert : (int) Column to be inserted.
array_to_insert : (string array) Start column to delete.
table_id : (int)(optional) Number of the ID of the table.
Returns: Void.
array_to_table_row(table_object, row_to_insert, array_to_insert) Insert string array to table row by passing table object.
Parameters:
table_object : (table) table object to be changed.
row_to_insert : (int) Row to be inserted.
array_to_insert : (string array) Start column to delete.
Returns: Void.
array_to_table_column(table_object, column_to_insert, array_to_insert) Insert string array to table column by passing table object.
Parameters:
table_object : (table) table object to be changed.
column_to_insert : (int) Column to be inserted.
array_to_insert : (string array) Start column to delete.
Returns: Void.
blink_cell(cell_column, cell_row, c_color, blink_interval_ms, table_id) Changes cell color at set intervals (blink).
Parameters:
cell_column : (int) Cell column position.
cell_row : (int) Cell row position.
c_color : (color) Color to blink.
blink_interval_ms : (int)(opt) Interval in milliseconds.
table_id : (int)(opt) Table ID number.
change_table_style(table_object, number_of_columns, number_of_rows, color) Changes table pre-style by selecting a pre-style number.
Parameters:
table_object : (table) table object to be changed.
number_of_columns : (int) Table column size.
number_of_rows : (int) Table row size.
color : 1 (color) Color of .
Returns: Void.
create_table_clean(n_of_columns, n_of_rows, position) Create a simple(blank) table without any styling.
Parameters:
n_of_columns : (int) Numbers of columns in the table.
n_of_rows : (int) Number of rows in the table.
position : (string) table position.
Returns: table object.
create_table_with_style(n_of_columns, n_of_rows, style_number, position) Create table with a pre-set style.
Parameters:
n_of_columns : (int) Numbers of columns in the table.
n_of_rows : (int) Number of rows in the table.
style_number : (int) Style number.
position : (string) table position.
Returns: table object.
json_to_table(raw_json) Create table based on input raw json string.
Parameters:
raw_json : (int) Raw json string.
Returns: table object.
json_example() Example function that display a table based on a json
example_create_table()
Casa_TableLibrary "Casa_Table"
A powerful library for creating customizable tables from data arrays and matrices.
Features flexible formatting options including:
- Multiple function implementations for different levels of control
- Consistent column counts required across matrix rows
- Matching dimensions needed for color arrays/matrices
- Cell spanning capabilities across rows/columns
- Rich examples demonstrating proper data structure setup
The library makes it easy to transform your data into professional-looking
tables while maintaining full control over their visual appearance.
floatArrayToCellArray(floatArray)
Helper function that converts a float array to a Cell array so it can be rendered with the fromArray function
Parameters:
floatArray (array) : (array) the float array to convert to a Cell array.
Returns: array The Cell array to return.
stringArrayToCellArray(stringArray)
Helper function that converts a string array to a Cell array so it can be rendered with the fromArray function
Parameters:
stringArray (array) : (array) the array to convert to a Cell array.
Returns: array The Cell array to return.
floatMatrixToCellMatrix(floatMatrix)
Helper function that converts a float matrix to a Cell matrix so it can be rendered with the fromMatrix function
Parameters:
floatMatrix (matrix) : (matrix) the float matrix to convert to a string matrix.
Returns: matrix The Cell matrix to render.
stringMatrixToCellMatrix(stringMatrix)
Helper function that converts a string matrix to a Cell matrix so it can be rendered with the fromMatrix function
Parameters:
stringMatrix (matrix) : (matrix) the string matrix to convert to a Cell matrix.
Returns: matrix The Cell matrix to return.
fromMatrix(CellMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Takes a CellMatrix and renders it as a table.
Parameters:
CellMatrix (matrix) : (matrix) The Cells to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromMatrix(dataMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Renders a float matrix as a table.
Parameters:
dataMatrix (matrix) : (matrix_float) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromMatrix(dataMatrix, position, verticalOffset, transposeTable, textSize, borderWidth, tableNumRows, blankCellText)
Renders a string matrix as a table.
Parameters:
dataMatrix (matrix) : (matrix_string) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
tableNumRows (int) : (int) Optional. The number of rows in the table. Not required, defaults to the number of rows in the provided matrix. If your matrix will have a variable number of rows, you must provide the max number of rows or the function will error when it attempts to set a cell value on a row that the table hadn't accounted for when it was defined.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a Cell array as a table.
Parameters:
dataArray (array) : (array) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a string array as a table.
