MyMovingAveragesLibraryLibrary "MyMovingAveragesLibrary"
alma(src, lkbk, alma_offset, alma_sigma)
ALMA - Arnaud Legoux Moving Average
Parameters:
src (float) : float
lkbk (int) : int
alma_offset (simple float)
alma_sigma (simple float) : float
Returns: moving average
frama(src, lkbk, FC, SC)
FRAMA - Fractal Adaptive Moving Average
Parameters:
src (float) : float
lkbk (int) : int
FC (int) : int
SC (int) : int
Returns: moving average
kama(src, lkbk, kamafastend, kamaslowend)
KAMA - Kaufman Adaptive Moving Average
Parameters:
src (float) : float
lkbk (int) : int
kamafastend (int) : int
kamaslowend (int) : int
Returns: moving average
ema(src, lkbk)
EMA - Exponential Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
dema(src, lkbk)
DEMA - Double Exponential Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
tema(src, lkbk)
TEMA - Triple Exponential Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
hma(src, lkbk)
HMA - Hull Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
jma(src, lkbk, jurik_power, jurik_phase)
JMA - Jurik Moving Average
Parameters:
src (float) : float
lkbk (int) : int
jurik_power (int)
jurik_phase (float)
Returns: moving average
laguerre(src, alpha)
Laguerre Filter
Parameters:
src (float) : float
alpha (float) : float
Returns: moving average
lsma(src, lkbk, lsma_offset)
LSMA - Least Squares Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
lsma_offset (simple int) : int
Returns: moving average
mcginley(src, lkbk)
McGinley Dynamic
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
mf(src, lkbk, mf_feedback, mf_beta, mf_z)
Modular Filter
Parameters:
src (float) : float
lkbk (int) : int
mf_feedback (bool) : float
mf_beta (float) : boolean
mf_z (float) : float
Returns: moving average
rdma(src)
RDMA - RexDog Moving Average (RDA, as he calls it)
Parameters:
src (float) : flot
Returns: moving average
sma(src, lkbk)
SMA - Simple Moving Average
Parameters:
src (float) : float
lkbk (int) : int
Returns: moving average
smma(src, lkbk)
SMMA - Smoothed Moving Average (known as RMA in TradingView)
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
t3(src, lkbk)
T3 Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
tma(src, lkbk)
TMA - Triangular Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
vama(src, lkbk, vol_lkbk)
VAMA - Volatility-Adjusted Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
vol_lkbk (int) : int
vwma(src, lkbk)
VWMA - Volume-Weighted Moving Average
Parameters:
src (float) : float
lkbk (simple int) : int
Returns: moving average
mf_zlagma(src, lkbk)
Zero-Lag Moving Average
Parameters:
src (float) : float
lkbk (int) : int
Returns: moving average
Techindicator
Absolute ZigZag LibLibrary "Absolute_ZigZag_Lib"
This ZigZag Library is a Bit different. Instead of using percentages or looking more than 1 bar left or right, this Zigzag library calculates pivots by just looking at the current bar highs and lows and the ones of one bar earlier.
This is the most accurate way of calculating pivots and it also eliminates lag.
The library also features a solution for bars that have both a higher high and a higher low like seen below.
You can also use your own colors for the labels and the lines.
You can also quickly select a one-colored theme without changing all colors at once
method isHigherHigh(this)
Checks if current pivot is a higher high
Namespace types: Pivot
Parameters:
this (Pivot) : (Pivot) The object to work with.
@return (bool) True if the pivot is a higher high, false if not.
method isLowerHigh(this)
Checks if current pivot is a lower high
Namespace types: Pivot
Parameters:
this (Pivot) : (Pivot) The object to work with.
@return (bool) True if the pivot is a lower high, false if not.
method isHigherLow(this)
Checks if current pivot is a higher low
Namespace types: Pivot
Parameters:
this (Pivot) : (Pivot) The object to work with.
@return (bool) True if the pivot is a higher low, false if not.
method isLowerLow(this)
Checks if current pivot is a lower low
Namespace types: Pivot
Parameters:
this (Pivot) : (Pivot) The object to work with.
@return (bool) True if the pivot is a lower low, false if not.
method getLastPivotHigh(this)
Gets the last Pivot High
Namespace types: Pivot
Parameters:
this (Pivot ) : (array) The object to work with.
@return (Pivot) The latest Pivot High
method getLastPivotLow(this)
Gets the last Pivot Low
Namespace types: Pivot
Parameters:
this (Pivot ) : (array) The object to work with.
@return (Pivot) The latest Pivot Low
method prev(this, index)
Namespace types: Pivot
Parameters:
this (Pivot )
index (int)
method last(this, throwError)
Namespace types: Pivot
Parameters:
this (Pivot )
throwError (bool)
new(highFirst, theme)
Parameters:
highFirst (bool)
theme (Theme)
getLowerTimeframePeriod()
Theme
Used to create a (color) theme to draw Zigzag
Fields:
colorDefault (series color)
colorNeutral (series color)
colorBullish (series color)
colorBearish (series color)
coloredLines (series bool)
Point
Used to determine a coordination on the chart
Fields:
x (series int)
y (series float)
Pivot
Used to determine pivots on the chart
Fields:
point (Point)
isHigh (series bool)
isHigher (series bool)
ln (series line)
lb (series label)
GeneratorBetaLib:Generator
This library generate levels that could be used inside SNG scripts and strategies. Also uses beta version of SNG Types library
IndicatorsLibrary "Indicators"
this has a calculation for the most used indicators.
