tts_conventionLibrary "tts_convention"
This library can convert the start, end, cancel start, cancel end deal conditions that are used in the
"Template Trailing Strategy" script into a signal value and vice versa. The "two channels mod div" convention is unsed
internaly and the signal value can be composed/decomposed into two channels that contain the afforementioned actions
for long and short positions separetely.
getDealConditions(signal)
โโgetDealConditions - Get the start, end, cancel start and cancel end deal conditions that are used in the "Template Trailing Strategy" script by decomposing the given signal
โโParameters:
โโโโ signal (int) : - The signal value to decompose
โโReturns: An object with the start, end, cancel start and cancel end deal conditions for long and short
getSignal(dealConditions)
โโgetSignal - Get the signal value from the composition of the start, end, cancel start and cancel end deal conditions that are used in the "Template Trailing Strategy" script
โโParameters:
โโโโ dealConditions (DealConditions) : - The deal conditions object that containd the start, end, cancel start and cancel end deal conditions for long and short
โโReturns: The composed signal value
DealConditions
โโFields:
โโโโ startLongDeal (series__bool)
โโโโ startShortDeal (series__bool)
โโโโ endLongDeal (series__bool)
โโโโ endShortDeal (series__bool)
โโโโ cnlStartLongDeal (series__bool)
โโโโ cnlStartShortDeal (series__bool)
โโโโ cnlEndLongDeal (series__bool)
โโโโ cnlEndShortDeal (series__bool)
Indikator dan strategi
CommonTypesMapUtilLibrary "CommonTypesMapUtil"
Common type Container library, for central usage across other reference libraries.
ArrayBool
โโFields:
โโโโ v (bool )
ArrayBox
โโFields:
โโโโ v (box )
ArrayPoint
โโFields:
โโโโ v (chart.point )
ArrayColor
โโFields:
โโโโ v (color )
ArrayFloat
โโFields:
โโโโ v (float )
ArrayInt
โโFields:
โโโโ v (int )
ArrayLabel
โโFields:
โโโโ v (label )
ArrayLine
โโFields:
โโโโ v (line )
ArrayLinefill
โโFields:
โโโโ v (linefill )
ArrayString
โโFields:
โโโโ v (string )
ArrayTable
โโFields:
โโโโ v (table )
signal_datagramThe purpose of this library is to split and merge an integer into useful pieces of information that can easily handled and plotted.
The basic piece of information is one word. Depending on the underlying numerical system a word can be a bit, octal, digit, nibble, or byte.
The user can define channels. Channels are named groups of words. Multiple words can be combined to increase the value range of a channel.
A datagram is a description of the user-defined channels in an also user-defined numeric system that also contains all runtime information that is necessary to split and merge the integer.
This library simplifies the communication between two scripts by allowing the user to define the same datagram in both scripts.
On the sender's side, the channel values can be merged into one single integer value called signal. This signal can be 'emitted' using the plot function. The other script can use the 'input.source' function to receive that signal.
On the receiver's end based on the same datagram, the signal can be split into several channels. Each channel has the piece of information that the sender script put.
In the example of this library, we use two channels and we have split the integer in half. However, the user can add new channels, change them, and give meaning to them according to the functionality he wants to implement and the type of information he wants to communicate.
Nowadays many 'input.source' calls are allowed to pass information between the scripts, When that is not a price or a floating value, this library is very useful.
The reason is that most of the time, the convention that is used is not clear enough and it is easy to do things the wrong way or break them later on.
With this library validation checks are done during the initialization minimizing the possibility of error due to some misconceptions.
Library "signal_datagram"
Conversion of a datagram type to a signal that can be "send" as a single value from an indicator to a strategy script
method init(this, positions, maxWords)
โโinit - Initialize if the word positons array with an empty array
โโNamespace types: WordPosArray
โโParameters:
โโโโ this (WordPosArray) : - The word positions array object
โโโโ positions (int ) : - The array that contains all the positions of the worlds that shape the channel
โโโโ maxWords (int) : - The maximum words allowed based on the span
โโReturns: The initialized object
method init(this)
โโinit - Initialize if the channels word positons map with an empty map
โโNamespace types: ChannelDesc
โโParameters:
โโโโ this (ChannelDesc) : - The channels' descriptor object
โโReturns: The initialized object
method init(this, numericSystem, channelDesc)
โโinit - Initialize if the datagram
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object
โโโโ numericSystem (simple string) : - The numeric system of the words to be used
โโโโ channelDesc (ChannelDesc) : - The channels descriptor that contains the positions of the words that each channel consists of
โโReturns: The initialized object
method add_channel(this, name, positions)
โโadd_channel - Add a new channel descriptopn with its name and its corresponding word positons to the map
โโNamespace types: ChannelDesc
โโParameters:
โโโโ this (ChannelDesc) : - The channels' descriptor object to update
โโโโ name (simple string)
โโโโ positions (int )
โโReturns: The initialized object
method set_signal(this, value)
โโset_signal - Set the signal value
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to update
โโโโ value (int) : - The signal value to set
method get_signal(this)
โโget_signal - Get the signal value
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to query
โโReturns: The value of the signal in digits
method set_signal_sign(this, sign)
โโset_signal_sign - Set the signal sign
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to update
โโโโ sign (int) : - The negative -1 or positive 1 sign of the underlying value
method get_signal_sign(this)
โโget_signal_sign - Get the signal sign
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to query
โโReturns: The sign of the signal value -1 if it is negative and 1 if it is possitive
method get_channel_names(this)
โโget_channel_names - Get an array of all channel names
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram)
โโReturns: An array that has all the channel names that are used by the datagram
method set_channel_value(this, channelName, value)
โโset_channel_value - Set the value of the channel
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to update
โโโโ channelName (simple string) : - The name of the channel to set the value to. Then name should be as described int the schemas channel descriptor
โโโโ value (int) : - The channel value to set
method set_all_channels_value(this, value)
โโset_all_channels_value - Set the value of all the channels
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to update
โโโโ value (int) : - The channel value to set
method set_all_channels_max_value(this)
โโset_all_channels_value - Set the value of all the channels
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to update
method get_channel_value(this, channelName)
โโget_channel_value - Get the value of the channel
โโNamespace types: Datagram
โโParameters:
โโโโ this (Datagram) : - The datagram object to query
โโโโ channelName (simple string)
โโReturns: Digit group of words (bits/octals/digits/nibbles/hexes/bytes) found at the channel accodring to the schema
WordDesc
โโFields:
โโโโ numericSystem (series__string)
โโโโ span (series__integer)
WordPosArray
โโFields:
โโโโ positions (array__integer)
ChannelDesc
โโFields:
โโโโ map (map__series__string:|WordPosArray|#OBJ)
Schema
โโFields:
โโโโ wordDesc (|WordDesc|#OBJ)
โโโโ channelDesc (|ChannelDesc|#OBJ)
Signal
โโFields:
โโโโ value (series__integer)
โโโโ isNegative (series__bool)
โโโโ words (array__integer)
Datagram
โโFields:
โโโโ schema (|Schema|#OBJ)
โโโโ signal (|Signal|#OBJ)
lib_retracement_labelLibrary "lib_retracement_label"
creates a retracement label between the origin and target of a retracement, updating it's position (via update + draw) when the target moves.
create_tooltip(name, min, max, tol_min, tol_max)
โโParameters:
โโโโ name (string)
โโโโ min (float)
โโโโ max (float)
โโโโ tol_min (float)
โโโโ tol_max (float)
method update(this)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ this (RetracementLabel)
method create_retracement_label(this, move_endpoint, args, tooltip)
โโCreates a new RetracementLabel object.
โโNamespace types: D.Line
โโParameters:
โโโโ this (Line type from robbatt/lib_plot_objects/23)
โโโโ move_endpoint (Point type from robbatt/lib_plot_objects/23)
โโโโ args (LabelArgs type from robbatt/lib_plot_objects/23)
โโโโ tooltip (string)
method create_retracement_label(this, move_end, args, tooltip)
โโCreates a new RetracementLabel object.