Parameters:
dataArray (array) : (array_string) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
fromArray(dataArray, position, verticalOffset, transposeTable, textSize, borderWidth, blankCellText)
Renders a float array as a table.
Parameters:
dataArray (array) : (array_float) The data to be rendered in a table
position (string) : (string) Optional. The position of the table. Defaults to position.top_right
verticalOffset (int) : (int) Optional. The vertical offset of the table from the top or bottom of the chart. Defaults to 0.
transposeTable (bool) : (bool) Optional. Will transpose all of the data in the matrices before rendering. Defaults to false.
textSize (string) : (string) Optional. The size of text to render in the table. Defaults to size.small.
borderWidth (int) : (int) Optional. The width of the border between table cells. Defaults to 2.
blankCellText (string) : (string) Optional. Text to use cells when adding blank rows for vertical offsetting.
debug(message, position)
Renders a debug message in a table at the desired location on screen.
Parameters:
message (string) : (string) The message to render.
position (string) : (string) Optional. The position of the debug message. Defaults to position.middle_right.
Cell
Type for each cell's content and appearance
Fields:
content (series string)
bgColor (series color)
textColor (series color)
align (series string)
colspan (series int)
rowspan (series int)
Adaptive MFT Extremum Pivots [Elysian_Mind]Adaptive MFT Extremum Pivots
Overview:
The Adaptive MFT Extremum Pivots indicator, developed by Elysian_Mind, is a powerful Pine Script tool that dynamically displays key market levels, including Monthly Highs/Lows, Weekly Extremums, Pivot Points, and dynamic Resistances/Supports. The term "dynamic" emphasizes the adaptive nature of the calculated levels, ensuring they reflect real-time market conditions. I thank Zandalin for the excellent table design.
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Chart Explanation:
The table, a visual output of the script, is conveniently positioned in the bottom right corner of the screen, showcasing the indicator's dynamic results. The configuration block, elucidated in the documentation, empowers users to customize the display position. The default placement is at the bottom right, exemplified in the accompanying chart.
The deliberate design ensures that the table does not obscure the candlesticks, with traders commonly situating it outside the candle area. However, the flexibility exists to overlay the table onto the candles. Thanks to transparent cells, the underlying chart remains visible even with the table displayed atop.
In the initial column of the table, users will find labels for the monthly high and low, accompanied by their respective numerical values. The default precision for these values is set at #.###, yet this can be adjusted within the configuration block to suit markets with varying degrees of volatility.
Mirroring this layout, the last column of the table presents the weekly high and low data. This arrangement is part of the upper half of the table. Transitioning to the lower half, users encounter the resistance levels in the first column and the support levels in the last column.
At the center of the table, prominently displayed, is the monthly pivot point. For a comprehensive understanding of the calculations governing these values, users can refer to the documentation. Importantly, users retain the freedom to modify these mathematical calculations, with the table seamlessly updating to reflect any adjustments made.
Noteworthy is the table's persistence; it continues to display reliably even if users choose to customize the mathematical calculations, providing a consistent and adaptable tool for informed decision-making in trading.
This detailed breakdown offers traders a clear guide to interpreting the information presented by the table, ensuring optimal use and understanding of the Adaptive MFT Extremum Pivots indicator.
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Usage:
Table Layout:
The table is a crucial component of this indicator, providing a structured representation of various market levels. Color-coded cells enhance readability, with blue indicating key levels and a semi-transparent background to maintain chart visibility.
1. Utilizing a Table for Enhanced Visibility:
In presenting this wealth of information, the indicator employs a table format beneath the chart. The use of a table is deliberate and offers several advantages:
2. Structured Organization:
The table organizes the diverse data into a structured format, enhancing clarity and making it easier for traders to locate specific information.
3. Concise Presentation:
A table allows for the concise presentation of multiple data points without cluttering the main chart. Traders can quickly reference key levels without distraction.
4. Dynamic Visibility:
As the market dynamically evolves, the table seamlessly updates in real-time, ensuring that the most relevant information is readily visible without obstructing the candlestick chart.
5. Color Coding for Readability:
Color-coded cells in the table not only add visual appeal but also serve a functional purpose by improving readability. Key levels are easily distinguishable, contributing to efficient analysis.
Data Values:
Numerical values for each level are displayed in their respective cells, with precision defined by the iPrecision configuration parameter.
