LinearRegressionLibraryLibrary "LinearRegressionLibrary" contains functions for fitting a regression line to the time series by means of different models, as well as functions for estimating the accuracy of the fit.
Linear regression algorithms:
RepeatedMedian(y, n, lastBar) applies repeated median regression (robust linear regression algorithm) to the input time series within the selected interval.
Parameters:
y :: float series, source time series (e.g. close)
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
mSlope :: float, slope of the regression line
mInter :: float, intercept of the regression line
TheilSen(y, n, lastBar) applies the Theil-Sen estimator (robust linear regression algorithm) to the input time series within the selected interval.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
tsSlope :: float, slope of the regression line
tsInter :: float, intercept of the regression line
OrdinaryLeastSquares(y, n, lastBar) applies the ordinary least squares regression (non-robust) to the input time series within the selected interval.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
olsSlope :: float, slope of the regression line
olsInter :: float, intercept of the regression line
Model performance metrics:
metricRMSE(y, n, lastBar, slope, intercept) returns the Root-Mean-Square Error (RMSE) of the regression. The better the model, the lower the RMSE.
Parameters:
y :: float series, source time series (e.g. close)
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
rmse :: float, RMSE value
metricMAE(y, n, lastBar, slope, intercept) returns the Mean Absolute Error (MAE) of the regression. MAE is is similar to RMSE but is less sensitive to outliers. The better the model, the lower the MAE.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
mae :: float, MAE value
metricR2(y, n, lastBar, slope, intercept) returns the coefficient of determination (R squared) of the regression. The better the linear regression fits the data (compared to the sample mean), the closer the value of the R squared is to 1.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
Rsq :: float, R-sqared score
Usage example:
//@version=5
indicator('ExampleLinReg', overlay=true)
// import the library
import tbiktag/LinearRegressionLibrary/1 as linreg
// define the studied interval: last 100 bars
int Npoints = 100
int lastBar = bar_index
int firstBar = bar_index - Npoints
// apply repeated median regression to the closing price time series within the specified interval
{square bracket}slope, intercept{square bracket} = linreg.RepeatedMedian(close, Npoints, lastBar)
// calculate the root-mean-square error of the obtained linear fit
rmse = linreg.metricRMSE(close, Npoints, lastBar, slope, intercept)
// plot the line and print the RMSE value
float y1 = intercept
float y2 = intercept + slope * (Npoints - 1)
if barstate.islast
{indent} line.new(firstBar,y1, lastBar,y2)
{indent} label.new(lastBar,y2,text='RMSE = '+str.format("{0,number,#.#}", rmse))
Mô hình Thị trường
FunctionGeometricLineDrawingsLibrary "FunctionGeometricLineDrawings"
array_delete_all_lines(lines) deletes all lines in array.
Parameters:
lines : line array, array with line objects to delete.
Returns: void.
triangle(sample_x, sample_y, xloc, extend, color, style, width) Draw a Triangle with 3 vector2D(x, y) coordinates.
Parameters:
sample_x : int array, triangle sample data X coordinate values.
sample_y : float array, triangle sample data Y coordinate values.
xloc : string, defaultoptions=xloc.bar_index, xloc.bar_time.
extend : string, default=extend.none, options=(extend.none, extend.right, extend.left, extend.both).
color : color, default=
style : options line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both
width : width in pixels.
Returns: line array
trapezoid(sample_x, sample_y, xloc, extend, color, style, width) Draw a Trapezoid with 4 vector2D(x, y) coordinates:
Parameters:
sample_x : int array, trapezoid sample data X coordinate values.
sample_y : float array, trapezoid sample data Y coordinate values.
xloc : string, defaultoptions=xloc.bar_index, xloc.bar_time.
extend : string, default=extend.none, options=(extend.none, extend.right, extend.left, extend.both).
color : color, default=
style : options line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both
width : width in pixels.