macd4C(fastMa, slowMa)
this calculates macd 4c
Parameters:
fastMa (simple int) : is the period for the fast ma. the minimum value is 7
slowMa (simple int) : is the period for the slow ma. the minimum value is 7
Returns: the macd 4c value for the current bar
rsi(rsiSourceInput, rsiLengthInput)
this calculates rsi
Parameters:
rsiSourceInput (float) : is the source for the rsi
rsiLengthInput (simple int) : is the period for the rsi
Returns: the rsi value for the current bar
ao(source, fastPeriod, slowPeriod)
this calculates ao
Parameters:
source (float) : is the source for the ao
fastPeriod (int) : is the period for the fast ma
slowPeriod (int) : is the period for the slow ma
Returns: the ao value for the current bar
kernelAoOscillator(kernelFastLookback, kernelSlowLookback, kernelFastWeight, kernelSlowWeight, kernelFastRegressionStart, kernelSlowRegressionStart, kernelFastSmoothPeriod, kernelSlowSmoothPeriod, kernelFastSmooth, kernelSlowSmooth, source)
this calculates our own kernel ao oscillator which we made
Parameters:
kernelFastLookback (simple int)
kernelSlowLookback (simple int)
kernelFastWeight (simple float)
kernelSlowWeight (simple float)
kernelFastRegressionStart (simple int)
kernelSlowRegressionStart (simple int)
kernelFastSmoothPeriod (int)
kernelSlowSmoothPeriod (int)
kernelFastSmooth (bool)
kernelSlowSmooth (bool)
source (float) : is the source for the ao
Returns: the kernel ao oscillator value for the current bar, the colors for both the fast and slow kernel, the fast & slow kernel
signalLineKernel(lag, h, r, x_0, smoothColors, _src, c_bullish, c_bearish)
Parameters:
lag (int)
h (float)
r (float)
x_0 (int)
smoothColors (bool)
_src (float)
c_bullish (color)
c_bearish (color)
zigzagCalc(Depth, Deviation, Backstep, repaint, Show_zz, line_thick, text_color)
Parameters:
Depth (int)
Deviation (int)
Backstep (int)
repaint (bool)
Show_zz (bool)
line_thick (int)
text_color (color)
RelativeValue█ OVERVIEW
This library is a Pine Script™ programmer's tool offering the ability to compute relative values, which represent comparisons of current data points, such as volume, price, or custom indicators, with their analogous historical data points from corresponding time offsets. This approach can provide insightful perspectives into the intricate dynamics of relative market behavior over time.
█ CONCEPTS
Relative values
In this library, a relative value is a metric that compares a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
For instance, suppose we wanted to calculate relative volume on an hourly chart over five daily periods, and the last chart bar is two hours into the current trading day. In this case, we would compare the current volume to the average of volume in the second hour of trading across five days. We obtain the relative volume value by dividing the current volume by this average.
This form of analysis rests on the hypothesis that substantial discrepancies or aberrations in present market activity relative to historical time intervals might help indicate upcoming changes in market trends.
Cumulative and non-cumulative values
In the context of this library, a cumulative value refers to the cumulative sum of a series since the last occurrence of a specific condition (referred to as `anchor` in the function definitions). Given that relative values depend on time, we use time-based conditions such as the onset of a new hour, day, etc. On the other hand, a non-cumulative value is simply the series value at a specific time without accumulation.
Calculating relative values
Four main functions coordinate together to compute the relative values: `maintainArray()`, `calcAverageByTime()`, `calcCumulativeSeries()`, and `averageAtTime()`. These functions are underpinned by a `collectedData` user-defined type (UDT), which stores data collected since the last reset of the timeframe along with their corresponding timestamps. The relative values are calculated using the following procedure:
1. The `averageAtTime()` function invokes the process leveraging all four of the methods and acts as the main driver of the calculations. For each bar, this function adds the current bar's source and corresponding time value to a `collectedData` object.
2. Within the `averageAtTime()` function, the `maintainArray()` function is called at the start of each anchor period. It adds a new `collectedData` object to the array and ensures the array size does not exceed the predefined `maxSize` by removing the oldest element when necessary. This method plays an essential role in limiting memory usage and ensuring only relevant data over the desired number of periods is in the calculation window.
3. Next, the `calcAverageByTime()` function calculates the average value of elements within the `data` field for each `collectedData` object that corresponds to the same time offset from each anchor condition. This method accounts for cases where the current index of a `collectedData` object exceeds the last index of any past objects by using the last available values instead.
4. For cumulative calculations, the `averageAtTime()` function utilizes the `isCumulative` boolean parameter. If true, the `calcCumulativeSeries()` function will track the running total of the source data from the last bar where the anchor condition was met, providing a cumulative sum of the source values from one anchor point to the next.
To summarize, the `averageAtTime()` function continually stores values with their corresponding times in a `collectedData` object for each bar in the anchor period. When the anchor resets, this object is added to a larger array. The array's size is limited by the specified number of periods to be averaged. To correlate data across these periods, time indexing is employed, enabling the function to compare corresponding points across multiple periods.
█ USING THIS LIBRARY
The library simplifies the complex process of calculating relative values through its intuitive functions. Follow the steps below to use this library in your scripts.
Step 1: Import the library and declare inputs
Import the library and declare variables based on the user's input. These can include the timeframe for each period, the number of time intervals to include in the average, and whether the calculation uses cumulative values. For example:
//@version=5
import TradingView/RelativeValue/1 as TVrv
indicator("Relative Range Demo")
string resetTimeInput = input.timeframe("D")
int lengthInput = input.int(5, "No. of periods")
Step 2: Define the anchor condition
With these inputs declared, create a condition to define the start of a new period (anchor). For this, we use the change in the time value from the input timeframe:
bool anchor = timeframe.change(resetTimeInput)
Step 3: Calculate the average
At this point, one can calculate the average of a value's history at the time offset from the anchor over a number of periods using the `averageAtTime()` function. In this example, we use True Range (TR) as the `source` and set `isCumulative` to false:
float pastRange = TVrv.averageAtTime(ta.tr, lengthInput, anchor, false)
Step 4: Display the data
You can visualize the results by plotting the returned series. These lines display the non-cumulative TR alongside the average value over `lengthInput` periods for relative comparison:
plot(pastRange, "Past True Range Avg", color.new(chart.bg_color, 70), 1, plot.style_columns)
plot(ta.tr, "True Range", close >= open ? color.new(color.teal, 50) : color.new(color.red, 50), 1, plot.style_columns)
This example will display two overlapping series of columns. The green and red columns depict the current TR on each bar, and the light gray columns show the average over a defined number of periods, e.g., the default inputs on an hourly chart will show the average value at the hour over the past five days. This comparative analysis aids in determining whether the range of a bar aligns with its typical historical values or if it's an outlier.