โโNamespace types: D.Line
โโParameters:
โโโโ this (Line type from robbatt/lib_plot_objects/23)
โโโโ move_end (Pivot type from robbatt/lib_pivot/43)
โโโโ args (LabelArgs type from robbatt/lib_plot_objects/23)
โโโโ tooltip (string)
method enqueue(id, item, max)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ id (RetracementLabel )
โโโโ item (RetracementLabel)
โโโโ max (int)
method draw(this)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ this (RetracementLabel)
method draw(this)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ this (RetracementLabel )
method delete(this)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ this (RetracementLabel)
method delete(this)
โโNamespace types: RetracementLabel
โโParameters:
โโโโ this (RetracementLabel )
RetracementLabel
โโFields:
โโโโ move_endpoint (|robbatt/lib_plot_objects/23;Point|#OBJ)
โโโโ center_label (|robbatt/lib_plot_objects/23;CenterLabel|#OBJ)
SimilarityMeasuresLibrary "SimilarityMeasures"
Similarity measures are statistical methods used to quantify the distance between different data sets
or strings. There are various types of similarity measures, including those that compare:
- data points (SSD, Euclidean, Manhattan, Minkowski, Chebyshev, Correlation, Cosine, Camberra, MAE, MSE, Lorentzian, Intersection, Penrose Shape, Meehl),
- strings (Edit(Levenshtein), Lee, Hamming, Jaro),
- probability distributions (Mahalanobis, Fidelity, Bhattacharyya, Hellinger),
- sets (Kumar Hassebrook, Jaccard, Sorensen, Chi Square).
---
These measures are used in various fields such as data analysis, machine learning, and pattern recognition. They
help to compare and analyze similarities and differences between different data sets or strings, which
can be useful for making predictions, classifications, and decisions.
---
References:
en.wikipedia.org
cran.r-project.org
numerics.mathdotnet.com
github.com
github.com
github.com
Encyclopedia of Distances, doi.org
ssd(p, q)
โโSum of squared difference for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Measure of distance that calculates the squared euclidean distance.
euclidean(p, q)
โโEuclidean distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Measure of distance that calculates the straight-line (or Euclidean).
manhattan(p, q)
โโManhattan distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Measure of absolute differences between both points.
minkowski(p, q, p_value)
โโMinkowsky Distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโโโ p_value (float) : `float` P value, default=1.0(1: manhatan, 2: euclidean), does not support chebychev.
โโReturns: Measure of similarity in the normed vector space.
chebyshev(p, q)
โโChebyshev distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Measure of maximum absolute difference.
correlation(p, q)
โโCorrelation distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Measure of maximum absolute difference.
cosine(p, q)
โโCosine distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Cosine distance between vectors `p` and `q`.
---
angiogenesis.dkfz.de
camberra(p, q)
โโCamberra distance for N dimensions.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Weighted measure of absolute differences between both points.
mae(p, q)
โโMean absolute error is a normalized version of the sum of absolute difference (manhattan).
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Mean absolute error of vectors `p` and `q`.
mse(p, q)
โโMean squared error is a normalized version of the sum of squared difference.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Mean squared error of vectors `p` and `q`.
lorentzian(p, q)
โโLorentzian distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Lorentzian distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
intersection(p, q)
โโIntersection distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Intersection distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
penrose(p, q)
โโPenrose Shape distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Penrose shape distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
meehl(p, q)
โโMeehl distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` Vector with first numeric distribution.
โโโโ q (float ) : `array` Vector with second numeric distribution.
โโReturns: Meehl distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
edit(x, y)
โโEdit (aka Levenshtein) distance for indexed strings.
โโParameters:
โโโโ x (int ) : `array` Indexed array.
โโโโ y (int ) : `array` Indexed array.
โโReturns: Number of deletions, insertions, or substitutions required to transform source string into target string.
---
generated description:
The Edit distance is a measure of similarity used to compare two strings. It is defined as the minimum number of
operations (insertions, deletions, or substitutions) required to transform one string into another. The operations
are performed on the characters of the strings, and the cost of each operation depends on the specific algorithm
used.
The Edit distance is widely used in various applications such as spell checking, text similarity, and machine
translation. It can also be used for other purposes like finding the closest match between two strings or
identifying the common prefixes or suffixes between them.
---
github.com
www.red-gate.com
planetcalc.com
lee(x, y, dsize)
โโDistance between two indexed strings of equal length.
โโParameters:
โโโโ x (int ) : `array` Indexed array.
โโโโ y (int ) : `array` Indexed array.
โโโโ dsize (int) : `int` Dictionary size.
โโReturns: Distance between two strings by accounting for dictionary size.
---
www.johndcook.com
hamming(x, y)
โโDistance between two indexed strings of equal length.
โโParameters:
โโโโ x (int ) : `array` Indexed array.
โโโโ y (int ) : `array` Indexed array.
โโReturns: Length of different components on both sequences.
---
en.wikipedia.org
jaro(x, y)
โโDistance between two indexed strings.
โโParameters:
โโโโ x (int ) : `array` Indexed array.
โโโโ y (int ) : `array` Indexed array.
โโReturns: Measure of two strings' similarity: the higher the value, the more similar the strings are.
The score is normalized such that `0` equates to no similarities and `1` is an exact match.
---
rosettacode.org
mahalanobis(p, q, VI)
โโMahalanobis distance between two vectors with population inverse covariance matrix.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโโโ VI (matrix) : `matrix` Inverse of the covariance matrix.
โโReturns: The mahalanobis distance between vectors `p` and `q`.
---
people.revoledu.com
stat.ethz.ch
docs.scipy.org
fidelity(p, q)
โโFidelity distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Bhattacharyya Coefficient between vectors `p` and `q`.
---
en.wikipedia.org
bhattacharyya(p, q)
โโBhattacharyya distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Bhattacharyya distance between vectors `p` and `q`.
---
en.wikipedia.org
hellinger(p, q)
โโHellinger distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The hellinger distance between vectors `p` and `q`.
---
en.wikipedia.org
jamesmccaffrey.wordpress.com
kumar_hassebrook(p, q)
โโKumar Hassebrook distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Kumar Hassebrook distance between vectors `p` and `q`.
---
github.com
jaccard(p, q)
โโJaccard distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Jaccard distance between vectors `p` and `q`.
---
github.com
sorensen(p, q)
โโSorensen distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโReturns: The Sorensen distance between vectors `p` and `q`.
---
people.revoledu.com
chi_square(p, q, eps)
โโChi Square distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโโโ eps (float)
โโReturns: The Chi Square distance between vectors `p` and `q`.
---
uw.pressbooks.pub
stats.stackexchange.com
www.itl.nist.gov
kulczynsky(p, q, eps)
โโKulczynsky distance between provided vectors.
โโParameters:
โโโโ p (float ) : `array` 1D Vector.
โโโโ q (float ) : `array` 1D Vector.
โโโโ eps (float)
โโReturns: The Kulczynsky distance between vectors `p` and `q`.
---
github.com
FunctionMatrixCovarianceLibrary "FunctionMatrixCovariance"
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or varianceโcovariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector.
Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions. As an example, the variation in a collection of random points in two-dimensional space cannot be characterized fully by a single number, nor would the variances in the `x` and `y` directions contain all of the necessary information; a `2 ร 2` matrix would be necessary to fully characterize the two-dimensional variation.
Any covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the covariance of each element with itself).
The covariance matrix of a random vector `X` is typically denoted by `Kxx`, `ฮฃ` or `S`.
~wikipedia.
method cov(M, bias)
โโEstimate Covariance matrix with provided data.
โโNamespace types: matrix
โโParameters:
โโโโ M (matrix) : `matrix` Matrix with vectors in column order.
โโโโ bias (bool)
โโReturns: Covariance matrix of provided vectors.