Configuration:
// User configuration: You can modify this part without code understanding
// Table location configuration
// Position: Table
const string iPosition = position.bottom_right
// Width: Table borders
const int iBorderWidth = 1
// Color configuration
// Color: Borders
const color iBorderColor = color.new(color.white, 75)
// Color: Table background
const color iTableColor = color.new(#2B2A29, 25)
// Color: Title cell background
const color iTitleCellColor = color.new(#171F54, 0)
// Color: Characters
const color iCharColor = color.white
// Color: Data cell background
const color iDataCellColor = color.new(#25456E, 0)
// Precision: Numerical data
const int iPrecision = 3
// End of configuration
The code includes a configuration block where users can customize the following parameters:
Precision of Numerical Table Data (iPrecision):
// Precision: Numerical data
const int iPrecision = 3
This parameter (iPrecision) sets the precision of the numerical values displayed in the table. The default value is 3, displaying numbers in #.### format.
Position of the Table (iPosition):
// Position: Table
const string iPosition = position.bottom_right
This parameter (iPosition) sets the position of the table on the chart. The default is position.bottom_right.
Color preferences
Table borders (iBorderColor):
// Color: Borders
const color iBorderColor = color.new(color.white, 75)
This parameters (iBorderColor) sets the color of the borders everywhere within the window.
Table Background (iTableColor):
// Color: Table background
const color iTableColor = color.new(#2B2A29, 25)
This is the background color of the table. If you've got cells without custom background color, this color will be their background.
Title Cell Background (iTitleCellColor):
// Color: Title cell background
const color iTitleCellColor = color.new(#171F54, 0)
This is the background color the title cells. You can set the background of data cells and text color elsewhere.
Text (iCharColor):
// Color: Characters
const color iCharColor = color.white
This is the color of the text - titles and data - within the table window. If you change any of the background colors, you might want to change this parameter to ensure visibility.
Data Cell Background: (iDataCellColor):
// Color: Data cell background
const color iDataCellColor = color.new(#25456E, 0)
The data cells have a background color to differ from title cells. You can configure this is a different parameter (iDataColor). You might even set the same color for data as for the titles if you will.
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Mathematical Background:
Monthly and Weekly Extremums:
The indicator calculates the High (H) and Low (L) of the previous month and week, ensuring accurate representation of these key levels.
Standard Monthly Pivot Point:
The standard pivot point is determined based on the previous month's data using the formula:
PivotPoint = (PrevMonthHigh + PrevMonthLow + Close ) / 3
Monthly Pivot Points (R1, R2, R3, S1, S2, S3):
Additional pivot points are calculated for Resistances (R) and Supports (S) using the monthly data:
R1 = 2 * PivotPoint - PrevMonthLow
S1 = 2 * PivotPoint - PrevMonthHigh
R2 = PivotPoint + (PrevMonthHigh - PrevMonthLow)
S2 = PivotPoint - (PrevMonthHigh - PrevMonthLow)
R3 = PrevMonthHigh + 2 * (PivotPoint - PrevMonthLow)
S3 = PrevMonthLow - 2 * (PrevMonthHigh - PivotPoint)
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Code Explanation and Interpretation:
The table displayed beneath the chart provides the following information:
Monthly Extremums:
(H) High of the previous month
(L) Low of the previous month
// Function to get the high and low of the previous month
getPrevMonthHighLow() =>
var float prevMonthHigh = na
var float prevMonthLow = na
monthChanged = month(time) != month(time )
if (monthChanged)
prevMonthHigh := high
prevMonthLow := low
Weekly Extremums:
(H) High of the previous week
(L) Low of the previous week
// Function to get the high and low of the previous week
getPrevWeekHighLow() =>
var float prevWeekHigh = na
var float prevWeekLow = na
weekChanged = weekofyear(time) != weekofyear(time )
if (weekChanged)
prevWeekHigh := high
prevWeekLow := low
Monthly Pivots:
Pivot: Standard pivot point based on the previous month's data
// Function to calculate the standard pivot point based on the previous month's data
getStandardPivotPoint() =>
= getPrevMonthHighLow()
pivotPoint = (prevMonthHigh + prevMonthLow + close ) / 3
Resistances:
R3, R2, R1: Monthly resistance levels
// Function to calculate additional pivot points based on the monthly data
getMonthlyPivotPoints() =>
= getPrevMonthHighLow()
pivotPoint = (prevMonthHigh + prevMonthLow + close ) / 3
r1 = (2 * pivotPoint) - prevMonthLow
s1 = (2 * pivotPoint) - prevMonthHigh
r2 = pivotPoint + (prevMonthHigh - prevMonthLow)
s2 = pivotPoint - (prevMonthHigh - prevMonthLow)
r3 = prevMonthHigh + 2 * (pivotPoint - prevMonthLow)
s3 = prevMonthLow - 2 * (prevMonthHigh - pivotPoint)
Initializing and Populating the Table:
The myTable variable initializes the table with a blue background, and subsequent table.cell functions populate the table with headers and data.