█ NOTES
• The foundational concept of this library was derived from our initial Relative Volume at Time script. This library's logic significantly boosts its performance. Keep an eye out for a forthcoming updated version of the indicator. The demonstration code included in the library emulates a streamlined version of the indicator utilizing the library functions.
• Key efficiencies in the data management are realized through array.binary_search_leftmost() , which offers a performance improvement in comparison to its loop-dependent counterpart.
• This library's architecture utilizes user-defined types (UDTs) to create custom objects which are the equivalent of variables containing multiple parts, each able to hold independent values of different types . The recently added feature was announced in this blog post.
• To enhance readability, the code substitutes array functions with equivalent methods .
Look first. Then leap.
█ FUNCTIONS
This library contains the following functions:
calcCumulativeSeries(source, anchor)
Calculates the cumulative sum of `source` since the last bar where `anchor` was `true`.
Parameters:
source (series float) : Source used for the calculation.
anchor (series bool) : The condition that triggers the reset of the calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
Returns: (float) The cumulative sum of `source`.
averageAtTime(source, length, anchor, isCumulative)
Calculates the average of all `source` values that share the same time difference from the `anchor` as the current bar for the most recent `length` bars.
Parameters:
source (series float) : Source used for the calculation.
length (simple int) : The number of reset periods to consider for the average calculation of historical data.
anchor (series bool) : The condition that triggers the reset of the average calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
isCumulative (simple bool) : If `true`, `source` values are accumulated until the next time `anchor` is `true`. Optional. The default is `true`.
Returns: (float) The average of the source series at the specified time difference.
AoDivergenceLibrary_Library "AoDivergenceLibrary_"
this has functions which calculate and plot divergences which are used for ao divergences. essentially, this finds divergences by using the ao divergence logic. this logic has been used in "AO Hid & Reg Div with LC & Kernel".
regBullDivergence(swingLow, osc, colour)
Parameters:
swingLow (bool)
osc (float)
colour (color)
regBearDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
hidBullDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
hidBearDivergence(swingHigh, osc, colour)
Parameters:
swingHigh (bool)
osc (float)
colour (color)
HelperTALibrary "HelperTA"
This library contains useful technical indicators that I use regularly in my charts.
`stockRSI` is not mine, but included because used often and referenced by internal functions.
`DCO` is a normalisation of the donchian channels; the price relative to the donchian channels, on a range.
`MarketCycle` is a weighted aggregate of RSI, Stochastic RSI & DCO (demo on the chart)
stockRSI(src, K, D, rsiPeriod, stochPeriod)
stockRSI
Parameters:
src (float)
K (int)
D (int)
rsiPeriod (simple int)
stochPeriod (int)
Returns:
DCO(price, donchianPeriod, smaPeriod)
DCO
Parameters:
price (float)
donchianPeriod (int)
smaPeriod (int)
Returns:
MarketCycle(donchianPrice, rsiPrice, srsiPrice, donchianPeriod, donchianSmoothing, rsiPeriod, rsiSmoothing, srsiPeriod, srsiSmoothing, srsiK, srsiD, rsiWeight, srsiWeight, dcoWeight)
MarketCycle
Parameters:
donchianPrice (float)
rsiPrice (float)
srsiPrice (float)
donchianPeriod (simple int)
donchianSmoothing (simple int)
rsiPeriod (simple int)
rsiSmoothing (int)
srsiPeriod (simple int)
srsiSmoothing (simple int)
srsiK (simple int)
srsiD (simple int)
rsiWeight (simple float)
srsiWeight (simple float)
dcoWeight (simple float)
Returns:
CurrentlyPositionIndicatorLibrary "CurrentlyPositionIndicator"
Currently position indicator
run(_index, _price, _stoploss, _high, _low, _side, _is_entered, _colors, _position_left, _box_width)
Currently positions indicator
Parameters:
_index (int) : entry index
_price (float) : entry price
_stoploss (float) : stoploss price
_high (float) : range high
_low (float) : range low
_side (int)
_is_entered (bool) : is entered
_colors (color ) : color array
_position_left (int) : Left position
_box_width (int) : box's width
Returns: TODO: add what function returns
BankNifty_CSMLibrary "BankNifty_CSM"
TODO: add library description here
getLtp_N_Chang(openPrice, closePrice, highPrice, hl2Price, lowPrice, hlc3Price, bankNiftyClose)
Parameters:
openPrice (float)
closePrice (float)
highPrice (float)
hl2Price (float)
lowPrice (float)
hlc3Price (float)
bankNiftyClose (float)
ka66: lib/MovingAveragesLibrary "MovingAverages"
Exotic or Interesting Moving Averages Collection. Just the one right now!
alphaConfigurableEma(src, alpha, nSmooth)
Calculates a variation of the EMA by specifying a custom alpha value.
Parameters:
src (float) : a float series to get the EMA for, e.g. close, hlc3, etc.
alpha (float) : a value between 0 (ideally greater, to get any MA!) and 1. Closer
to one makes it more responsive, and choppier.
nSmooth (int) : Just applies the same alpha and EMA to the last Alpha-EMA output.