---
en.wikipedia.org
numpy.org
PScolorLibrary "PScolor"
TODO: add library description here
////variable/////////////////////////////
//COLOR brightness
Each color has 0โ9 / A1โA4
(5th standard: Bright if small, dark if big)
(Fluorescence based on A2)
//Color Name
1 = RED
2 = DEEP_ORANGE
3 = ORANGE
4 = AMBER
5 = YELLOW
6 = LIME
7 = LIGHT_GREEN
8 = GREEN
9 = TEAL
10= CYAN
11= LIGHT_BLUE
12= BLUE
13= INDIGO
14= DEEP_PURPLE
15= PURPLE
16= PINK
0= GRAY
// Transparency
///////////////////////////////////////
lvcol(colormode, Number, trans)
โโParameters:
โโโโ colormode (int)
โโโโ Number (simple int)
โโโโ trans (float)
lvcolA(colormode, Number, trans)
โโParameters:
โโโโ colormode (int)
โโโโ Number (simple int)
โโโโ trans (float)
lvcol2(colormode, colorName, trans)
โโParameters:
โโโโ colormode (int)
โโโโ colorName (simple string)
โโโโ trans (float)
lvcol2A(colormode, colorName, trans)
โโParameters:
โโโโ colormode (int)
โโโโ colorName (simple string)
โโโโ trans (float)
TradeTrackerv2Library "TradeTrackerv2"
This library can be used to track (hypothetical) trades on the chart. Enter the Open, SL, and TP prices (or TP in R to have it calculated) and then call Trade.TrackTrade(barIndex). Keep track of your trades in an array and then simply call TradeTracker.UpdateAllTrades(close) to update all trades based on the current close price.
How to use:
1. Import the library, as always. I'm assuming the alias of "Tracker" below.
2. The Type Trade is exported, so generate a Trade object like newTrade = Tracker.Trade.new() .
3. Set the values for Open, SL, and TP. TP can be set either by price or by R, which will calculate the R based on the Open->SL range:
newTrade.priceOpen = 1.0
newTrade.priceSl = 0.5
newTrade.priceTp = 2.0
-- or in place of the third line above --
newTrade.rTp = 2
4. On each interval you want to update (whether that's per tick/close or on each bar), call trades.UpdateAllTrades(close) . This snippet assumes you have an array named trades (var trades = array.new()) .
In future updates, more customization options will be created. This is the initial prototype.
method MakeTradeLines(t, barIdx)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ barIdx (int)
method UpdateLabel(t)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
method MakeLabel(t, barIdx)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ barIdx (int)
method CloseTrade(t)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
method OpenTrade(t)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
method OpenCloseTrade(t, _close)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ _close (float)
method CalculateProfits(t, _close)
โโCalculates profits/losses for the Trade, given _close price
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ _close (float)
method UpdateTrade(t, _close)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ _close (float)
method SetInitialValues(t, barIdx)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ barIdx (int)
method UpdateAllTrades(trades, _close)
โโNamespace types: Trade
โโParameters:
โโโโ trades (Trade )
โโโโ _close (float)
method TrackTrade(t, barIdx)
โโNamespace types: Trade
โโParameters:
โโโโ t (Trade)
โโโโ barIdx (int)
Trade
โโFields:
โโโโ id (series__integer)
โโโโ isOpen (series__bool)
โโโโ isClosed (series__bool)
โโโโ isBuy (series__bool)
โโโโ priceOpen (series__float)
โโโโ priceTp (series__float)
โโโโ priceSl (series__float)
โโโโ rTP (series__float)
โโโโ profit (series__float)
โโโโ r (series__float)
โโโโ resultR (series__float)
โโโโ lineOpen (series__line)
โโโโ lineTp (series__line)
โโโโ lineSl (series__line)
โโโโ labelStats (series__label)
utilsLibrary "utils"
TODO: add library description here
maCustomseries(source, typeMa, length)
โโParameters:
โโโโ source (float)
โโโโ typeMa (simple string)
โโโโ length (simple int)
barCrossoverCounter(signalPrice, basePrice)
โโParameters:
โโโโ signalPrice (float)
โโโโ basePrice (float)
barCrossunderCounter(signalPrice, basePrice)
โโParameters:
โโโโ signalPrice (float)
โโโโ basePrice (float)
WHAlertCommandLibrary "WHAlertCommand"
f_WH_Risk(risk_Type_)
โโParameters:
โโโโ risk_Type_ (string)
f_WH_Open_Position(uuid_, enable_Buy_, enable_Sell, enable_All_Group_Members_, enable_Close_Opposite_Side_, enable_Risk_, risk_Type_, signal_Type_Buy_Or_Sell)
โโParameters:
โโโโ uuid_ (string)
โโโโ enable_Buy_ (bool)
โโโโ enable_Sell (bool)
โโโโ enable_All_Group_Members_ (bool)
โโโโ enable_Close_Opposite_Side_ (bool)
โโโโ enable_Risk_ (bool)
โโโโ risk_Type_ (string)
โโโโ signal_Type_Buy_Or_Sell (string)
f_WH_TP(uuid_, position_Size_Percent_, side_)
โโParameters:
โโโโ uuid_ (string)
โโโโ position_Size_Percent_ (float)
โโโโ side_ (string)
f_WH_MARKET_CLOSE(uuid_, side_)
โโParameters:
โโโโ uuid_ (string)
โโโโ side_ (string)
RiskToolsLibrary "RiskTools"
Provides functions for calculating risk metrics
pctDrop(start, result)
โโCalculates what is the percentage drop from a reference price
โโParameters:
โโโโ start (float) : Starting price before the drop occurred
โโโโ result (float) : Resulting price to which the percentage drop occurred
โโReturns: Percentage drop from "start" to "result"
priceBeforeDrop(pctDrop, result)
โโCalculates a starting price given a resulting price and a percentage drop to that price
โโParameters:
โโโโ pctDrop (float) : Percentage drop
โโโโ result (float) : Resulting price to which the percentage drop occurred
โโReturns: The starting price from which a percentage drop "pctDrop" gave a "result"
dropzone(price, masource, malength, window, zonesize)
โโCalculates drop zone as an integer representing some multiple of the "zoning size"
โโParameters:
โโโโ price (float) : The current price from which you want to calculate the drop zone
โโโโ masource (float) : The source series used in the SMA calculation from which the floor price is determined
โโโโ malength (simple int) : The length used in the SMA calculation from which the floor price is determined
โโโโ window (simple int) : The lookback period from which to calculate the floor price
โโโโ zonesize (simple int)
โโReturns: The zone identifier as a multiple of the zone size. A value of zero or less is translated to the first zone.
RSNPSDLibrary "RSNPSD"
EMA5(source, EMAlength, Smoothlength)
โโParameters:
โโโโ source (float)
โโโโ EMAlength (simple int)
โโโโ Smoothlength (simple int)
SLOPE(source, slopeDistance)
โโParameters:
โโโโ source (float)
โโโโ slopeDistance (simple int)
print(txt)
โโParameters:
โโโโ txt (string)
libHTF[without request.security()]Library "libHTF"
libHTF: use HTF values without request.security()
This library enables to use HTF candles without request.security().
Basic data structure
Using to access values in the same manner as series variable.
The last member of HTF array is always latest current TF's data.
If new bar in HTF(same as last bar closes), new member is pushed to HTF array.
2nd from the last member of HTF array is latest fixed(closed) bar.
