Strategy█ OVERVIEW
This library is a Pine Script™ programmer’s tool containing a variety of strategy-related functions to assist in calculations like profit and loss, stop losses and limits. It also includes several useful functions one can use to convert between units in ticks, price, currency or a percentage of the position's size.
█ CONCEPTS
The library contains three types of functions:
1 — Functions beginning with `percent` take either a portion of a price, or the current position's entry price and convert it to the value outlined in the function's documentation.
Example: Converting a percent of the current position entry price to ticks, or calculating a percent profit at a given level for the position.
2 — Functions beginning with `tick` convert a tick value to another form.
These are useful for calculating a price or currency value from a specified number of ticks.
3 — Functions containing `Level` are used to calculate a stop or take profit level using an offset in ticks from the current entry price.
These functions can be used to plot stop or take profit levels on the chart, or as arguments to the `limit` and `stop` parameters in strategy.exit() function calls.
Note that these calculated levels flip automatically with the position's bias.
For example, using `ticksToStopLevel()` will calculate a stop level under the entry price for a long position, and above the entry price for a short position.
There are also two functions to assist in calculating a position size using the entry's stop and a fixed risk expressed as a percentage of the current account's equity. By varying the position size this way, you ensure that entries with different stop levels risk the same proportion of equity.
█ NOTES
Example code using some of the library's functions is included at the end of the library. To see it in action, copy the library's code to a new script in the Pine Editor, and “Add to chart”.
For each trade, the code displays:
• The entry level in orange.
• The stop level in fuchsia.
• The take profit level in green.
The stop and take profit levels automatically flip sides based on whether the current position is long or short.
Labels near the last trade's levels display the percentages used to calculate them, which can be changed in the script's inputs.
We plot markers for entries and exits because strategy code in libraries does not display the usual markers for them.
Look first. Then leap.
█ FUNCTIONS
percentToTicks(percent) Converts a percentage of the average entry price to ticks.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to ticks. 50 is 50% of the entry price.
Returns: (float) A value in ticks.
percentToPrice(percent) Converts a percentage of the average entry price to a price.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to price. 50 is 50% of the entry price.
Returns: (float) A value in the symbol's quote currency (USD for BTCUSD).
percentToCurrency(price, percent) Converts the percentage of a price to money.
Parameters:
price : (series int/float) The symbol's price.
percent : (series int/float) The percentage of `price` to calculate.
Returns: (float) A value in the symbol's currency.
percentProfit(exitPrice) Calculates the profit (as a percentage of the position's `strategy.position_avg_price` entry price) if the trade is closed at `exitPrice`.
Parameters:
exitPrice : (series int/float) The potential price to close the position.
Returns: (float) Percentage profit for the current position if closed at the `exitPrice`.
priceToTicks(price) Converts a price to ticks.
Parameters:
price : (series int/float) Price to convert to ticks.
Returns: (float) A quantity of ticks.
ticksToPrice(price) Converts ticks to a price offset from the average entry price.
Parameters:
price : (series int/float) Ticks to convert to a price.
Returns: (float) A price level that has a distance from the entry price equal to the specified number of ticks.
ticksToCurrency(ticks) Converts ticks to money.
Parameters:
ticks : (series int/float) Number of ticks.
Returns: (float) Money amount in the symbol's currency.
ticksToStopLevel(ticks) Calculates a stop loss level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `stop` parameter of a `strategy.exit()` call. NOTE: The stop level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the stop loss level.
Returns: (float) A stop loss level for the current position.
ticksToTpLevel(ticks) Calculates a take profit level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `limit` parameter of a `strategy.exit()` call. NOTE: The take profit level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the take profit level.
Returns: (float) A take profit level for the current position.
calcPositionSizeByStopLossTicks(stopLossTicks, riskPercent) Calculates the position size needed to implement a given stop loss (in ticks) corresponding to `riskPercent` of equity.
Parameters:
stopLossTicks : (series int) The stop loss (in ticks) that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
Returns: (int) A quantity of contracts.
calcPositionSizeByStopLossPercent(stopLossPercent, riskPercent, entryPrice) Calculates the position size needed to implement a given stop loss (%) corresponding to `riskPercent` of equity.
Parameters:
stopLossPercent : (series int/float) The stop loss in percent that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
entryPrice : (series int/float) The entry price of the position.
Returns: (int) A quantity of contracts.
exitPercent(id, lossPercent, profitPercent, qty, qtyPercent, comment, when, alertMessage) A wrapper of the `strategy.exit()` built-in which adds the possibility to specify loss & profit in as a value in percent. NOTE: this function may work incorrectly with pyramiding turned on due to the use of `strategy.position_avg_price` in its calculations of stop loss and take profit offsets.