A value between 0 and 10 (just keeping a a reasonable bound). The idea is
you can first use a reasonably high alpha, then smooth it out. Default 0,
no further smoothing.
Returns: MA series.
bands(src, multiplier)
Calculates fixed bands around a series, can be any series, though the intent
here is for MA series.
Parameters:
src (float) : a float series.
multiplier (float) : a value greater than or equal to 0 (ideally greater, to get any MA!),
determines the width of the bands. Start with small float values, or it may go
beyond the scale, e.g. 0.005.
Returns: a 2-tuple of (upBand, downBand)
Spider_PlotIntroduction:
Spider charts, also known as radar charts or web charts, are a powerful data visualization tool that can display multiple variables in a circular format. They are particularly useful when you want to compare different data sets or evaluate the performance of a single data set across multiple dimensions. In this blog post, we will dive into the world of spider charts, explore their benefits, and demonstrate how you can create your own spider chart using the Spider_Plot library.
Why Spider Charts are Cool:
Spider charts have a unique visual appeal that sets them apart from other chart types. They allow you to display complex data in a compact, easy-to-understand format, making them perfect for situations where you need to convey a lot of information in a limited space. Some of the key benefits of spider charts include:
Multi-dimensional analysis: Spider charts can display multiple variables at once, making them ideal for analyzing relationships between different data sets or examining a single data set across multiple dimensions.
Easy comparison: By displaying data in a circular format, spider charts make it simple to compare different data points, identify trends, and spot potential issues.
Versatility: Spider charts can be used for a wide range of applications, from business and finance to sports and health. They are particularly useful for situations where you need to analyze performance or make comparisons between different entities.
Creating Your Own Spider Chart with the Spider_Plot Library:
The Spider_Plot library is a user-friendly, easy-to-use tool that allows you to create stunning spider charts with minimal effort. To get started, you'll need to import the Spider_Plot library:
import peacefulLizard50262/Spider_Plot/1
With the library imported, you can now create your own spider chart. The first step is to normalize your data. Normalizing ensures that all data points fall within the 0 to 1 range, which is important for creating a visually balanced spider chart.
The Spider_Plot library provides the data_normalize function to help you normalize your data. This function accepts several parameters, including the normalization style ("All Time", "Range", or "Custom"), length of the range, outlier level, lookback period for standard deviation, and minimum and maximum values for the "Custom" normalization style.
Once you have normalized your data, you can create an array of your data points using the array.from function. This array will be used as input for the draw_spider_plot function, which is responsible for drawing the spider plot on your chart.
The draw_spider_plot function accepts an array of float values (the normalized data points), an array of background colors for each sector, a color for the axes, and a scaling factor.
Example Usage:
Here's an example script that demonstrates how to create a spider chart using the Spider_Plot library:
oc = data_normalize(ta.ema(math.abs(open - close), 20), "Range", 20)
// Create an array of your data points
data = array.from(tr, rsi, stoch, dev, tr, oc, tr)
// Define colors for each sector
colors = array.from(color.new(color.red, 90), color.new(color.blue, 90), color.new(color.green, 90), color.new(color.orange, 90), color.new(color.purple, 90), color.new(color.purple, 90), color.new(color.purple, 90))
// Draw the spider plot on your chart
draw_spider_plot(data, colors, color.gray, 100)
In this example, we have first normalized six different data points (rsi, source, stoch, dev, tr, and oc) using the data_normalize function. Next, we create an array of these normalized data points and define an array of colors for each sector of the spider chart. Finally, we call the draw_spider_plot function to draw the spider chart on our chart.
Conclusion:
Spider charts are a versatile and visually appealing tool for analyzing and comparing multi-dimensional data. With the Spider_Plot library, you can easily create your own spider charts and unlock valuable insights from your data. Just remember to normalize your data and create an array of data points before calling the draw_spider_plot function. Happy charting!
Library "Spider_Plot"
data_normalize(data, style, length, outlier_level, dev_lookback, min, max)
data_normalize(data, string style, int length, float outlier_level, simple int dev_lookback, float min, float max)
Parameters:
data (float) : float , A float value to normalize.
style (string) : string , The normalization style: "All Time", "Range", or "Custom".
length (int) : int , The length of the range for "Range" normalization style.
outlier_level (float) : float , The outlier level to exclude from calculations.
dev_lookback (simple int) : int , The lookback period for calculating the standard deviation.
min (float) : float , The minimum value for the "Custom" normalization style.
max (float) : float , The maximum value for the "Custom" normalization style.
Returns: array , The normalized float value.
draw_spider_plot(values, bg_colors, axes_color, scale)
draw_spider_plot(array values, array bg_colors, color axes_color, float scale)
Parameters:
values (float ) : array , An array of float values to plot in the spider plot.
bg_colors (color ) : array , An array of background colors for each sector in the spider plot.
axes_color (color) : color , The color of the axes in the spider plot. Default: color.gray
scale (float) : float , A scaling factor for the spider plot. Default: 10
Returns: void , Draws the spider plot on the chart.
ReversalChartPatternLibraryLibrary "ReversalChartPatternLibrary"
User Defined Types and Methods for reversal chart patterns - Double Top, Double Bottom, Triple Top, Triple Bottom, Cup and Handle, Inverted Cup and Handle, Head and Shoulders, Inverse Head and Shoulders
method delete(this)
Deletes the drawing components of ReversalChartPatternDrawing object
Namespace types: ReversalChartPatternDrawing
Parameters:
this (ReversalChartPatternDrawing) : ReversalChartPatternDrawing object
Returns: current ReversalChartPatternDrawing object
method delete(this)
Deletes the drawing components of ReversalChartPattern object. In turn calls the delete of ReversalChartPatternDrawing
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern) : ReversalChartPattern object
Returns: current ReversalChartPattern object
method lpush(this, obj, limit, deleteOld)
Array push with limited number of items in the array. Old items are deleted when new one comes and exceeds the limit
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern ) : array object
obj (ReversalChartPattern) : ReversalChartPattern object which need to be pushed to the array
limit (int) : max items on the array. Default is 10
deleteOld (bool) : If set to true, also deletes the drawing objects. If not, the drawing objects are kept but the pattern object is removed from array. Default is false.