HTF: How to use
1. set TF
tf_higher() function selects higher TF. TF steps are ("1","5","15","60","240","D","W","M","3M","6M","Y").
example:
tfChart = timeframe.period
htf1 = tf_higher(tfChart)
2. set HTF matrix
htf_candle() function returns 1 bool and 1 matrix.
bool is a flag for start of new candle in HTF context.
matrix is HTF candle data(0:open,1:time_open,2:close,3:time_close,4:high,5:time:high,6:low,7:time_low).
example:
=htf_candle(htf1)
3. how to access HTF candle data
you can get values using .lastx() method.
please be careful, return value is always float evenif it is "time". you need to cast to int time value when using for xloc.bartime.
example:
htf1open=m1.lastx("open")
htf1close=m1.lastx("close")
//if you need to use histrical value.
lastopen=open
lasthtf1open=m1.lastx("open",1)
4. how to store Data of HTF context
you have to use array to store data of HTF context.
array.htf_push() method handles the last member of array. if new_bar in HTF, it push new member. otherwise it set value to the last member.
example:
array a_close=array.new(1,na)
a_close.htf_push(b_new_bar1,m1.lastx("close"))
HTFsrc: How to use
1. how to setup src.
set_src() function is set current tf's src from string(open/high/low/close/hl2/hlc3/ohlc4/hlcc4).
set_htfsrc() function returns src array of HTF candle.
example:
_src="ohlc4"
src=set_src(_src)
htf1src=set_htfsrc(_src,b_new_bar1,m1)
(if you need to use HTF src in series float)
s_htf1src=htf1src.lastx()
HighLow: How to use
1. set HTF arrays
highlow() and htfhighlow() function calculates high/low and return high/low prices and time.
the functions return 1 int and 8arrays.
int is a flag for new high(1) or new low(-1).
arrays are high/low and return high/low data. float for price, int for time.
example
=
highlow()
=
htfhighlow(m1)
2. how to access HighLow data
you can get values using .lastx() method.
example:
if i_renew==1
myhigh=a_high.lastx()
//if you need to use histrical value.
myhigh=a_high.lastx(1)
other functions
functions for HTF candle matrix or HTF src array in this script are
htf_sma()/htf_ema()/htf_rma()
htf_rsi()/htf_rci()/htf_dmi()
method lastx(arrayid, lastindex)
โโmethod like array.last. it returns lastindex from the last member, if parameter is set.
โโNamespace types: float
โโParameters:
โโโโ arrayid (float )
โโโโ lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
โโReturns: float value of lastindex from the last member of the array. returns na, if fail.
method lastx(arrayid, lastindex)
โโmethod like array.last. it returns lastindex from the last member, if parameter is set.
โโNamespace types: int
โโParameters:
โโโโ arrayid (int )
โโโโ lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
โโReturns: int value of lastindex from the last member of the array. returns na, if fail.
method lastx(m, _type, lastindex)
โโmethod for handling htf matrix.
โโNamespace types: matrix
โโParameters:
โโโโ m (matrix) : (matrix) matrix for htf candle.
โโโโ _type (string) : (string) value type of htf candle:
โโโโ lastindex (int) : (int) default value is "0"(the last member).
โโReturns: (float) value of htf candle. (caution: need to cast float to int to use time values!)
method set_last(arrayid, val)
โโmethod to set a value of the last member of the array. it sets value to the last member.
โโNamespace types: float
โโParameters:
โโโโ arrayid (float )
โโโโ val (float) : (float) value to set.
โโReturns: nothing
method htf_push(arrayid, b, val)
โโmethod to push new member to htf context. if new bar in htf, it works as push. else it works as set_last.
โโNamespace types: float
โโParameters:
โโโโ arrayid (float )
โโโโ b (bool) : (bool) true:push,false:set_last
โโโโ val (float) : (float) _f the value to set.
โโReturns: nothing
method tf_higher(tf)
โโmethod to set higher tf from tf string. TF steps are .
โโNamespace types: series string, simple string, input string, const string
โโParameters:
โโโโ tf (string) : (string) tf string
โโReturns: (string) string of higher tf.
htf_candle(_tf, _TZ)
โโbuild htf candles
โโParameters:
โโโโ _tf (string) : (string) tf string.
โโโโ _TZ (string) : of timezone. default value is "GMT+3".
โโReturns: bool for new bar@htf and matrix for snapshot of htf candle
set_src(_src_type)
โโset src.
โโParameters:
โโโโ _src_type (string) : (string) type of source:
โโReturns: (series float) src value
set_htfsrc(_src_type, _nb, _m)
โโset htf src.
โโParameters:
โโโโ _src_type (string) : (string) type of source:
โโโโ _nb (bool) : (bool) flag of new bar
โโโโ _m (matrix) : (matrix) matrix for htf candle.
โโReturns: (array) array of src value
is_up()
last_is_up()
peak_bottom(_latest, _last)
โโParameters:
โโโโ _latest (bool)
โโโโ _last (bool)
htf_is_up(_m)
โโParameters:
โโโโ _m (matrix)
htf_last_is_up(_m)
โโParameters:
โโโโ _m (matrix)
highlow(_b_bartime_price)
โโParameters:
โโโโ _b_bartime_price (bool)
htfhighlow(_m, _b_bartime_price)
โโParameters:
โโโโ _m (matrix)
โโโโ _b_bartime_price (bool)
htf_sma(_a_src, _len)
โโParameters:
โโโโ _a_src (float )
โโโโ _len (int)
htf_rma(_a_src, _new_bar, _len)
โโParameters:
โโโโ _a_src (float )
โโโโ _new_bar (bool)
โโโโ _len (int)
htf_ema(_a_src, _new_bar, _len)
โโParameters:
โโโโ _a_src (float )
โโโโ _new_bar (bool)
โโโโ _len (int)
htf_rsi(_a_src, _new_bar, _len)
โโParameters:
โโโโ _a_src (float )
โโโโ _new_bar (bool)
โโโโ _len (int)
rci(_src, _len)
โโParameters:
โโโโ _src (float)
โโโโ _len (int)
htf_rci(_a_src, _len)
โโParameters:
โโโโ _a_src (float )
โโโโ _len (int)
htf_dmi(_m, _new_bar, _len, _ma_type)
โโParameters:
โโโโ _m (matrix)
โโโโ _new_bar (bool)
โโโโ _len (int)
โโโโ _ma_type (string)
TradeLibrary "Trade"
A Trade Tracking Library
Monitor conditions with less code by using Arrays. When your conditions are met in chronologically, a signal is returned and the scanning starts again.
Create trades automatically with Stop Loss, Take Profit and Entry. The trades will automatically track based on the market movement and update when the targets are hit.
Sample Usage
Enter a buy trade when RSI crosses below 70 then crosses above 80 before it crosses 40.
Note: If RSI crosses 40 before 80, No trade will be entered.
rsi = ta.rsi(close, 21)
buyConditions = array.new_bool()
buyConditions.push(ta.crossunder(rsi, 70))
buyConditions.push(ta.crossover(rsi, 80))
buy = Trade.signal(buyConditions, ta.crossunder(rsi, 40))
trade = Trade.new(close-(100*syminfo.mintick), close +(200*syminfo.mintick), condition=buy)
plot(trade.takeprofit, "TP", style=plot.style_circles, linewidth=4, color=color.lime)
alertcondition(trade.tp_hit, "TP Hit")
method signal(conditions, reset)
โโSignal Conditions
โโNamespace types: bool
โโParameters:
โโโโ conditions (bool )
โโโโ reset (bool)
โโReturns: Boolean: True when all the conditions have occured
method update(this, stoploss, takeprofit, entry)
โโUpdate Trade Parameters
โโNamespace types: Trade
โโParameters:
โโโโ this (Trade)
โโโโ stoploss (float)
โโโโ takeprofit (float)
โโโโ entry (float)
โโReturns: nothing
method clear(this)
โโClear Trade Parameters
โโNamespace types: Trade
โโParameters:
โโโโ this (Trade)
โโReturns: nothing
method track(this, _high, _low)
โโTrack Trade Parameters
โโNamespace types: Trade
โโParameters:
โโโโ this (Trade)
โโโโ _high (float)
โโโโ _low (float)
โโReturns: nothing
new(stoploss, takeprofit, entry, _high, _low, condition, update)
โโNew Trade with tracking
โโParameters:
โโโโ stoploss (float)
โโโโ takeprofit (float)
โโโโ entry (float)
โโโโ _high (float)
โโโโ _low (float)
โโโโ condition (bool)
โโโโ update (bool)
โโReturns: a Trade with targets and updates if stoploss or takeprofit is hit
new()
โโNew Empty Trade
โโReturns: an empty trade
Trade
โโFields:
โโโโ stoploss (series__float)
โโโโ takeprofit (series__float)
โโโโ entry (series__float)
โโโโ sl_hit (series__bool)
โโโโ tp_hit (series__bool)
โโโโ open (series__integer)
imlibLibrary "imlib"
Description
The library allows you to display images in your scripts utilising the objects. You can change the image size and screen aspect ratio (the ratio of width to height which you can change if the image is too wide / tall). The library has "example()" function which you can use to see how it works. It also has a handy "logo()" function which you can use to quickly display an image by passing the "Image data string", table position, image size and aspect ratio. And of course you can use it in your own custom way by taking the "logo()" function as an example and modifying the code to your needs.