Parameters:
id : (series string) The order identifier of the `strategy.exit()` call.
lossPercent : (series int/float) Stop loss as a percent of the entry price.
profitPercent : (series int/float) Take profit as a percent of the entry price.
qty : (series int/float) Number of contracts/shares/lots/units to exit a trade with. The default value is `na`.
qtyPercent : (series int/float) The percent of the position's size to exit a trade with. If `qty` is `na`, the default value of `qty_percent` is 100.
comment : (series string) Optional. Additional notes on the order.
when : (series bool) Condition of the order. The order is placed if it is true.
alertMessage : (series string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
Indikatoren und Strategien
adx: Configurable ADX (library) Library "adx"
Calculate ADX (and its constituent parts +DI, -DI, ATR),
using different moving averages and periods.
adx(atrMA, diMA, adxMA, atrLen, diLen, adxLen, h, l, c)
Parameters:
atrMA : Moving Average used for calculating the Average True Range.
Traditionally RMA, but using SMA here and in adxMA gives good results too.
diMA : Moving Average used for calculating the Directional Index.
Traditionally, RMA.
adxMA : Moving Average used for calculating the Average Directional
Index. Traditionally RMA, but using SMA here and in atrMA gives good results
too.
atrLen : Length of the Average True Range.
diLen : Length of the Directional Index.
adxLen : Length (smoothing) of the Average Directional Index.
h : Candle's high.
l : Candle's low.
c : Candle's close.
Returns:
ColorsLibrary "Colors"
This Library delivers Hex Codes of Colors frequently used in indicators and strategies.
v3(colorName) Collection: Pinescript v3 Colors.
Parameters:
colorName : Color Name.
Returns: Hex code of the inquired color.
v4(colorName) Collection: Pinescript v4 Colors.
Parameters:
colorName : Color Name.
Returns: Hex code of the inquired color.
lib_MilitzerLibrary "lib_Militzer"
// This is a collection of functions either found on the internet, or made by me.
// This is only public so my other scripts that reference this can also be public.
// But if you find anything useful here, be my guest.
print()
strToInt()
timeframeToMinutes()
FunctionCosineSimilarityLibrary "FunctionCosineSimilarity"
Cosine Similarity method.
function(sample_a, sample_b) Measure the similarity of 2 vectors.
Parameters:
sample_a : float array, values.
sample_b : float array, values.
Returns: float.
diss(cosim) Dissimilarity helper function.
Parameters:
cosim : float, cosine similarity value (0 > 1)
Returns: float
eHarmonicpatternsExtendedLibrary "eHarmonicpatternsExtended"
Library provides an alternative method to scan harmonic patterns. This is helpful in reducing iterations. Republishing as new library instead of existing eHarmonicpatterns because I need that copy for existing scripts.
scan_xab(bcdRatio, err_min, err_max, patternArray) Checks if bcd ratio is in range of any harmonic pattern
Parameters:
bcdRatio : AB/XA ratio
err_min : minimum error threshold
err_max : maximum error threshold
patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten.
scan_abc_axc(abcRatio, axcRatio, err_min, err_max, patternArray) Checks if abc or axc ratio is in range of any harmonic pattern
Parameters:
abcRatio : BC/AB ratio
axcRatio : XC/AX ratio
err_min : minimum error threshold
err_max : maximum error threshold
patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten.
scan_bcd(bcdRatio, err_min, err_max, patternArray) Checks if bcd ratio is in range of any harmonic pattern
Parameters:
bcdRatio : CD/BC ratio
err_min : minimum error threshold
err_max : maximum error threshold
patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten.
scan_xad_xcd(xadRatio, xcdRatio, err_min, err_max, patternArray) Checks if xad or xcd ratio is in range of any harmonic pattern
Parameters:
xadRatio : AD/XA ratio
xcdRatio : CD/XC ratio
err_min : minimum error threshold
err_max : maximum error threshold
patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten.
isHarmonicPattern(x, a, b, c, d, flags, errorPercent) Checks for harmonic patterns
Parameters:
x : X coordinate value
a : A coordinate value
b : B coordinate value
c : C coordinate value
d : D coordinate value
flags : flags to check patterns. Send empty array to enable all
errorPercent : Error threshold
Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names
isHarmonicProjection(x, a, b, c, flags, errorPercent) Checks for harmonic pattern projection
Parameters:
x : X coordinate value
a : A coordinate value
b : B coordinate value
c : C coordinate value
flags : flags to check patterns. Send empty array to enable all
errorPercent : Error threshold
Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names.
get_prz_range(x, a, b, c, patternArray, errorPercent, start_adj, end_adj) Provides PRZ range based on BCD and XAD ranges
Parameters:
x : X coordinate value
a : A coordinate value
b : B coordinate value
c : C coordinate value
patternArray : Pattern flags for which PRZ range needs to be calculated
errorPercent : Error threshold
start_adj : - Adjustments for entry levels
end_adj : - Adjustments for stop levels
Returns: Start and end of consolidated PRZ range
get_prz_range_xad(x, a, b, c, patternArray, errorPercent, start_adj, end_adj) Provides PRZ range based on XAD range only
Parameters:
x : X coordinate value
a : A coordinate value
b : B coordinate value
c : C coordinate value
patternArray : Pattern flags for which PRZ range needs to be calculated
errorPercent : Error threshold
start_adj : - Adjustments for entry levels
end_adj : - Adjustments for stop levels
Returns: Start and end of consolidated PRZ range
MathProbabilityDistributionLibrary "MathProbabilityDistribution"
Probability Distribution Functions.
name(idx) Indexed names helper function.