Returns: current ReversalChartPattern object
method draw(this)
Draws the components of ReversalChartPatternDrawing
Namespace types: ReversalChartPatternDrawing
Parameters:
this (ReversalChartPatternDrawing) : ReversalChartPatternDrawing object
Returns: current ReversalChartPatternDrawing object
method draw(this)
Draws the components of ReversalChartPatternDrawing within the ReversalChartPattern object.
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern) : ReversalChartPattern object
Returns: current ReversalChartPattern object
method scan(zigzag, patterns, errorPercent, shoulderStart, shoulderEnd)
Scans zigzag for ReversalChartPattern occurences
Namespace types: zg.Zigzag
Parameters:
zigzag (Zigzag type from HeWhoMustNotBeNamed/ZigzagTypes/2) : ZigzagTypes.Zigzag object having array of zigzag pivots and other information on each pivots
patterns (ReversalChartPattern ) : Existing patterns array. Used for validating duplicates
errorPercent (float) : Error threshold for considering ratios. Default is 13
shoulderStart (float) : Starting range of shoulder ratio. Used for identifying shoulders, handles and necklines
shoulderEnd (float) : Ending range of shoulder ratio. Used for identifying shoulders, handles and necklines
Returns: int pattern type
method createPattern(zigzag, patternType, patternColor, riskAdjustment)
Create Pattern from ZigzagTypes.Zigzag object
Namespace types: zg.Zigzag
Parameters:
zigzag (Zigzag type from HeWhoMustNotBeNamed/ZigzagTypes/2) : ZigzagTypes.Zigzag object having array of zigzag pivots and other information on each pivots
patternType (int) : Type of pattern being created. 1 - Double Tap, 2 - Triple Tap, 3 - Cup and Handle, 4 - Head and Shoulders
patternColor (color) : Color in which the patterns are drawn
riskAdjustment (float) : Used for calculating stops
Returns: ReversalChartPattern object created
method getName(this)
get pattern name of ReversalChartPattern object
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern) : ReversalChartPattern object
Returns: string name of the pattern
method getDescription(this)
get consolidated description of ReversalChartPattern object
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern) : ReversalChartPattern object
Returns: string consolidated description
method init(this)
initializes the ReversalChartPattern object and creates sub object types
Namespace types: ReversalChartPattern
Parameters:
this (ReversalChartPattern) : ReversalChartPattern object
Returns: ReversalChartPattern current object
ReversalChartPatternDrawing
Type which holds the drawing objects for Reversal Chart Pattern Types
Fields:
patternLines (Line type from HeWhoMustNotBeNamed/DrawingTypes/1) : array of Line objects representing pattern
entry (Line type from HeWhoMustNotBeNamed/DrawingTypes/1) : Entry price Line
target (Line type from HeWhoMustNotBeNamed/DrawingTypes/1) : Target price Line
patternLabel (Label type from HeWhoMustNotBeNamed/DrawingTypes/1)
ReversalChartPattern
Reversal Chart Pattern master type which holds the pattern components, drawings and trade details
Fields:
pivots (Pivot type from HeWhoMustNotBeNamed/ZigzagTypes/2) : Array of Zigzag Pivots forming the pattern
patternType (series int) : Defines the main type of pattern 1 - Double Tap, 1 - Triple Tap, 3 - Cup and Handle, 4 - Head and Shoulders
patternColor (series color) : Color in which the pattern will be drawn on chart
riskAdjustment (series float) : Percentage adjustment of risk. Used for setting stops
drawing (ReversalChartPatternDrawing) : ReversalChartPatternDrawing object which holds the drawing components
trade (Trade type from HeWhoMustNotBeNamed/TradeTracker/1) : TradeTracker.Trade object holding trade components
TradeTrackerLibrary "TradeTracker"
Simple Library for tracking trades
method track(this)
tracks trade when called on every bar
Namespace types: Trade
Parameters:
this (Trade) : Trade object
Returns: current Trade object
Trade
Has the constituents to track trades generated by any method.
Fields:
id (series int)
direction (series int) : Trade direction. Positive values for long and negative values for short trades
initialEntry (series float) : Initial entry price. This value will not change even if the entry is changed in the lifecycle of the trade
entry (series float) : Updated entry price. Allows variations to initial calculated entry. Useful in cases of trailing entry.
initialStop (series float) : Initial stop. Similar to initial entry, this is the first calculated stop for the lifecycle of trade.
stop (series float) : Trailing Stop. If there is no trailing, the value will be same as that of initial trade
targets (float ) : array of target values.
startBar (series int) : bar index of starting bar. Set by default when object is created. No need to alter this after that.
endBar (series int) : bar index of last bar in trade. Set by tracker on each execution
startTime (series int) : time of the start bar. Set by default when object is created. No need to alter this after that.
endTime (series int) : time of the ending bar. Updated by tracking method.
status (series int) : Integer parameter to track the status of the trade
retest (series bool) : Boolean parameter to notify if there was retest of the entry price
peacefulIndicatorsWe are delighted to present the PeacefulIndicators library, a modest yet powerful collection of custom technical indicators created to enhance your trading analysis. The library features an array of practical tools, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
The PeacefulIndicators library offers the following functions:
macdDynamicLength: An adaptive version of the classic MACD indicator, which adjusts the lengths of the moving averages based on the dominant cycle period, providing a more responsive signal.
rsiDivergence: A unique implementation of RSI Divergence detection that identifies potential bullish and bearish divergences using a combination of RSI and linear regression.
trendReversalDetection: A helpful tool for detecting trend reversals using the Rate of Change (ROC) and Moving Averages, offering valuable insights into possible market shifts.
volume_flow_oscillator: A custom oscillator that combines price movement strength and volume to provide a unique perspective on market dynamics.
weighted_volatility_oscillator: Another custom oscillator that factors in price volatility and volume to deliver a comprehensive view of market fluctuations.
rvo: The Relative Volume Oscillator highlights changes in volume relative to historical averages, helping to identify potential breakouts or reversals.
acb: The Adaptive Channel Breakout indicator combines a moving average with an adjustable volatility multiplier to create dynamic channels, useful for identifying potential trend shifts.