Since tables in Pinescript are limited to 100 by 100 cells, the limit for image's size is also 100x100 px. All the necessary data to display an image is passed as a string variable, and since Pinescript has a limit of 4096 characters for variables of type, that string can have a maximum length of 4096 characters, which is enough to display a 64x64px image (but can be enough to display a 100x100 image, depending on the image itself).
Below you can find the definitions of functions for this library.
_decompress(data)
โโ: Decompresses string with data image
โโParameters:
โโโโ data (string)
โโReturns: : Array of with decompressed data
load(data)
โโ: Splits the string with image data into components and builds an object
โโParameters:
โโโโ data (string)
โโReturns: : An object
show(imgdata, table_id, image_size, screen_ratio)
โโ: Displays an image in a table
โโParameters:
โโโโ imgdata (ImgData)
โโโโ table_id (table)
โโโโ image_size (float)
โโโโ screen_ratio (string)
โโReturns: : nothing
example()
โโ: Use it as an example of how this library works and how to use it in your own scripts
โโReturns: : nothing
logo(imgdata, position, image_size, screen_ratio)
โโ: Displays logo using image data string
โโParameters:
โโโโ imgdata (string)
โโโโ position (string)
โโโโ image_size (float)
โโโโ screen_ratio (string)
โโReturns: : nothing
ImgData
โโFields:
โโโโ w (series__integer)
โโโโ h (series__integer)
โโโโ s (series__string)
โโโโ pal (series__string)
โโโโ data (array__string)
multidataLibrary "multidata"
A library for multi-dimensional data arrays.
Full documentation: faiyaz7283.github.io
This library is designed to enhance data storage capabilities in Pine Script, enabling users to work with two separate data structures: data2d (key -> main-value | alternate-value) and data3d (primary key -> data key-> main-value | alternate-value). These structures facilitate storing key-value pairs in a flexible and efficient manner, offering various methods for manipulation and retrieval of data. Please check out the full documentation at faiyaz7283.github.io .
Extended Moving Average (MA) LibraryThis Extended Moving Average Library is a sophisticated and comprehensive tool for traders seeking to expand their arsenal of moving averages for more nuanced and detailed technical analysis.
The library contains various types of moving averages, each with two versions - one that accepts a simple constant length parameter and another that accepts a series or changing length parameter.
This makes the library highly versatile and suitable for a wide range of strategies and trading styles.
Moving Averages Included:
Simple Moving Average (SMA): This is the most basic type of moving average. It calculates the average of a selected range of prices, typically closing prices, by the number of periods in that range.
Exponential Moving Average (EMA): This type of moving average gives more weight to the latest data and is thus more responsive to new price information. This can help traders to react faster to recent price changes.
Double Exponential Moving Average (DEMA): This is a composite of a single exponential moving average, a double exponential moving average, and an exponential moving average of a triple exponential moving average. It aims to eliminate lag, which is a key drawback of using moving averages.
Jurik Moving Average (JMA): This is a versatile and responsive moving average that can be adjusted for market speed. It is designed to stay balanced and responsive, regardless of how long or short it is.
Kaufman's Adaptive Moving Average (KAMA): This moving average is designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Smoothed Moving Average (SMMA): This type of moving average applies equal weighting to all observations and smooths out the data.
Triangular Moving Average (TMA): This is a double smoothed simple moving average, calculated by averaging the simple moving averages of a dataset.
True Strength Force (TSF): This is a moving average of the linear regression line, a statistical tool used to predict future values from past values.
Volume Moving Average (VMA): This is a simple moving average of a volume, which can help to identify trends in volume.
Volume Adjusted Moving Average (VAMA): This moving average adjusts for volume and can be more responsive to volume changes.
Zero Lag Exponential Moving Average (ZLEMA): This type of moving average aims to eliminate the lag in traditional EMAs, making it more responsive to recent price changes.
Selector: The selector function allows users to easily select and apply any of the moving averages included in the library inside their strategy.
This library provides a broad selection of moving averages to choose from, allowing you to experiment with different types and find the one that best suits your trading strategy.
By providing both simple and series versions for each moving average, this library offers great flexibility, enabling users to pass both constant and changing length parameters as needed.
ta_mLibrary "ta_m"
This library is a Pine Scriptโข programmerโs tool containing calcs for my oscillators and some helper functions.
upDnIntrabarVolumesByPolarity()
โโDetermines if the volume for an intrabar is up or down.
โโReturns: ( ) A tuple of two values, one of which contains the bar's volume. `upVol` is the positive volume of up bars. `dnVol` is the negative volume of down bars.
Note that when this function is designed to be called with `request.security_lower_tf()`,
which will return a tuple of "array" arrays containing up and dn volume for all the intrabars in a chart bar.
upDnIntrabarVolumesByPrice()
โโDetermines if the intrabar volume is up or down
โโReturns: ( ) A tuple of two values, one of which contains the bar's volume. `upVol` is the positive volume of up bars. `dnVol` is the negative volume of down bars.
Note that when this function is designed to be called with `request.security_lower_tf()`,
which will return a tuple of "array" arrays containing up and dn volume for all the intrabars in a chart bar.
merge_pinbar_modifiedLibrary "merge_pinbar"
Published by @dandrideng
Modified by @RpNm1337
merge_pinbar: merge bars and check whether the bar is a pinbar
merge_pinbar(period, max_bars)
โโmerge_pinbar: merge bars and check whether the bar is a pinbar
โโParameters:
โโโโ period (simple int)
โโโโ max_bars (simple int)
โโReturns: array:
A_Taders_Edge_LIBRARYLibrary "A_Taders_Edge_LIBRARY"
RCI(_rciLength, _close, _interval, _outerMostRangeOfOscillator)
โโ- You will see me using this a lot. DEFINITELY my favorite oscillator to utilize for SO many different things from timing entries/exits to determining trends.
โโParameters:
โโโโ _rciLength (int)
โโโโ _close (float)
โโโโ _interval (int)
โโโโ _outerMostRangeOfOscillator (int)
โโReturns: - Outputs a single RCI value that will between (-)_outerMostRangeOfOscillator to (+)_outerMostRangeOfOscillator
InvalidTID(_close, _showInvalidAssets, _securityTickerid, _invalidArray)
โโ- This is to add a table on the right of your chart that prints all the TickerID's that were either not formulated correctly in the scripts input or that is not a valid symbol and should be changed.
โโParameters:
โโโโ _close (float)
โโโโ _showInvalidAssets (simple bool)
โโโโ _securityTickerid (string)
โโโโ _invalidArray (string )
โโReturns: - Does NOT return a value but rather the table with the invalid TickerID's from the scripts input that need to be changed.
LabelLocation(_firstLocation)
โโ- This is ONLY for when you are wanting to print ALERT LABELS with the assets name for when an alert trigger occurs for that asset. There are a total of 40 assets that can be used in each copy of the script. You don't want labels from different assets printing on top of each other because you will not be able to read the asset name that the label is for. Ex. If you put your _firstLocation in the input settings as 1 and have 40 assets on this copy of the scanner then the first asset in the list is assigned to the location value 1 on the scale, and the 2nd in the list is assigned to location value 2...and so on. If your first location is set to 81 then the 1st asset is 81 and 2nd is 82 and so on.
โโParameters:
โโโโ _firstLocation (simple int)
โโReturns: - regardless of if you have the maximum amount of assets being screened (40 max), this export function will output 40 locationsโฆ So there needs to be 40 variables assigned to the tuple in this export function. What I mean by that is there needs to be 40 variables between the ' '. If you only have 20 assets in your scripts input settings, then only the first 20 variables within the ' ' Will be assigned to a value location and the other 20 will be assigned 'NA'.
SeparateTickerids(_string)
โโ- You must form this single tickerID input string exactly as laid out in the water (a little gray circle at the end of the setting, that you hover your cursor over to read the details of). IF the string is formed correctly then it will break up. All of the tip rate is within the string into a total of 40 separate strings which will be all of the tickerIDs that the script is using in your MO scanner.