Parameters:
idx : int, position in the range (0, 6).
Returns: string, distribution name.
usage:
.name(1)
Notes:
(0) => 'StdNormal'
(1) => 'Normal'
(2) => 'Skew Normal'
(3) => 'Student T'
(4) => 'Skew Student T'
(5) => 'GED'
(6) => 'Skew GED'
zscore(position, mean, deviation) Z-score helper function for x calculation.
Parameters:
position : float, position.
mean : float, mean.
deviation : float, standard deviation.
Returns: float, z-score.
usage:
.zscore(1.5, 2.0, 1.0)
std_normal(position) Standard Normal Distribution.
Parameters:
position : float, position.
Returns: float, probability density.
usage:
.std_normal(0.6)
normal(position, mean, scale) Normal Distribution.
Parameters:
position : float, position in the distribution.
mean : float, mean of the distribution, default=0.0 for standard distribution.
scale : float, scale of the distribution, default=1.0 for standard distribution.
Returns: float, probability density.
usage:
.normal(0.6)
skew_normal(position, skew, mean, scale) Skew Normal Distribution.
Parameters:
position : float, position in the distribution.
skew : float, skewness of the distribution.
mean : float, mean of the distribution, default=0.0 for standard distribution.
scale : float, scale of the distribution, default=1.0 for standard distribution.
Returns: float, probability density.
usage:
.skew_normal(0.8, -2.0)
ged(position, shape, mean, scale) Generalized Error Distribution.
Parameters:
position : float, position.
shape : float, shape.
mean : float, mean, default=0.0 for standard distribution.
scale : float, scale, default=1.0 for standard distribution.
Returns: float, probability.
usage:
.ged(0.8, -2.0)
skew_ged(position, shape, skew, mean, scale) Skew Generalized Error Distribution.
Parameters:
position : float, position.
shape : float, shape.
skew : float, skew.
mean : float, mean, default=0.0 for standard distribution.
scale : float, scale, default=1.0 for standard distribution.
Returns: float, probability.
usage:
.skew_ged(0.8, 2.0, 1.0)
student_t(position, shape, mean, scale) Student-T Distribution.
Parameters:
position : float, position.
shape : float, shape.
mean : float, mean, default=0.0 for standard distribution.
scale : float, scale, default=1.0 for standard distribution.
Returns: float, probability.
usage:
.student_t(0.8, 2.0, 1.0)
skew_student_t(position, shape, skew, mean, scale) Skew Student-T Distribution.
Parameters:
position : float, position.
shape : float, shape.
skew : float, skew.
mean : float, mean, default=0.0 for standard distribution.
scale : float, scale, default=1.0 for standard distribution.
Returns: float, probability.
usage:
.skew_student_t(0.8, 2.0, 1.0)
select(distribution, position, mean, scale, shape, skew, log) Conditional Distribution.
Parameters:
distribution : string, distribution name.
position : float, position.
mean : float, mean, default=0.0 for standard distribution.
scale : float, scale, default=1.0 for standard distribution.
shape : float, shape.
skew : float, skew.
log : bool, if true apply log() to the result.
Returns: float, probability.
usage:
.select('StdNormal', __CYCLE4F__, log=true)
Adaptive_LengthLibrary "Adaptive_Length"
This library contains functions to calculate Adaptive dynamic length which can be used in Moving Averages and other indicators.
Two Exponential Moving Averages (EMA) are plotted. Coloring in plot is derived from Chikou filter and Dynamic length of MA1 is adapted using Signal output from Chikou library.
dynamic(para, adapt_Pct, minLength, maxLength) Adaptive dynamic length based on boolean parameter
Parameters:
para : Boolean parameter; if true then length would decrease and would increase if its false
adapt_Pct : Percentage adaption based on parameter
minLength : Minimum allowable length
maxLength : Maximum allowable length
Returns: Adaptive Dynamic Length based on Boolean Parameter
auto_alpha(src, a) Adaptive length based on automatic alpha calculations from source input
Parameters:
src : Price source for alpha calculations
a : Input Alpha value
Returns: Adaptive Length calculated from input price Source and Alpha
MovingAveragesLibrary "MovingAverages"
Contains utilities for generating moving average values including getting a moving average by name and a function for generating a Volume-Adjusted WMA.
sma(_D, _len) Simple Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
ema(_D, _len) Exponential Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
rma(_D, _len) RSI Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
wma(_D, _len) Weighted Moving Avereage
Parameters:
_D : The series to measure from.