Returns: line array
CreateAndShowZigzagLibrary "CreateAndShowZigzag"
Functions in this library creates/updates zigzag array and shows the zigzag
getZigzag(zigzag, prd, max_array_size) calculates zigzag using period
Parameters:
zigzag : is the float array for the zigzag (should be defined like "var zigzag = array.new_float(0)"). each zigzag points contains 2 element: 1. price level of the zz point 2. bar_index of the zz point
prd : is the length to calculate zigzag waves by highest(prd)/lowest(prd)
max_array_size : is the maximum number of elements in zigzag, keep in mind each zigzag point contains 2 elements, so for example if it's 10 then zigzag has 10/2 => 5 zigzag points
Returns: dir that is the current direction of the zigzag
showZigzag(zigzag, oldzigzag, dir, upcol, dncol) this function shows zigzag
Parameters:
zigzag : is the float array for the zigzag (should be defined like "var zigzag = array.new_float(0)"). each zigzag points contains 2 element: 1. price level of the zz point 2. bar_index of the zz point
oldzigzag : is the float array for the zigzag, you get copy the zigzag array to oldzigzag by "oldzigzag = array.copy(zigzay)" before calling get_zigzag() function
dir : is the direction of the zigzag wave
upcol : is the color of the line if zigzag direction is up
dncol : is the color of the line if zigzag direction is down
Returns: null
LineGetPriceOnLogScaleLibrary "LineGetPriceOnLogScale"
This library provides a way to calculate the y-coordinate of a line on a specified bar when the chart scale is Log.
The built-in `line.get_price()` function only works with linear scale and gives incorrect results when the chart is in Log scale.
The library only works with `bar_index` values and `xloc.bar_index`-based lines, `time`-based lines will cause errors to appear.
coordGetPriceLog(x1, y1, x2, y2, xi) Calculates the y-coordinate on the specified bar on the logarithmic scale.
Only coordinates based on bar index are applicable, bar time will throw an error.
Parameters:
x1 : First X coordinate of a line, index of the bar where the line starts.
y1 : First Y coordinate of a line, price on the price scale.
x2 : Second X coordinate of a line, index of the bar where the line ends.
y2 : Second Y coordinate of a line, price on the price scale.
xi : Index of the bar for which the price should be calculated.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
lineGetPriceLog(_line, xi) Calculates the y-coordinate on the specified bar for the logarithmic scale. Takes a line.
Only lines drawn based on `xloc.bar_index` are applicable, `xloc.bar_time` will throw and error.
Parameters:
_line : The line for which the price is calculated.
xi : Index of the bar for which the bar should calculate the price.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
MathGeometryCurvesChaikinLibrary "MathGeometryCurvesChaikin"
Implements the chaikin algorithm to create a curved path, from assigned points.
chaikin(points_x, points_y, closed) Chaikin algorithm method, uses provided points to generate a smoothed path.
Parameters:
points_x : float array, the x value of points.
points_y : float array, the y value of points.
closed : bool, default=false, is the path closed or not.
Returns: tuple with 2 float arrays.
smooth(points_x, points_y, iterations, closed) Iterate the chaikin algorithm, to smooth a sample of points into a curve path.
Parameters:
points_x : float array, the x value of points.
points_y : float array, the y value of points.
iterations : int, number of iterations to apply the smoothing.
closed : bool, default=false, is the path closed or not.
Returns: array of lines.
draw(path_x, path_y, closed) Draw the path.
Parameters:
path_x : float array, the x value of the path.
path_y : float array, the y value of the path.
closed : bool, default=false, is the path closed or not.
Returns: array of lines.
HarmonicPatternLibrary "HarmonicPattern"
Functions to detect/check harmonic patterns from provided values.
line_price_rate(point_c, point_b, point_a) Compute the price rate of the line AB divided by the the line BC
Parameters:
point_c : float, the price at point C.
point_b : float, the price at point B.
point_a : float, the price at point A.
Returns: float
line_time_rate(_c, _b, _a) Compute the time rate of the line AB divided by the the line BC
Parameters:
_c : float, the time or bar_index at point C.
_b : float, the time or bar_index at point B.
_a : float, the time or bar_index at point A.
Returns: float
is_inrange(value, min, max) Check if value is within min/max range of tolerance.
Parameters:
value : float, value to check tolerance.
min : float, minimum value in range of tolerance.
max : float, maximum value in range of tolerance.
Returns: bool
isHarmonicTriangle(rate_cba, margin_of_error) Check if the rate(s) correspond to pattern ("Harmonic Triangle").