We hope this library proves to be a valuable addition to your trading toolbox.
Library "peacefulIndicators"
A custom library of technical indicators for trading analysis, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
macdDynamicLength(src, shortLen, longLen, signalLen, dynLow, dynHigh)
Moving Average Convergence Divergence with Dynamic Length
Parameters:
src (float) : Series to use
shortLen (int) : Shorter moving average length
longLen (int) : Longer moving average length
signalLen (int) : Signal line length
dynLow (int) : Lower bound for the dynamic length
dynHigh (int) : Upper bound for the dynamic length
Returns: tuple of MACD line and Signal line
Computes MACD using lengths adapted based on the dominant cycle period
rsiDivergence(src, rsiLen, divThreshold, linRegLength)
RSI Divergence Detection
Parameters:
src (float) : Series to use
rsiLen (simple int) : Length for RSI calculation
divThreshold (float) : Divergence threshold for RSI
linRegLength (int) : Length for linear regression calculation
Returns: tuple of RSI Divergence (positive, negative)
Computes RSI Divergence detection that identifies bullish (positive) and bearish (negative) divergences
trendReversalDetection(src, rocLength, maLength, maType)
Trend Reversal Detection (TRD)
Parameters:
src (float) : Series to use
rocLength (int) : Length for Rate of Change calculation
maLength (int) : Length for Moving Average calculation
maType (string) : Type of Moving Average to use (default: "sma")
Returns: A tuple containing trend reversal direction and the reversal point
Detects trend reversals using the Rate of Change (ROC) and Moving Averages.
volume_flow_oscillator(src, length)
Volume Flow Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price movement strength and volume
weighted_volatility_oscillator(src, length)
Weighted Volatility Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price volatility and volume
rvo(length)
Relative Volume Oscillator
Parameters:
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on relative volume
acb(price_series, ma_length, vol_length, multiplier)
Adaptive Channel Breakout
Parameters:
price_series (float) : Price series to use
ma_length (int) : Period for the moving average calculation
vol_length (int) : Period for the volatility calculation
multiplier (float) : Multiplier for the volatility
Returns: Tuple containing the ACB upper and lower values and the trend direction (1 for uptrend, -1 for downtrend)
UtilityLibrary "Utility"
dema(src, length)
Parameters:
src (float)
length (simple int)
tema(src, length)
Parameters:
src (float)
length (simple int)
hma(src, length)
Parameters:
src (float)
length (int)
zlema(src, length)
Parameters:
src (float)
length (simple int)
stochRSI(src, lengthRSI, lengthStoch, smoothK, smoothD)
Parameters:
src (float)
lengthRSI (simple int)
lengthStoch (int)
smoothK (int)
smoothD (int)
slope(src, length)
Parameters:
src (float)
length (int)
RsiLibLibrary "RsiLib"
TODO: add library description here
bullishDivergence(rsi, check_backward_length, rsi_threshold, rsi_overload_threshold, power_threshhold)
Parameters:
rsi (float)
check_backward_length (int)
rsi_threshold (float)
rsi_overload_threshold (float)
power_threshhold (int)
peterzorve-libraryLibrary "library"
is_bullish_engulfing()
is_bearish_engulfing()
is_hammer(fib_level)
Parameters:
fib_level (float)
is_shooting_star(fib_level)
Parameters:
fib_level (float)
is_hammer_and_star(fib_level)
Parameters:
fib_level (float)
is_star_and_hammer(fib_level)
Parameters:
fib_level (float)
is_dogi(dogi_body_ratio)
Parameters:
dogi_body_ratio (float)
is_bear_bear_bullish_engulf()
is_atr_stoploss_takeprofit(atr_multiplier, atr_length, reward_ratio)
Parameters:
atr_multiplier (float)
atr_length (simple int)
reward_ratio (float)
is_fixed_stoploss_takeprofit(stoploss_pips, reward_ratio)
Parameters:
stoploss_pips (float)
reward_ratio (float)
is_step_trailing_stoploss(stoploss_pips)
Parameters:
stoploss_pips (float)
is_atr_trailing_stoploss(atr_multiplier, break_even_pip)
Parameters:
atr_multiplier (float)
break_even_pip (int)
is_pull_back_strategy(length)
Parameters:
length (simple int)
is_trade_statistics(condition, entrypoint, stoploss, takeprofit)
Parameters:
condition (bool)
entrypoint (float)
stoploss (float)
takeprofit (float)
is_table_of_statistics(win_trades, lost_trades, even_trades, pips_won, pips_lost)
Parameters:
win_trades (int)
lost_trades (int)
even_trades (int)
pips_won (float)
pips_lost (float)
is_pine_info(lotsize, stoploss, takeprofit)
Parameters:
lotsize (float)
stoploss (float)
takeprofit (float)
is_support_and_resistance_strategy(look_back, look_forward)
Parameters:
look_back (int)
look_forward (int)
is_choral_strategy(smoothing_period, constant_d)
Parameters:
smoothing_period (int)
constant_d (float)
is_bollinger_band_strategy(length, dev_entry, dev_stoploss, dev_takeprofit)
Parameters:
length (int)
dev_entry (simple float)
dev_stoploss (simple float)
dev_takeprofit (simple float)
VolumeLibLibrary "VolumeLib"
Contains types and methods related to VOLUME
volumePrice()
TODO: add function description here
Returns: TODO: add what function returns
averageVolumePrice(length)
Parameters:
length (simple int)
volumePower(volume_price, average_volume_price)
Parameters:
volume_price (float)
average_volume_price (float)
volumePower(length)
Parameters:
length (simple int)
AdxLibLibrary "AdxLib"
TODO: add library description here
create(di_length, adx_length)
Parameters:
di_length (simple int)
adx_length (simple int)
create(adx_length)
Parameters:
adx_length (simple int)
LibreLibrary "Libre"
TODO: add library description here
MMMM(toe)
Parameters:
toe (string)
OOOO(toe, toe1, toe2, toe3, toe4, toe5, init)
Parameters:
toe (string)
toe1 (string)
toe2 (string)
toe3 (string)
toe4 (string)
toe5 (string)
init (int)
XXXX(toe)
Parameters:
toe (string)
WWWW(toe)
Parameters:
toe (string)
OHLC📕 LIBRARY OHLC
🔷 Introduction
This library is a custom library designed to work with real-time bars. It allows to easily calculate OHLC values for any source.