_len : The number of bars to measure with.
vwma(_D, _len) volume-weighted Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
alma(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
cma(_D, _len, C, compound) Coefficient Moving Avereage (CMA) is a variation of a moving average that can simulate SMA or WMA with the advantage of previous data.
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
C : The coefficient to use when averaging. 0 behaves like SMA, 1 behaves like WMA.
compound : When true (default is false) will use a compounding method for weighting the average.
dema(_D, _len) Double Exponential Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
zlsma(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
zlema(_D, _len) Arnaud Legoux Moving Avereage
Parameters:
_D : The series to measure from. Default is 'close'.
_len : The number of bars to measure with.
get(type, len, src) Generates a moving average based upon a 'type'.
Parameters:
type : The type of moving average to generate. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
len : The number of bars to measure with.
src : The series to measure from. Default is 'close'.
Returns: The moving average series requested.
ChikouLibrary "Chikou"
This library contains Chikou Filter function to enhances functionality of Chikou-Span from Ichimoku Cloud using a simple trend filter.
Chikou is basically close value of ticker offset to close and it is a good for indicating if close value has crossed potential Support/Resistance zone from past. Chikou is usually used with 26 period.
Chikou filter uses a lookback length calculated from provided lookback percentage and checks if trend was bullish or bearish within that lookback period.
Bullish : Trend is bullish if Chikou span is above high values of all candles within defined lookback period. Bull color shows bullish trend .
Bearish : Trend is bearish if Chikou span is below low values of all candles within defined lookback period. This is indicated by Bearish color.
Reversal / Choppiness : Reversal color indicates that Chikou are swinging around candles within defined lookback period which is an indication of consolidation or trend reversal.
chikou(src, len, perc, _high, _low, bull_col, bear_col, r_col) Chikou Filter for Ichimoku Cloud with Color and Signal Output
Parameters:
src : Price Source (better to use (OHLC4+high+low/3 instead of default close value)
len : Chikou Legth (displaced source value)
perc : Percentage lookback period for Chikou Filter with defined how much candels of total length should be considered for backward filteration
_high : Ticker High Value
_low : Ticker Low Value
bull_col : Color to be returned if source value is greater than all candels within provided lookback percentage.
bear_col : Color to be returned if source value is lower than all candels within provided lookback percentage.
r_col : Color to be returned if source value is swinging around candles within defined lookback period which is an indication of consolidation or trend reversal.
Returns: Color based on trend. 'bull_col' if trend is bullish, 'bear_col' if trend is bearish. 'r_col' if no prominent trend. Integer Signal is also returned as 1 for Bullish, -1 for Bearish and 0 for no prominent trend.
HA_CandlesLibrary "HA_Candles"
Heikin Ashi Candles
HA_Close() Heikin Ashi Modified Close
Returns: Heikin Ashi Modified Close
HA_Open() Heikin Ashi Modified Open
Returns: Heikin Ashi Modified Open
HA_High() Heikin Ashi Modified High
Returns: Heikin Ashi Modified High
HA_Low() Heikin Ashi Modified Low
Returns: Heikin Ashi Modified Low
HA_Delta(Heikin) Heikin Ashi Delta
Parameters:
Heikin : Ashi Close, Heikin Ashi Open
Returns: Heikin Ashi Delta
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()
jsonLibrary "json"
Convert JSON strings to tradingview
▦ FEATURES ▦
█ Json to array █ Get json key names █ Get json key values █ Size of json
get_json_keys_names(raw_json) Returns string array with all key names
Parameters:
raw_json : (string) Raw JSON string
Returns: (string array) Array with all key names
get_values_by_id_name(raw_json, key_name) Returns string array with values of the input key name
Parameters:
raw_json : (string) Raw JSON string
key_name : (string) Name of the key to be fetched
Returns: (string array) Array with values of the input key name
size_of_json_string(raw_json) Returns size of raw JSON string
Parameters:
raw_json : (string) Raw JSON string
Returns: Size of n_of_values, size of n_of_keys_names
timeUtilsLibrary "timeUtils"
Utils for time series
tradingDaysTillEndOfMonth() Calculates how many full trading days left until the end of the current month. (It doesn't take into account market holidays)
Returns: int series of the remaining trading days until the end of the month.