Parameters:
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
is2Tap(rate_cba, margin_of_error) Check if the rate(s) correspond to pattern ("2Tap", 'Double Top / Bottom').
Parameters:
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
is3Tap(rate_edc, rate_cba, margin_of_error) Check if the rate(s) correspond to pattern ("3Tap", "Triple Top / Bottom").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
is4Tap(rate_gfe, rate_edc, rate_cba, margin_of_error) Check if the rate(s) correspond to pattern ("4Tap", "Quadruple Top / Bottom").
Parameters:
rate_gfe : float, percent rate of the triangle GFE. expects a negative rate.
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isABCD(rate_cba, rate_dcb, margin_of_error) Check if the rate(s) correspond to pattern ("AB=CD").
Parameters:
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isBat(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Bat").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isButterfly(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Butterfly").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isGartley(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Gartley").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isCrab(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Crab").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isShark(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Shark").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
is5o(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("5o").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isWolfe(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Wolfe").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
is3Driver(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("3 Driver").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isConTria(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Contracting Triangle").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isExpTria(rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Expanding Triangle").
Parameters:
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
isHnS(rate_fed, rate_feb, rate_edc, rate_dcb, rate_cba, rate_eda, margin_of_error) Check if the rate(s) correspond to pattern ("Head and Shoulders").
Parameters:
rate_fed : float, percent rate of the triangle FED. expects a negative rate.
rate_feb : float, percent rate of the triangle FEB. expects a negative rate.
rate_edc : float, percent rate of the triangle EDC. expects a negative rate.
rate_dcb : float, percent rate of the triangle DCB. expects a negative rate.
rate_cba : float, percent rate of the triangle CBA. expects a negative rate.
rate_eda : float, percent rate of the triangle EDA. expects a negative rate.
margin_of_error : float, percent rate of expected error margin, default 0.05(5%).
Returns: bool
Function Square WaveThis is a script to draw a square wave on the chart, with an indicator for current price.
Markets undergoing Dow Jones or Wyckoff Accumulation/Distribution cycles tend to move in such waves, and if the period of the cycles are detected, a signal for accumulation/distribution phases can be created as an early warning.
Useful inputs:
- Average True Range as the wave height.
- Assumed Wave period as the wave duration.
I divided the current price wave by 2 to make the indicator more visually friendly.
GLHF
- DPT
Grid SystemThis script plots a a square composed of 8 equilateral triangles ("grid"). User can set the frequency of calculation/interval by adjusting the 't' parameter.
Steps for calculating grid:
1. Find the highest high and lowest low for last 't' periods.
2. Calculate midpoint for prices during that interval (highest high + lowest low) / 2.
3. Center of the grid = {time , price midpoint}.
Interpretation:
Volatility : If price is volatile for a given period, the area of the grid will expand, since the top and bottom sides are based on the highest high and lowest low for the period. So as range for a given period increases, the grid's area increases.
Support and resistance : The grid's center line often acts as the support / resistance line.
Trend Following : The example chart shows Cognex (CGNX) price using an interval of t=365. When the stock's trend was bullish, the area of the grids became increasingly larger and the y-coordinate of each grid was greater than that of the previous grid.
[JRL] Murrey Math LinesMurrey Math Lines are support and resistance lines based on geometric mathematical formulas developed by T.
H. Murrey. MM lines are a derivation of the observations of W.D. Gann. Murrey's geometry facilitate the use of Gann's theories in a somewhat easier application. According to Gann's theory, price tends to trend and retrace in 1/8th intervals. The most important MM line levels are the 0/8, 4/8 and 8/8 levels, which typically provide strong support and resistance points. The 3/8 and 5/8 levels represent the low and high of the typical trading range. When price is above the typical trading range, it is considered overbought, and when it is below it is considered oversold. The 2/8 and 6/8 levels provide strong pivot points.
Some of the other Murrey Math indicators on TradingView use different formulas and therefore produce varying results. I've checked my indicator against MM indicators on other platforms and it is consistent with those indicators.
This indicator also allows users to switch to alternative timeframes for analysis and it includes labels for the MM lines. If you have any suggestions or comments, please leave them below.
Cheers!
[RS]Function - Geometric Line Drawingsfunctions using the new line functions in V4 to draw multiple geometric shapes.