Personally, I use this library to accurately display the highest and lowest values on visual indicators such as my progress bars.
🔷 How to Use
◼ 1. Import the OHLC library into your TradingView script:
import cryptolinx/OHLC/1
- or -
Instead of the library namespace, you can define a custom namespace as alias.
import cryptolinx/OHLC/1 as src
◼ 2. Create a new OHLC source using the `new()` function.
varip mySrc = OHLC.new() // It is required to use the `varip` keyword to init your ``
- or -
If you has set up an alias before.
varip mySrc = src.new()
===
In that case, your `` needs to be `na`, define your object like that
varip mySrc = na
◼ 3. Call the `hydrateOHLC()` method on your OHLC source to update its values:
Basic
float rsi = ta.rsi(close, 14)
mySrc.hydrateOHLC(rsi)
- or -
Inline
rsi = ta.rsi(close, 14).hydrateOHLC(mySrc)
◼ 4. The data is accessible under their corresponding names.
mySrc.open
mySrc.high
mySrc.low
mySrc.close
🔷 Note: This library only works with real-time bars and will not work with historical bars.
Lex_3CR_Functions_Library2Library "Lex_3CR_Functions_Library2"
This is a source code for a technical analysis library in Pine Script language,
designed to identify and mark Bullish and Bearish Three Candle Reversal (3CR) chart patterns.
The library provides three functions to be used in a trading algorithm.
The first function, Bull_3crMarker, adds a dashed line and label to a Bullish 3CR chart pattern, indicating the 3CR point.
The second function, Bear_3crMarker, adds a dashed line and label to a Bearish 3CR chart pattern.
The third function, Bull_3CRlogicals, checks for a Bullish 3CR pattern where the first candle's low is greater than the second candle's low and the second candle's low is less than the third candle's low.
If found, creates a line at the breakout point and a label at the fail point,
if specified. All functions take parameters such as the chart pattern's characteristics and output colors, labels, and markers.
Bull_3crMarker(bulllinearray, barnum, breakpoint, failpointB, failpoint, linecolorbull, bulllabelarray, labelcolor, textcolor, labelon)
Bull_3crMarker Adds a 3CR marker to a Bullish 3CR chart pattern
@description Adds a dashed line and label to a 3CR up chart pattern, indicating the 3CR (3 Candle Reversal) point.
Parameters:
bulllinearray (line )
barnum (int)
breakpoint (float)
failpointB (float )
failpoint (float)
linecolorbull (color)
bulllabelarray (label )
labelcolor (color)
textcolor (color)
labelon (bool)
Bear_3crMarker(bearlinearray, barnum, breakpoint, failpointB, failpoint, linecolorbear, bearlabelarray, labelcolor, textcolor, labelon)
Bear_3crMarker Adds a 3CR marker to a Bearish 3CR chart pattern
@description Adds a dashed line and label to a 3CR down chart pattern, indicating the 3CR (3 Candle Reversal) point.
Parameters:
bearlinearray (line )
barnum (int)
breakpoint (float)
failpointB (float )
failpoint (float)
linecolorbear (color)
bearlabelarray (label )
labelcolor (color)
textcolor (color)
labelon (bool)
Bull_3CRlogicals(low1, low2, low3, bulllinearray, bulllabelarray, failpointB, linecolorbull, labelcolor, textcolor, labelon)
Checks for a bullish three candle reversal pattern and creates a line and label at the breakout point if found
@description Checks for a bullish three candle reversal pattern where the first candle's low is greater than the second candle's low and the second candle's low is less than the third candle's low. If found, creates a line at the breakout point and a label at the fail point, if specified.
Parameters:
low1 (float)
low2 (float)
low3 (float)
bulllinearray (line )
bulllabelarray (label )
failpointB (float )
linecolorbull (color)
labelcolor (color)
textcolor (color)
labelon (bool)
Bear_3CRlogicals(high1, high2, high3, bearlinearray, bearlabelarray, failpointB, linecolorbear, labelcolor, textcolor, labelon)
Checks for a Bearish 3CR pattern and draws a bearish marker on the chart at the appropriate location
@description This function checks for a Bearish 3CR (Three-Candle Reversal) pattern, which is defined as the second candle having a higher high than the first and third candles, and the third candle having a lower high than the first candle. If the pattern is detected, a bearish marker is drawn on the chart at the appropriate location, and an optional label can be added to the marker.