insideRange()
utilsLibrary "utils"
ma_smooth(alg, src, len) Calculates various moving averages
Parameters:
alg : Smoothing algorithm to use
src : Source data
len : Length of moving average
RVSILibrary "RVSI"
This Library contains functions that calculate all types of " Relative Volume Strength Index (MZ RVSI ) " depending upon unique volume oscillator. Achieved RVSI value can be used for divergence detection in volume or to adapt dynamic length in Moving Averages or other functions.
rvsi_tfs(vol_src, vol_Len, rvsiLen, _open, _close) Relative Volume Strength Index based on TFS Volume Oscillator
Parameters:
vol_src : Volume Source
vol_Len : Volume Legth for TFS Volume Oscillato
rvsiLen : Period of Relative Volume Strength Index
_open : Ticker Open Value
_close : Ticker Close Value
Returns: Relative Volume Strength Index value based on TFS Volume Oscillator
rvsi_obv(vol_src, rvsiLen, _close) Relative Volume Strength Index based on On Balance Volume
Parameters:
vol_src : Volume Source to Calculate On Balance Volume
rvsiLen : Period of Relative Volume Strength Index
_close : Ticker Close Value
Returns: Relative Volume Strength Index value based on On Balance Volume
rvsi_kvo(vol_src, FastX, SlowX, rvsiLen, _close) Relative Volume Strength Index based on Klinger Volume Oscillator
Parameters:
vol_src : Volume Source
FastX : Volume Fast Length
SlowX : Volume Slow Length
rvsiLen : Period of Relative Volume Strength Index
_close : Ticker Close Value
Returns: Relative Volume Strength Index value based on Klinger Volume Oscillator
rvsi_vzo(vol_src, zLen, rvsiLen, _close) Relative Volume Strength Index based on Volume Zone Oscillator
Parameters:
vol_src : Volume Source
zLen : Volume Legth for Volume Zone Oscillator
rvsiLen : Period of Relative Volume Strength Index
_close : Ticker Close Value
Returns: Relative Volume Strength Index value based on Volume Zone Oscillator
rvsi_cvo_obv(vol_src, ema1len, ema2len, rvsiLen) Relative Volume Strength Index based on Cumulative Volume Oscillator with On Balance Volume as Calculations Source
Parameters:
vol_src : Volume Source
ema1len : EMA Fast Length
ema2len : EMA Slow Length
rvsiLen : Period of Relative Volume Strength Index
Returns: Relative Volume Strength Index value based on Cumulative Volume Oscillator with On Balance Volume as Calculations Source
rvsi_cvo_pvt(vol_src, FastX, SlowX, rvsiLen) Relative Volume Strength Index based on Cumulative Volume Oscillator with Price Volume Trend as Calculations Source
Parameters:
vol_src : Volume Source
FastX : EMA Fast Length
SlowX : EMA Slow Length
rvsiLen : Period of Relative Volume Strength Index
Returns: Relative Volume Strength Index value based on Cumulative Volume Oscillator with Price Volume Trend as Calculations Source
rvsi_cvo_cvd(vol_src, FastX, SlowX, rvsiLen, _open, _close, _high, _low) Relative Volume Strength Index based on Cumulative Volume Oscillator with Cumulative Volume Delta as Calculations Source
Parameters:
vol_src : Volume Source
FastX : EMA Fast Length
SlowX : EMA Slow Length
rvsiLen : Period of Relative Volume Strength Index
_open : Ticker Open Value
_close : Ticker Close Value
_high : Ticker High Value
_low : Ticker Low Value
Returns: Relative Volume Strength Index value based on Cumulative Volume Oscillator with Cumulative Volume Delta as Calculations Source
eStrategyLibrary "eStrategy"
Library contains methods which can help build custom strategy for continuous investment plans and also compare it with systematic buy and hold.
sip(startYear, initialDeposit, depositFrequency, recurringDeposit, buyPrice) Depicts systematic buy and hold over period of time
Parameters:
startYear : Year on which SIP is started
initialDeposit : Initial one time investment at the start
depositFrequency : Frequency of recurring deposit - can be monthly or weekly
recurringDeposit : Recurring deposit amount
buyPrice : Indicatinve buy price. Use high to be conservative. low, close, open, hl2, hlc3, ohlc4, hlcc4 are other options.
Returns: totalInvestment - initial + recurring deposits
totalQty - Quantity of units held for given instrument
totalEquity - Present equity
customStrategy(startYear, initialDeposit, depositFrequency, recurringDeposit, buyPrice, sellPrice, initialInvestmentPercent, recurringInvestmentPercent, signal, tradePercent) Allows users to define custom strategy and enhance systematic buy and hold by adding take profit and reloads
Parameters:
startYear : Year on which SIP is started
initialDeposit : Initial one time investment at the start
depositFrequency : Frequency of recurring deposit - can be monthly or weekly
recurringDeposit : Recurring deposit amount
buyPrice : Indicatinve buy price. Use high to be conservative. low, close, open, hl2, hlc3, ohlc4, hlcc4 are other options.