// Initialize the table with adjusted bgcolor
var myTable = table.new(position = iPosition, columns = 5, rows = 10, bgcolor = color.new(color.blue, 90), border_width = 1, border_color = color.new(color.blue, 70))
Dynamic Data Population:
Data is dynamically populated in the table using the calculated values for Monthly Extremums, Weekly Extremums, Monthly Pivot Points, Resistances, and Supports.
// Add rows dynamically with data
= getPrevMonthHighLow()
= getPrevWeekHighLow()
= getMonthlyPivotPoints()
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Conclusion:
The Adaptive MFT Extremum Pivots indicator offers traders a detailed and clear representation of critical market levels, empowering them to make informed decisions. However, users should carefully analyze the market and consider their individual risk tolerance before making any trading decisions. The indicator's disclaimer emphasizes that it is not investment advice, and the author and script provider are not responsible for any financial losses incurred.
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Disclaimer:
This indicator is not investment advice. Trading decisions should be made based on a careful analysis of the market and individual risk tolerance. The author and script provider are not responsible for any financial losses incurred.
Kind regards,
Ely
BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
Multiple Moving Average ToolkitFeatures Overview:
Multiple Moving Averages: The script allows you to plot up to five different Moving Averages (MAs) on your chart at the same time. You can choose the type of MA (EMA, SMA, HMA, WMA, DEMA, VWMA, VWAP) and the length of each one.
Color Ribbon: You can turn the MAs into a color ribbon by selecting the "Turn into Color Ribbon?" option. This will make the area between the MAs colored and can help you identify trends more easily.
MA Value Table: You can draw a table on your chart that displays the current values of each MA, whether the trend is bullish or bearish along with the length of the MAs. The current ATR value is also shown in the last cell of the table. You can choose the location of the table (Top Left, Top Right, Bottom Left, Bottom Right) and the transparency of the background color.
Crosses: The script can detect when two MAs cross over each other (1st MA crosses 5th MA and vice versa), indicating a potential trend reversal. It will plot crosses on the chart at the point of the crossover and give an alert if the "Bullish Cross Detected" or "Bearish Cross Detected" condition is met.
How to use:
Once the script is added to your chart, you can customize the settings to fit your preferences. You can choose the type and length of each MA, whether to turn them into a color ribbon, whether to plot crosses, and whether to draw the MA Value Table.
The MA Value Table can be moved to a different location on the chart by selecting the "Location of Table" option and choosing Top Left, Top Right, Bottom Left, or Bottom Right.
Watch for MA crossovers and alerts to identify potential trend reversals. The script can help you identify bullish and bearish trends by color-coding the area between the MAs and displaying the current values of each MA in the table.
Breakdown of the script:
User Inputs
The first section of the script defines several user inputs that allows you to customize the indicator. These include options for turning the MAs into a color ribbon, plotting crosses when there is a bullish or bearish cross of the MAs, drawing a table of the MA values, and setting the transparency of the ribbon. You can also select the location of the MA value table and customize the settings for each individual MA.
Moving Average Calculation
The script defines a function called "getMA" that calculates the moving average for a given type and length. The function uses a switch statement to determine which type of moving average to use, such as an exponential moving average (EMA), simple moving average (SMA), Hull moving average (HMA), weighted moving average (WMA), double exponential moving average (DEMA), volume-weighted moving average (VWMA), or volume-weighted average price (VWAP).
The script then calls this function to calculate the values of up to five different MAs, depending on the user input. The ATR (average true range) is also calculated using the TA library.
Color Filter and Cross Detection
The script sets a color filter based on the relationship between the MAs. If the shorter-term MAs are above the longer-term MAs, the filter is set to green to indicate a bullish trend, and if the shorter-term MAs are below the longer-term MAs, the filter is set to red to indicate a bearish trend. You can adjust the transparency of the ribbon to make it more or less visible.
The script also detects when there is a bullish or bearish cross of the MAs and can generate alerts to notify you.
MA Plotting
The script plots up to five MAs on the chart, depending on the user input. The MAs are plotted as lines with different colors and thicknesses, and you can choose to turn them into a color ribbon if desired.
Cross Plotting
The script plots crosses on the chart when there is a bullish or bearish cross of the MAs. The crosses are plotted as X shapes at the location of the cross and are color-coded to indicate the direction of the cross.
MA Value Table
Finally, the script draws a table of the MA values on the chart, displaying the values of each MA as well as the current trend and the ATR. You can customize the location of the table, and the table is colored to match the color filter of the MAs.