โโParameters:
โโโโ _string (simple string)
โโReturns: - this will output, 40 different security assets within the tuple output (ie. 40 variable within the ' ') regardless of if you were including 40 assets, to be screened in the MO Screener or not. if you have less than 40 assets, then once the variables are assigned to all of the tickerIDs, the rest of the variables will be assigned "NA".
TickeridForLabelsAndSecurity(_includeExchange, _ticker)
โโ- this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
โโParameters:
โโโโ _includeExchange (simple bool)
โโโโ _ticker (simple string)
โโReturns: - this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
PercentChange(_startingValue, _endingValue)
โโ- this is a quick export function to calculate how much % change has occurred between the _startingValue and the _endingValue that you input into the export function.
โโParameters:
โโโโ _startingValue (float)
โโโโ _endingValue (float)
โโReturns: - it will output a single percentage value between 0-100 with trailing numbers behind a decimal. If you want, only a certain amount of numbers behind the decimal, this export function needs to be put within a formatting function to do so. Explained in the MO Scanner INTRO VIDEO.
PrintedBarCount(_time, _barCntLength, _bcPmin)
โโ- This export function will outfit the percentage of printed bars (that occurred within _barCntLength amount of time) out of the MAX amount of bars that potentially COULD HAVE been printed. Iexplanation in the MO Scanner INTRO VIDEO.
โโParameters:
โโโโ _time (int)
โโโโ _barCntLength (int)
โโโโ _bcPmin (int)
โโReturns: - Gives 2 outputs. The first is the total % of Printed Bars within the user set time period and second is true/false according to if the Printed BarCount % is above the _bcPmin threshold that you input into this export function.
CandlestickPatternsLibrary "CandlestickPatterns"
This library provides a wide range of candlestick patterns, and available for user to call each pattern individually. It's a comprehensive and common tool designed for traders seeking to raise their technical analysis, and it may help users identify key turning of price action in financial instruments. Credit to public technical โ*All Candlestick Patterns*โ indicator.
abandonedBaby(order, d1)
โโThe "Abandoned Baby" candlestick pattern is a bullish/bearish pattern consists of three candles.
โโParameters:
โโโโ order (simple string) : (simple string) Pattern order type "bull" or "bear".
โโโโ d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
darkCloudCover(c1, n)
โโThe "Dark Cloud Cover" is a bearish pattern consists of two candles.
โโParameters:
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
doji(d0)
โโThe "Doji" is neither bullish or bearish consists of one candles.
โโParameters:
โโโโ d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
dojiStar(order, c1, n, d0)
โโThe "Doji Star" is a bullish/bearish pattern consists of two candles.
โโParameters:
โโโโ order (simple string) : (simple string) Pattern order type "bull" or "bear" .
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
โโโโ d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
downsideTasukiGap(c2, c1, n)
โโThe "Downside Tasuki Gap" is a bearish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
dragonflyDoji(d0)
โโThe "Dragon Fly Doji" is a bullish pattern consists of one candle.
โโParameters:
โโโโ d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
engulfing(order, c1, c0, n)
โโThe "Engulfing" is a bullish/bearish pattern consists of two candles.
โโParameters:
โโโโ order (simple string) : (simple string) Pattern order type "bull" or "bear".
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningDojiStar(c2, c0, d1, n)
โโThe "Evening Doji Star" is a bearish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningStar(c2, c1, c0, n)
โโThe "Evening Star" is a bearish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
fallingThreeMethods(c4, c3, c2, c1, c0, n)
โโThe "Falling Three Methods" is a bearish pattern consists of five candles.
โโParameters:
โโโโ c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
โโโโ c3 (simple bool) : (simple bool) 4th candle ago body must be lower than average. Optional argument, default is true.
โโโโ c2 (simple bool) : (simple bool) 3rd candle ago body must be lower than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) 2nd candle ago body must be lower than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
โโReturns: (bool)
fallingWindow()
โโThe "Falling Window" is a bearish pattern consists of two candles.
gravestoneDoji(d0)
โโThe "Gravestone Doji" is a bearish pattern consists of one candle.
โโParameters:
โโโโ d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
hammer(c0, n)
โโThe "Hammer" is a bullish pattern consists of one candle.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
hangingMan(c0, n)
โโThe "Hanging Man" is a bearish pattern consists of one candle.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
haramiCross(order, c1, n)
โโThe "Harami Cross" candlestick pattern is a bullish/bearish pattern consists of two candles.
โโParameters:
โโโโ order (string) : (simple string) Pattern order type "bull" or "bear".
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
harami(order, c1, c0, n)
โโThe "Harami" candlestick pattern is a bullish/bearish pattern consists of two candles.
โโParameters:
โโโโ order (string) : (simple string) Pattern order type "bull" or "bear"
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
invertedHammer(c0, n)
โโThe "Inverted Hammer" is a bullish pattern consists of one candle.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
kicking(order, c1, c0, n)
โโThe "Kicking" candlestick pattern is a bullish/bearish pattern consists of two candles.
โโParameters:
โโโโ order (string) : (simple string) Pattern order type "bull" or "bear"
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
longLowerShadow(l0)
โโThe "Long Lower Shadow" candlestick pattern is a bullish pattern consists of one candles.
โโParameters:
โโโโ l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 75.
longUpperShadow(u0)
โโThe "Long Upper Shadow" candlestick pattern is a bearish pattern consists of one candles.
โโParameters:
โโโโ u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 75.
marubozuBlack(c0, n)
โโThe "Marubozu Black" candlestick pattern is a bearish pattern consists of one candles.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
marubozuWhite(c0, n)
โโThe "Marubozu White" candlestick pattern is a bullish pattern consists of one candles.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningDojiStar(c2, d1, c0, n)
โโThe "Morning Doji Star" candlestick pattern is a bullish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningStar(c2, c1, c0, n)
โโThe "Morning Star" candlestick pattern is a bullish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
onNeck(c1, c0, n)
โโThe "On Neck" candlestick pattern is a bearish pattern consists of two candles.
โโParameters:
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Cuurent candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
piercing(c1, n)
โโThe "Piercing" candlestick pattern is a bullish pattern consists of two candles.
โโParameters:
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingThreeMethods(c4, c3, c2, c1, c0, n)
โโThe "Rising Three Methods" candlestick pattern is a bullish pattern consists of five candles.
โโParameters:
โโโโ c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
โโโโ c3 (simple bool) : (simple bool) 4th candle ago body must be Lower than average. Optional argument, default is true.
โโโโ c2 (simple bool) : (simple bool) 3rd candle ago body must be Lower than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) 2nd candle ago body must be Lower than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingWindow()
โโThe "Rising Window" candlestick pattern is a bullish pattern consists of two candle.
shootingStar(c0, n)
โโThe "Shooting Star" candlestick pattern is a bearish pattern consists of one candle.
โโParameters:
โโโโ c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
spinningTopBlack(l0, u0)
โโThe "Spinning Top Black" is neither bullish or bearish.
โโParameters:
โโโโ l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
โโโโ u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
spinningTopWhite(l0, u0)
โโThe "Spinning Top White" is neither bullish or bearish.
โโParameters:
โโโโ l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
โโโโ u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
threeBlackCrows(c2, c1, c0, n)
โโThe "Three Black Crows" candlestick pattern is a bearish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
threeWhiteSoldiers(c2, c1, c0, n)
โโThe "Three White Soldiers" candlestick pattern is a bullish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
triStar(order, d2, d1, d0)
โโThe "Tri Star" candlestick pattern is a bullish/bearish pattern consists of three candles.
โโParameters:
โโโโ order (simple string) : (simple string) Pattern order type "bull" or "bear".
โโโโ d2 (simple float) : (simple float) Before previous candle's body percentage out of candle range. Optional argument, default is 5.
โโโโ d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
โโโโ d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
tweezerBottom(c1, n)
โโThe "Tweezer Bottom" candlestick pattern is a bullish pattern consists of two candles.