sellPrice : Indicatinve sell price. Use low to be conservative. high, close, open, hl2, hlc3, ohlc4, hlcc4 are other options.
initialInvestmentPercent : percent of amount to invest from the initial depost. Keep rest of them as cash
recurringInvestmentPercent : percent of amount to invest from recurring deposit. Keep rest of them as cash
signal : can be 1, -1 or 0. 1 means buy/reload. -1 means take profit and 0 means neither.
tradePercent : percent of amount to trade when signal is not 0. If taking profit, it will sell the percent from existing position. If reloading, it will buy with percent from cash reserve
Returns: totalInvestment - initial + recurring deposits
totalQty - Quantity of units held for given instrument
totalCash = Amount of cash held
totalEquity - Overall equity = totalQty*close + totalCash
JohnEhlersFourierTransformLibrary "JohnEhlersFourierTransform"
Fourier Transform for Traders By John Ehlers, slightly modified to allow to inspect other than the 8-50 frequency spectrum.
reference:
www.mesasoftware.com
high_pass_filter(source) Detrended version of the data by High Pass Filtering with a 40 Period cutoff
Parameters:
source : float, data source.
Returns: float.
transformed_dft(source, start_frequency, end_frequency) DFT by John Elhers.
Parameters:
source : float, data source.
start_frequency : int, lower bound of the frequency window, must be a positive number >= 0, window must be less than or 30.
end_frequency : int, upper bound of the frequency window, must be a positive number >= 0, window must be less than or 30.
Returns: tuple with float, float array.
db_to_rgb(db, transparency) converts the frequency decibels to rgb.
Parameters:
db : float, decibels value.
transparency : float, transparency value.
Returns: color.
windowing_taAll Signals Are the Sum of Sines. When looking at real-world signals, you usually view them as a price changing over time. This is referred to as the time domain. Fourier’s theorem states that any waveform in the time domain can be represented by the weighted sum of sines and cosines. For example, take two sine waves, where one is three times as fast as the other–or the frequency is 1/3 the first signal. When you add them, you can see you get a different signal.
Although performing an FFT on a signal can provide great insight, it is important to know the limitations of the FFT and how to improve the signal clarity using windowing. When you use the FFT to measure the frequency component of a signal, you are basing the analysis on a finite set of data. The actual FFT transform assumes that it is a finite data set, a continuous spectrum that is one period of a periodic signal. For the FFT, both the time domain and the frequency domain are circular topologies, so the two endpoints of the time waveform are interpreted as though they were connected together. When the measured signal is periodic and an integer number of periods fill the acquisition time interval, the FFT turns out fine as it matches this assumption. However, many times, the measured signal isn’t an integer number of periods. Therefore, the finiteness of the measured signal may result in a truncated waveform with different characteristics from the original continuous-time signal, and the finiteness can introduce sharp transition changes into the measured signal. The sharp transitions are discontinuities.
When the number of periods in the acquisition is not an integer, the endpoints are discontinuous. These artificial discontinuities show up in the FFT as high-frequency components not present in the original signal. These frequencies can be much higher than the Nyquist frequency and are aliased between 0 and half of your sampling rate. The spectrum you get by using a FFT, therefore, is not the actual spectrum of the original signal, but a smeared version. It appears as if energy at one frequency leaks into other frequencies. This phenomenon is known as spectral leakage, which causes the fine spectral lines to spread into wider signals.
You can minimize the effects of performing an FFT over a noninteger number of cycles by using a technique called windowing. Windowing reduces the amplitude of the discontinuities at the boundaries of each finite sequence acquired by the digitizer. Windowing consists of multiplying the time record by a finite-length window with an amplitude that varies smoothly and gradually toward zero at the edges. This makes the endpoints of the waveform meet and, therefore, results in a continuous waveform without sharp transitions. This technique is also referred to as applying a window.
Here is a windowing_ta library with J.F Ehlers Windowing functions proposed on Sep, 2021.
Library "windowing_ta"
hann()
hamm()
fir_sma()
fir_triangle()
harmonicpatterns1Library "harmonicpatterns1"
harmonicpatterns: methods required for calculation of harmonic patterns. Correction for library (missing export in line 303)
isGartleyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isGartleyPattern: Checks for harmonic pattern Gartley
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Gartley. False otherwise.
isBatPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isBatPattern: Checks for harmonic pattern Bat
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Bat. False otherwise.
isButterflyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isButterflyPattern: Checks for harmonic pattern Butterfly
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Butterfly. False otherwise.
isCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isCrabPattern: Checks for harmonic pattern Crab
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Crab. False otherwise.
isDeepCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isDeepCrabPattern: Checks for harmonic pattern DeepCrab
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is DeepCrab. False otherwise.