Parameters:
high1 (float)
high2 (float)
high3 (float)
bearlinearray (line )
bearlabelarray (label )
failpointB (float )
linecolorbear (color)
labelcolor (color)
textcolor (color)
labelon (bool)
bullLineDelete(i, bulllinearray, failarray, bulllabelarray, labelon)
Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bulllinearray (line )
failarray (float )
bulllabelarray (label )
labelon (bool)
bearLineDelete(i, bearlinearray, failarray, bearlabelarray, labelon)
Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bearlinearray (line )
failarray (float )
bearlabelarray (label )
labelon (bool)
bulloffsetdelete(i, bulllinearray, failarray, bulllabelarray, labelon)
Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bulllinearray (line )
failarray (float )
bulllabelarray (label )
labelon (bool)
bearoffsetdelete(i, bearlinearray, failarray, bearlabelarray, labelon)
Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bearlinearray (line )
failarray (float )
bearlabelarray (label )
labelon (bool)
BullEntry_setter(i, bulllinearray, failpointB, entrystopB, entryB, entryboolB)
Checks if the specified value is greater than the break point of any bullish line in an array, and removes that line if true
@description Checks if the s pecified value is greater than the break point of any bullish line in an array, and removes that line if true.
Parameters:
i (int)
bulllinearray (line )
failpointB (float )
entrystopB (float )
entryB (float )
entryboolB (bool )
Bull3CRchecker(close1, bulllinearray, FailpointB, rsiB, bulllabelarray, labelt, bullcolored, directionarray, rsi, secondbullline, entrystopB, entryB, entryboolB)
Parameters:
close1 (float)
bulllinearray (line )
FailpointB (float )
rsiB (float )
bulllabelarray (label )
labelt (bool)
bullcolored (color)
directionarray (label )
rsi (float)
secondbullline (line )
entrystopB (float )
entryB (float )
entryboolB (bool )
Bear3CRchecker(close1, bearlinearray, FailpointB, bearlabelarray, labelt, bearcolored, directionarray, rsi, secondbearline, rsiB)
Checks if the specified value is less than the break point of any bearish line in an array, and removes that line if true
@description Checks if the specified value is less than the break point of any bearish line in an array, and removes that line if true.
Parameters:
close1 (float)
bearlinearray (line )
FailpointB (float )
bearlabelarray (label )
labelt (bool)
bearcolored (color)
directionarray (label )
rsi (float)
secondbearline (line )
rsiB (float )
Bulloffsetcheck(FailpointB, bulllabelarray, linearray, labelt, offset)
Checks the offset of bullish lines and deletes them if they are beyond a certain offset from the current bar index
@description Checks the offset of bullish lines and deletes them if they are beyond a certain offset from the current bar index
Parameters:
FailpointB (float )
bulllabelarray (label )
linearray (line )
labelt (bool)
offset (int)
Bearoffsetcheck(FailpointB, bearlabelarray, linearray, labelt, offset)
Checks the offset of bearish lines and deletes them if they are beyond a certain offset from the current bar index
@description Checks the offset of bearish lines and deletes them if they are beyond a certain offset from the current bar index
Parameters:
FailpointB (float )
bearlabelarray (label )
linearray (line )
labelt (bool)
offset (int)
Bullfailchecker(close1, FailpointB, bulllabelarray, linearray, labelt)
Checks if the current price has crossed above a bullish fail point and deletes the corresponding line and label
@description Checks if the current price has crossed above a bullish fail point and deletes the corresponding line and label
Parameters:
close1 (float)
FailpointB (float )
bulllabelarray (label )
linearray (line )
labelt (bool)
Bearfailchecker(close1, FailpointB, bearlabelarray, linearray, labelt)
Checks for bearish lines that have failed to trigger and removes them from the chart
@description This function checks for bearish lines that have failed to trigger (i.e., where the current price is above the fail point) and removes them from the chart along with any associated label.
Parameters:
close1 (float)
FailpointB (float )
bearlabelarray (label )
linearray (line )
labelt (bool)
rsibullchecker(rsiinput, rsiBull, secondbullline)
Checks for bullish RSI lines that have failed to trigger and removes them from the chart
@description This function checks for bullish RSI lines that have failed to trigger (i.e., where the current RSI value is below the line's trigger level) and removes them from the chart along with any associated line.
Parameters:
rsiinput (float)
rsiBull (float )
secondbullline (line )
rsibearchecker(rsiinput, rsiBear, secondbearline)
Checks for bearish RSI lines that have failed to trigger and removes them from the chart
@description This function checks for bearish RSI lines that have failed to trigger (i.e., where the current RSI value is above the line's trigger level) and removes them from the chart along with any associated line.
Parameters:
rsiinput (float)
rsiBear (float )
secondbearline (line )
TrendIndicatorsLibrary "TrendIndicators"
This is a library of 'Trend Indicators'.
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the source, not being restricted to just the closing price.
Indicators (this is a work in progress):
1. Absolute DI (Directional Moviment Index) (Difference between DI+ and DI-).
Used in 'DMI Stochastic Extreme' by Barbara Star.
2. DMI
DI_Abs(lengthDI, smoothDI, typeMA, lengthMA)
@description Absolute DI (Directional Moviment Index).
Used in 'DMI Stochastic Extreme' by Barbara Star.
Difference between DI+ and DI-
Parameters:
lengthDI : (int) Length of DI+/DI-
smoothDI : (bool) Sets whether absolute DI should be smoothed
typeMA : (int) Type of moving average of smoothing
lengthMA : (int) Length for moving average of smoothing
Returns: (float) Absolute value of DI
dmi(diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Same as ta.dmi()
Parameters:
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
dmi(source, diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Customized version of ta.dmi(), with custom source
Parameters:
source : (float) Source for DI+/DI-
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