โโParameters:
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
tweezerTop(c1, n)
โโThe "Tweezer Top" candlestick pattern is a bearish pattern consists of two candles.
โโParameters:
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
upsideTasukiGap(c2, c1, n)
โโThe "Tri Star" candlestick pattern is a bullish pattern consists of three candles.
โโParameters:
โโโโ c2 (simple bool) : (simple bool) Before Previous candle's body must be higher than average. Optional argument, default is true.
โโโโ c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
โโโโ n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
LibrarySupertrendLibrary "LibrarySupertrend"
selective_ma(condition, source, length)
โโParameters:
โโโโ condition (bool)
โโโโ source (float)
โโโโ length (int)
trendUp(source)
โโParameters:
โโโโ source (float)
smoothrng(source, sampling_period, range_mult)
โโParameters:
โโโโ source (float)
โโโโ sampling_period (simple int)
โโโโ range_mult (float)
rngfilt(source, smoothrng)
โโParameters:
โโโโ source (float)
โโโโ smoothrng (float)
fusion(overallLength, rsiLength, mfiLength, macdLength, cciLength, tsiLength, rviLength, atrLength, adxLength)
โโParameters:
โโโโ overallLength (simple int)
โโโโ rsiLength (simple int)
โโโโ mfiLength (simple int)
โโโโ macdLength (simple int)
โโโโ cciLength (simple int)
โโโโ tsiLength (simple int)
โโโโ rviLength (simple int)
โโโโ atrLength (simple int)
โโโโ adxLength (simple int)
zonestrength(amplitude, wavelength)
โโParameters:
โโโโ amplitude (int)
โโโโ wavelength (simple int)
atr_anysource(source, atr_length)
โโParameters:
โโโโ source (float)
โโโโ atr_length (simple int)
supertrend_anysource(source, factor, atr_length)
โโParameters:
โโโโ source (float)
โโโโ factor (float)
โโโโ atr_length (simple int)
TradingToolsLibraryLibrary "TradingToolsLibrary"
Easily create advanced entries, exits, filters and qualifiers to simulate strategies. Supports DCA (Dollar Cost Averaging) Lines, Stop Losses, Take Profits (with trailing or without) & ATR.
method deepCopy(this)
โโThis creates a deep copy instead of a shallow copy of an entry_position. This does NOT deep copy the self_pyramiding_positions array reference, since only the master entry_position needs this to track the rest of its copies for efficiency reasons. This is to prevent a feedback loop.
โโNamespace types: entry_position
โโParameters:
โโโโ this (entry_position)
โโReturns: entry_position
method precision_fix(this, precision)
โโConvert a floating point number to a precise floating point number with digit precision to avoid floating point errors in quantity calculations.
โโNamespace types: series float, simple float, input float, const float
โโParameters:
โโโโ this (float)
โโโโ precision (int)
โโReturns: float
xSellBuyMidInterpolation(_x, _high, _low, _sellRange, _buyRange)
โโCreates an interpolation for a sell range and buy range but with an emphasis on reaching the _low the closer to the middle of the _sell and _buy range you go.
โโParameters:
โโโโ _x (float) : is the value you want to use to control interpolation bewteen the _high and _low value. This will return the lowest percentage at the mid between high and low and highest percentage at the _high and _low.
โโโโ _high (float)
โโโโ _low (float)
โโโโ _sellRange (float)
โโโโ _buyRange (float)
โโReturns: an interpolated float between the _high and _low supplied.
xSellBuyInterpolation(_x, _high, _low, _sellRange, _buyRange)
โโCreates an interpolation a sell range and buy range
โโParameters:
โโโโ _x (float) : is the value you want to use to control interpolation bewteen the _high and _low value.
โโโโ _high (float)
โโโโ _low (float)
โโโโ _sellRange (float)
โโโโ _buyRange (float)
โโReturns: an interpolated float between the _high and _low supplied.
activate_entries_and_exits(_entries, _exits, _filters, _qualifiers, _equity)
โโDetermines activation for entries or exits. Does not place the actual orders.
โโParameters:
โโโโ _entries (entry_position )
โโโโ _exits (exit_position )
โโโโ _filters (filter )
โโโโ _qualifiers (qualifier )
โโโโ _equity (equity_management)
โโReturns: void
create_entries_and_exits(_entries, _exits, _equity)
โโCreates actual entry and exit orders if activated
โโParameters:
โโโโ _entries (entry_position )
โโโโ _exits (exit_position )
โโโโ _equity (equity_management)
โโReturns: void
filter
โโFields:
โโโโ disabled (series__bool)
โโโโ filter_for_entries_or_exits (series__string)
โโโโ filter_for_groups (series__string)
โโโโ condition (series__bool)
โโโโ dynamic_condition (series__bool)
โโโโ use_dynamic_condition (series__bool)
โโโโ use_override_default_condition (series__bool)
โโโโ dynamic_condition_operator (series__string)
โโโโ dynamic_condition_source (series__float)
โโโโ dynamic_compare_source (series__float)
โโโโ dynamic_condition_source_prior (series__float)
โโโโ dynamic_compare_source_prior (series__float)
โโโโ use_dynamic_compare_source (series__bool)
โโโโ dynamic_condition_activate_value (series__string)
โโโโ expire_condition_activate_value (series__string)
โโโโ expire_condition_source (series__float)
โโโโ expire_condition_source_prior (series__float)
โโโโ expire_compare_source (series__float)
โโโโ expire_compare_source_prior (series__float)
โโโโ use_expire_compare_source (series__bool)
โโโโ expire_condition_operator (series__string)
qualifier
โโFields:
โโโโ disabled (series__bool)
โโโโ qualify_for_entries_or_exits (series__string)
โโโโ qualify_for_groups (series__string)
โโโโ disqualify (series__bool)
โโโโ condition (series__bool)
โโโโ dynamic_condition (series__bool)
โโโโ use_dynamic_condition (series__bool)
โโโโ use_override_default_condition (series__bool)
โโโโ dynamic_condition_operator (series__string)
โโโโ dynamic_condition_source (series__float)
โโโโ dynamic_compare_source (series__float)
โโโโ dynamic_condition_source_prior (series__float)
โโโโ dynamic_compare_source_prior (series__float)
โโโโ use_dynamic_compare_source (series__bool)
โโโโ dynamic_condition_activate_value (series__string)
โโโโ expire_after_x_bars (series__integer)
โโโโ use_expire_after_x_bars (series__bool)
โโโโ use_expire_condition (series__bool)
โโโโ use_override_expire_condition (series__bool)
โโโโ expire_condition_operator (series__string)
โโโโ expire_condition_source (series__float)
โโโโ expire_compare_source (series__float)
โโโโ expire_condition_source_prior (series__float)
โโโโ expire_compare_source_prior (series__float)
โโโโ use_expire_compare_source (series__bool)
โโโโ expire_condition_activate_value (series__string)
โโโโ active (series__bool)
โโโโ expire_after_bars_bar_index (series__integer)
โโโโ expire_after_bars_bar_index_prior (series__integer)
โโโโ expire_bar_count (series__integer)
โโโโ expire_bar_changed (series__bool)
entry_position
โโFields:
โโโโ disabled (series__bool)
โโโโ activate (series__bool)
โโโโ active (series__bool)
โโโโ override_occured (series__bool)
โโโโ passDebug (array__bool)
โโโโ initial_activation_price (series__float)
โโโโ dca_done (series__bool)
โโโโ condition (series__bool)
โโโโ dynamic_condition (series__bool)
โโโโ use_dynamic_condition (series__bool)
โโโโ use_override_default_condition (series__bool)
โโโโ dynamic_condition_operator (series__string)
โโโโ dynamic_condition_source (series__float)
โโโโ dynamic_compare_source (series__float)
โโโโ dynamic_condition_source_prior (series__float)