isCypherPattern(xabRatio, axcRatio, xadRatio, err_min, err_max) isCypherPattern: Checks for harmonic pattern Cypher
Parameters:
xabRatio : AB/XA
axcRatio : XC/AX
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Cypher. False otherwise.
isSharkPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isSharkPattern: Checks for harmonic pattern Shark
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Shark. False otherwise.
isNenStarPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isNenStarPattern: Checks for harmonic pattern Nenstar
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Nenstar. False otherwise.
isAntiNenStarPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiNenStarPattern: Checks for harmonic pattern Anti NenStar
Parameters:
xabRatio : - AB/XA
abcRatio : - BC/AB
bcdRatio : - CD/BC
xadRatio : - AD/XA
err_min : - Minumum error threshold
err_max : - Maximum error threshold
Returns: True if the pattern is Anti NenStar. False otherwise.
isAntiSharkPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiSharkPattern: Checks for harmonic pattern Anti Shark
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Shark. False otherwise.
isAntiCypherPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiCypherPattern: Checks for harmonic pattern Anti Cypher
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Cypher. False otherwise.
isAntiCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiCrabPattern: Checks for harmonic pattern Anti Crab
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Crab. False otherwise.
isAntiButterflyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiButterflyPattern: Checks for harmonic pattern Anti Butterfly
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Butterfly. False otherwise.
isAntiBatPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiBatPattern: Checks for harmonic pattern Anti Bat
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Bat. False otherwise.
isAntiGartleyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiGartleyPattern: Checks for harmonic pattern Anti Gartley
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Anti Gartley. False otherwise.
isNavarro200Pattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isNavarro200Pattern: Checks for harmonic pattern Navarro200
Parameters:
xabRatio : AB/XA
abcRatio : BC/AB
bcdRatio : CD/BC
xadRatio : AD/XA
err_min : Minumum error threshold
err_max : Maximum error threshold
Returns: True if the pattern is Navarro200. False otherwise.
isHarmonicPattern(x, a, c, c, d, flags, errorPercent) isHarmonicPattern: Checks for harmonic patterns
Parameters:
x : X coordinate value
a : A coordinate value
c : B coordinate value
c : C coordinate value
d : D coordinate value
flags : flags to check patterns. Send empty array to enable all
errorPercent : Error threshold
Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names
TS_FFALibrary "TS_FFA"
Splits the ticker and generates best configs for FP and PP
splitter(x) Splits the ticker and found the configuration regarding to name.
Parameters:
_x: ticker
Returns: Fib and Profit percent values
- Splitter had been added.
- USDTPERP coins on Binance had been added
- timeFrameMultiplier() timeframe multiplier had been added to the library
- timeframe period value fixed
- Changed timezone multiplier
- Changed VWMA Percent values
bytimeLibrary "bytime"
TODO: to do something at the specified time.
////Return =>> ht = hour , mt = minute , st = second ,Dt = Day, Mt = month, Yt = year , dateTime = full time format./////////////
Note : Remember to always add import when you call our library and change Gtime() to Timeset.Gtime() is used to access internal data.
import hapharmonic/bytime/1 as Timeset
=Timeset.Gtime()
/////////////Set a time to trigger an alert./////////////
ck = false
///hour : minute : second
if ht == TH and mt == TM and st == TS
//some action
//...
//.
ck := true
Gtime()
[e2] Drawing Library :: Horizontal Ray█ OVERVIEW
Library "e2hray"
A drawing library that contains the hray() function, which draws a horizontal ray/s with an initial point determined by a specified condition. It plots a ray until it reached the price. The function let you control the visibility of historical levels and setup the alerts.
█ HORIZONTAL RAY FUNCTION
hray(condition, level, color, extend, hist_lines, alert_message, alert_delay, style, hist_style, width, hist_width)
Parameters:
condition : Boolean condition that defines the initial point of a ray
level : Ray price level.
color : Ray color.
extend : (optional) Default value true, current ray levels extend to the right, if false - up to the current bar.
hist_lines : (optional) Default value true, shows historical ray levels that were revisited, default is dashed lines. To avoid alert problems set to 'false' before creating alerts.
alert_message : (optional) Default value string(na), if declared, enables alerts that fire when price revisits a line, using the text specified
alert_delay : (optional) Default value int(0), number of bars to validate the level. Alerts won't trigger if the ray is broken during the 'delay'.
style : (optional) Default value 'line.style_solid'. Ray line style.
hist_style : (optional) Default value 'line.style_dashed'. Historical ray line style.
width : (optional) Default value int(1), ray width in pixels.
hist_width : (optional) Default value int(1), historical ray width in pixels.
Returns: void
█ EXAMPLES
• Example 1. Single horizontal ray from the dynamic input.