Feel free to message me or comment on the post with any questions or issues!
Much more to come!
Thanks for reading, enjoy!
Cointegration Heatmap & Spread Table [EdgeTerminal]The Cointegration Heatmap is a powerful visual and quantitative tool designed to uncover deep, statistically meaningful relationships between assets.
Unlike traditional indicators that react to price movement, this tool analyzes the underlying statistical relationship between two time series and tracks when they diverge from their long-term equilibrium — offering actionable signals for mean-reversion trades .
What Is Cointegration?
Most traders are familiar with correlation, which measures how two assets move together in the short term. But correlation is shallow — it doesn’t imply a stable or predictable relationship over time.
Cointegration, however, is a deeper statistical concept: Two assets are cointegrated if a linear combination of their prices or returns is stationary , even if the individual series themselves are non-stationary.
Cointegration is a foundational concept in time series analysis, widely used by hedge funds, proprietary trading firms, and quantitative researchers. This indicator brings that institutional-grade concept into an easy-to-use and fully visual TradingView indicator.
This tool helps answer key questions like:
“Which stocks tend to move in sync over the long term?”
“When are two assets diverging beyond statistical norms?”
“Is now the right time to short one and long the other?”
Using a combination of regression analysis, residual modeling, and Z-score evaluation, this indicator surfaces opportunities where price relationships are stretched and likely to snap back — making it ideal for building low-risk, high-probability trade setups.
In simple terms:
Cointegrated assets drift apart temporarily, but always come back together over time. This behavior is the foundation of successful pairs trading.
How the Indicator Works
Cointegration Heatmap indicator works across any market supported on TradingView — from stocks and ETFs to cryptocurrencies and forex pairs.
You enter your list of symbols, choose a timeframe, and the indicator updates every bar with live cointegration scores, spread signals, and trade-ready insights.
Indicator Settings:
Symbol list: a customizable list of symbols separated by commas
Returns timeframe: time frame selection for return sampling (Weekly or Monthly)
Max periods: max periods to limit the data to a certain time and to control indicator performance
This indicator accomplishes three major goals in one streamlined package:
Identifies stable long-term relationships (cointegration) between assets, using a heatmap visualization.
Tracks the spread — the difference between actual prices and the predicted linear relationship — between each pair.
Generates trade signals based on Z-score deviations from the mean spread, helping traders know when a pair is statistically overextended and likely to mean revert.
The math:
Returns are calculated using spread tickers to ensure alignment in time and adjust for dividends, splits, and other inconsistencies.
For each unique pair of symbols, we perform a linear regression
Yt=α+βXt+ε
Then we compute the residuals (errors from the regression):
Spreadt=Yt−(α+βXt)
Calculate the standard deviation of the spread over a moving window (default: 100 samples) and finally, define the Cointegration Score:
S=1/Standard Deviation of Residuals
This means, the lower the deviation, the tighter the relationship, so higher scores indicate stronger cointegration.
Always remember that cointegration can break down so monitor the asset over time and over multiple different timeframes before making a decision.
How to use the indicator
The heatmap table:
The indicator displays 2 very important tables, one in the middle and one on the right side. After entering your symbols, the first table to pay attention to is the middle heatmap table.
Any assets with a cointegration value of 25% is something to pay attention to and have a strong and stable relationship. Anything below is weak and not tradable.
Additionally, the 40% level is another important line to cross. Assets that have a cointegration score of over 40% will most likely have an extremely strong relationship.
Think about it this way, the higher the percentage, the tighter and more statistically reliable the relationship is.
The spread table:
After finding a good asset pair using heatmap, locate the same pair in the spread table (right side).
Here’s what you’ll see on the table:
Spread: Current difference between the two symbols based on the regression fit
Mean: Historical average of that spread
Z-score: How far current spread is from the mean in standard deviations
Signal: Trade suggestion: Short, Long, or Neutral
Since you’re expecting mean reversion, the idea is that the spread will return to the average. You want to take a trade when the z-score is either over +2 or below -2 and exit when z-score returns to near 0.
You will usually see the trade suggestion on the spread chart but you can make your own decision based on your risk level.
Keep in mind that the Z-score for each pair refers to how off the first asset is from the mean compared to the second one, so for example if you see STOCKA vs STOCKB with a Z-score of -1.55, we are regressing STOCKB (Y) on STOCKA (X).
In this case, STOCKB is the quoted asset and STOCKA is the base asset.
In this case, this means that STOCKB is much lower than expected relative to STOCKA, so the trade would be a long position on stock B and short position on stock A.