โโโโ dynamic_compare_source_prior (series__float)
โโโโ use_dynamic_compare_source (series__bool)
โโโโ dynamic_condition_activate_value (series__string)
โโโโ use_cash (series__bool)
โโโโ use_percent_equity (series__bool)
โโโโ percent_equity_amount (series__float)
โโโโ cash_amount (series__float)
โโโโ position_size (series__float)
โโโโ total_position_size (series__float)
โโโโ prior_total_position_size (series__float)
โโโโ equity_remaining (series__float)
โโโโ prior_equity_remaining (series__float)
โโโโ initial_equity (series__float)
โโโโ use_martingale (series__bool)
โโโโ martingale_win_ratio (series__float)
โโโโ martingale_lose_ratio (series__float)
โโโโ martingale_win_limit (series__integer)
โโโโ martingale_lose_limit (series__integer)
โโโโ martingale_limit_reset_mode (series__string)
โโโโ use_dynamic_percent_equity (series__bool)
โโโโ dynamic_percent_equity_amount (series__float)
โโโโ initial_dynamic_percent_equity_amount (series__float)
โโโโ dynamic_percent_equity_source (series__float)
โโโโ dynamic_percent_equity_min (series__float)
โโโโ dynamic_percent_equity_max (series__float)
โโโโ dynamic_percent_equity_source_sell_range (series__float)
โโโโ dynamic_percent_equity_source_buy_range (series__float)
โโโโ dynamic_equity_interpolation_method (series__string)
โโโโ total_bars (series__integer)
โโโโ bar_index_at_activate (series__integer)
โโโโ bars_since_active (series__integer)
โโโโ time_at_activate (series__integer)
โโโโ time_since_active (series__integer)
โโโโ bar_index_at_activated (series__integer)
โโโโ bar_index_at_pyramid_change (series__integer)
โโโโ name (series__string)
โโโโ id (series__string)
โโโโ group (series__string)
โโโโ pyramiding_limit (series__integer)
โโโโ self_pyramiding_limit (series__integer)
โโโโ self_pyramiding_positions (array__|entry_position|#OBJ)
โโโโ new_pyramid_cancels_dca (series__bool)
โโโโ num_active_long_positions (series__integer)
โโโโ num_active_short_positions (series__integer)
โโโโ num_active_positions (series__integer)
โโโโ position_remaining (series__float)
โโโโ prior_position_remaining (series__float)
โโโโ direction (series__string)
โโโโ allow_flip_position (series__bool)
โโโโ flip_occurred (series__bool)
โโโโ ignore_flip (series__bool)
โโโโ use_dca (series__bool)
โโโโ dca_use_limit (series__bool)
โโโโ dca_num_positions (series__integer)
โโโโ dca_positions (array__float)
โโโโ dca_deviation_percentage (series__float)
โโโโ dca_scale (series__float)
โโโโ dca_percentages (series__string)
โโโโ dca_close_cancels (series__bool)
โโโโ dca_active_positions (series__integer)
โโโโ use_atr_deviation (series__bool)
โโโโ dca_atr_length (series__integer)
โโโโ dca_atr_mult (series__float)
โโโโ dca_atr_updates_dca_positions (series__bool)
โโโโ close_price_at_order (series__float)
โโโโ dca_use_deviation_atr_min (series__bool)
โโโโ dca_position_quantities (array__float)
โโโโ use_dca_dynamic_percent_equity (series__bool)
โโโโ dca_in_use (array__bool)
โโโโ dca_activated (array__bool)
โโโโ dca_money_used (array__float)
โโโโ dca_lines (array__line)
โโโโ dca_color (series__color)
โโโโ show_dca_lines (series__bool)
โโโโ atr_value (series__float)
โโโโ atr_value_at_activation (series__float)
โโโโ use_cooldown_bars (series__bool)
โโโโ cooldown_bars (series__integer)
โโโโ cooldown_bar_changed (series__bool)
โโโโ cooldown_bar_index (series__integer)
โโโโ cooldown_bar_index_prior (series__integer)
โโโโ cooldown_bar_change_count (series__integer)
โโโโ expire_condition_activate_value (series__string)
โโโโ expire_condition_source (series__float)
โโโโ expire_condition_source_prior (series__float)
โโโโ expire_compare_source (series__float)
โโโโ expire_compare_source_prior (series__float)
โโโโ use_expire_compare_source (series__bool)
โโโโ expire_condition_operator (series__string)
exit_position
โโFields:
โโโโ disabled (series__bool)
โโโโ id (series__string)
โโโโ group (series__string)
โโโโ exit_for_entries (series__string)
โโโโ exit_for_groups (series__string)
โโโโ total_bars (series__integer)
โโโโ name (series__string)
โโโโ condition (series__bool)
โโโโ dynamic_condition (series__bool)
โโโโ use_dynamic_condition (series__bool)
โโโโ use_override_default_condition (series__bool)
โโโโ dynamic_condition_operator (series__string)
โโโโ dynamic_condition_source (series__float)
โโโโ dynamic_compare_source (series__float)
โโโโ dynamic_condition_source_prior (series__float)
โโโโ dynamic_compare_source_prior (series__float)
โโโโ use_dynamic_compare_source (series__bool)
โโโโ dynamic_condition_activate_value (series__string)
โโโโ activate (series__bool)
โโโโ active (series__bool)
โโโโ reset_equity (series__bool)
โโโโ use_limit (series__bool)
โโโโ use_alerts (series__bool)
โโโโ reset_entry_cooldowns (series__bool)
โโโโ prevent_new_entries_on_partial_close (series__bool)
โโโโ show_activation_zone (series__bool)
โโโโ use_average_position (series__bool)
โโโโ source_value (series__float)
โโโโ trigger_x_times (series__integer)
โโโโ amount_of_times_triggered (series__integer)
โโโโ quantity_percent (series__float)
โโโโ trade_qty (series__float)
โโโโ exit_amount (series__float)
โโโโ entries_exiting_for (array__|entry_position|#OBJ)
โโโโ atr_value (series__float)
โโโโ update_atr (series__bool)
โโโโ use_activate_after_bars (series__bool)
โโโโ show_activate_after_bars (series__bool)
โโโโ activate_after_bars (series__integer)
โโโโ activate_after_bars_bar_changed (series__bool)
โโโโ activate_after_bars_bar_index (series__integer)
โโโโ activate_after_bars_bar_index_prior (series__integer)
โโโโ activate_after_bars_bar_change_count (series__integer)
โโโโ all_conditions_pass (series__bool)
โโโโ use_close_if_profit_only (series__bool)
โโโโ profit_value (series__float)
โโโโ exit_type (series__string)
โโโโ exit_modifier (series__string)
โโโโ update_atr_with_new_pyramid (series__bool)
โโโโ percentage (series__float)
โโโโ activation_percentage (series__float)
โโโโ atr_multiplier (series__float)
โโโโ use_cancel_if_percent (series__bool)
โโโโ cancel_if_percent (series__float)
โโโโ activation_value (series__float)
โโโโ activation_value_crossed (series__bool)
โโโโ exit_value (series__float)
โโโโ hypo_long_exit_value (series__float)
โโโโ hypo_short_exit_value (series__float)
โโโโ close_exit_value (series__float)
โโโโ debug (series__float)
โโโโ expire_condition_activate_value (series__string)
โโโโ expire_condition_source (series__float)
โโโโ expire_condition_source_prior (series__float)
โโโโ expire_compare_source (series__float)
โโโโ expire_compare_source_prior (series__float)
โโโโ use_expire_compare_source (series__bool)
โโโโ expire_condition_operator (series__string)
equity_management
โโFields:
โโโโ equity (series__float)
โโโโ prior_equity (series__float)
โโโโ position_used (series__float)
โโโโ prior_position_used (series__float)
โโโโ prevent_future_entries (series__bool)
โโโโ minimum_order_size (series__float)
โโโโ decimal_rounding_precision (series__integer)
โโโโ direction (series__string)
โโโโ show_order_info_in_comments (series__bool)
โโโโ show_order_info_in_labels (series__bool)
โโโโ allow_longs (series__bool)
โโโโ allow_shorts (series__bool)
โโโโ override_occured (series__bool)
โโโโ flip_occured (series__bool)
โโโโ num_concurrent_wins (series__integer)
โโโโ num_concurrent_losses (series__integer)
โโโโ first_entry (|entry_position|#OBJ)
โโโโ num_win_trades (series__integer)
โโโโ num_losing_trades (series__integer)