//@version=5
indicator("hray() example :: Dynamic input ray", overlay = true)
import e2e4mfck/e2hray/1 as e2draw
inputTime = input.time(timestamp("20 Jul 2021 00:00 +0300"), "Date", confirm = true)
inputPrice = input.price(54, 'Price Level', confirm = true)
e2draw.hray(time == inputTime, inputPrice, color.blue, alert_message = 'Ray level re-test!')
var label mark = label.new(inputTime, inputPrice, 'Selected point to start the ray', xloc.bar_time)
• Example 2. Multiple horizontal rays on the moving averages cross.
//@version=5
indicator("hray() example :: MA Cross", overlay = true)
import e2e4mfck/e2hray/1 as e2draw
float sma1 = ta.sma(close, 20)
float sma2 = ta.sma(close, 50)
bullishCross = ta.crossover( sma1, sma2)
bearishCross = ta.crossunder(sma1, sma2)
plot(sma1, 'sma1', color.purple)
plot(sma2, 'sma2', color.blue)
// 1a. We can use 2 function calls to distinguish long and short sides.
e2draw.hray(bullishCross, sma1, color.green, alert_message = 'Bullish Cross Level Broken!', alert_delay = 10)
e2draw.hray(bearishCross, sma2, color.red, alert_message = 'Bearish Cross Level Broken!', alert_delay = 10)
// 1b. Or a single call for both.
// e2draw.hray(bullishCross or bearishCross, sma1, bullishCross ? color.green : color.red)
• Example 3. Horizontal ray at the all time highs with an alert.
//@version=5
indicator("hray() example :: ATH", overlay = true)
import e2e4mfck/e2hray/1 as e2draw
var float ath = 0, ath := math.max(high, ath)
bool newAth = ta.change(ath)
e2draw.hray(nz(newAth ), high , color.orange, alert_message = 'All Time Highs Tested!', alert_delay = 10)
TAExtLibrary "TAExt"
Indicator functions can be used in other indicators and strategies. This will be extended by time with indicators I use in my strategies and studies.
atrwo(length, stdev_length, stdev_mult) ATR without outliers
Parameters:
length : The length of the ATR
stdev_length : The length of the standard deviation, used for detecting outliers
stdev_mult : The multiplier of the standard deviation, used for detecting outliers
Returns: The ATR value
atrwma(src, period, type, atr_length, stdev_length, stdev_mult) ATR without outlier weighted moving average
Parameters:
src : The source of the moving average
period : The period of the moving average
type : The type of the moving average, possible values: SMA, EMA, RMA
atr_length : The length of the ATR
stdev_length : The length of the standard deviation, used for detecting outliers
stdev_mult : The multiplier of the standard deviation, used for detecting outliers
Returns: The moving average value
jma(src, period, phase, power) Jurik Moving Average
Parameters:
src : The source of the moving average
period : The period of the moving average calculation
phase : The phase of jurik MA calculation (-100..100)
power : The power of jurik MA calculation
Returns: The Jurik MA series
anyma(src, period, type, offset, sigma, phase, power) Moving Average by type
Parameters:
src : The source of the moving average
period : The period of the moving average calculation
type : The type of the moving average
offset : Used only by ALMA, it is the ALMA offset
sigma : Used only by ALMA, it is the ALMA sigma
phase : The phase of jurik MA calculation (-100..100)
power : The power of jurik MA calculation
Returns: The moving average series
wae(macd_src, macd_fast_length, macd_slow_length, macd_sensitivity, bb_base_src, bb_upper_src, bb_lower_src, bb_length, bb_mult, dead_zone_length, dead_zone_mult) Waddah Attar Explosion (WAE)
Parameters:
macd_src : The source series used by MACD
macd_fast_length : The fast MA length of the MACD
macd_slow_length : The slow MA length of the MACD
macd_sensitivity : The MACD diff multiplier
bb_base_src : The source used by stdev
bb_upper_src : The source used by the upper Bollinger Band
bb_lower_src : The source used by the lower Bollinger Band
bb_length : The lenth for Bollinger Bands
bb_mult : The multiplier for Bollinger Bands
dead_zone_length : The ATR length for dead zone calculation
dead_zone_mult : The ATR multiplier for dead zone
Returns:
ssl(length, high_src, low_src) Semaphore Signal Level channel (SSL)
Parameters:
length : The length of the moving average
high_src : Source of the high moving average
low_src : Source of the low moving average
Returns:
adx(atr_length, di_length, adx_length, high_src, low_src, atr_ma_type, di_ma_type, adx_ma_type) Average Directional Index + Direction Movement Index (ADX + DMI)
Parameters:
atr_length : The length of ATR
di_length : DI plus and minus smoothing length
adx_length : ADX smoothing length
high_src : Source of the high moving average
low_src : Source of the low moving average
atr_ma_type : MA type of the ATR calculation
di_ma_type : MA type of the DI calculation
adx_ma_type : MA type of the ADX calculation
Returns:
