#------------------------------------------------------------------------------------
#hint: Expansion Contraction Indicator (ECI): \n ECI Identifies areas of price compression which leads to price expansion. ECI doesn't show the direction of a trend but does indicate when a trend is going to resume (price flagging) or if a change in trend polarity is happening.\n ECI plots the areas where price becomes compressed with colored and clouded bands. The indicator also leaves legacy points in areas of past compression.
# ECI is based on the FE algorithm
# Original plot style by Mobius
# Note: Default Lengths are not optimized. My personal experience has been length ranges between 8 and 13 are generally effective.
# Here's another way to look at Fractal Energy. This study plots it on the chart graph with clouded areas for the current price compression, exhaustion area and leaves colored points as a legacy plot for past areas.
# Good CSA choices with this study are:
# ECI + SuperTrend + Fractal Pivots
# ECI + SuperTrend + RSI in Laguerre Time
# ECI + SuperTrend + Standard Deviation Bands
# ECI + Linear Regression Standard Deviation Bands
# This version Modified to filter price to a normalized distribution
# User Inputs
input EciLength = 9; #hint EciLength: Length for calculations.
input AvgLength = 34; #hint AvgLength: Length for smoothing.
input AvgType = AverageType.SIMPLE; #hint AvgType: Average Type
input MeanValue = HL2; #hint MeanValue: Point of origen.
input DisplayPoints = yes; #hint DisplayPoints: No Points.
input OnExpansion = yes; #hint OnExpansion: Line extensions.
# Variables
script g {
input data = close;
def w = (2 * Double.Pi / 8);
def beta = (1 - Cos(w)) / (Power(1.414, 2.0 / 4) - 1 );
def alpha = (-beta + Sqrt(beta * beta + 2 * beta));
def G = Power(alpha, 4) * data +
4 * (1 – alpha) * G[1] – 6 * Power( 1 - alpha, 2 ) * G[2] +
4 * Power( 1 - alpha, 3 ) * G[3] - Power( 1 - alpha, 4 ) * G[4];
plot Line = G;
}
def o = g(data = open);
def h = g(data = high);
def l = g(data = low);
def c = g(data = close);
def bar = BarNumber();
def HMax = Highest(Max(h, c[1]), EciLength);
def LMax = Lowest(Min(l, c[1]), EciLength);
def TR = HMax - LMax;
def ECI = Round((Log(Sum(TrueRange(h, c, l), EciLength) / TR) /
Log(EciLength)) / TickSize(), 0) * TickSize();
def Avg = MovingAverage(AverageType = AvgType, ECI, AvgLength);
def S1 = if ECI crosses above Avg
then MeanValue
else S1[1];
def S = ECI > Avg;
def SBars = if ECI > Avg
then bar
else Double.NaN;
def StartBar = if ECI crosses above Avg
then bar
else StartBar[1];
def LastSBar = if ECI crosses below Avg
then bar
else LastSBar[1];
def PP = if ECI crosses above Avg
then MeanValue
else PP[1];
def Mean_Limit = if bar != StartBar
then bar - StartBar
else if bar == StartBar
then Double.NaN
else Mean_Limit[1];
def SHigh = if ECI crosses above Avg
then h
else SHigh[1];
def SHighBar = if S and
h == SHigh
then bar
else SHighBar[1];
def SHigh_Limit = if bar == StartBar
then Double.NaN
else if bar > StartBar
then bar - SHighBar
else SHigh_Limit[1];
def SLow = if ECI crosses above Avg
then l
else SLow[1];
def SLowBar = if S and
l == SLow
then bar
else SLowBar[1];
def SLow_Limit = if bar == StartBar
then Double.NaN
else if bar > StartBar
then bar - SLowBar
else SLow_Limit[1];
# Internal Script Reference
script LinePlot {
input LineLimit = 0;
input OnExpansion = yes;
input data = close;
input bar = 0;
def ThisBar = HighestAll(bar);
def cLine = if bar == ThisBar
then data
else Double.NaN;
def cond1 = CompoundValue(1, if IsNaN(data)
then cond1[1]
else data, data);
plot P = if ThisBar - LineLimit <= bar
then HighestAll(cLine)
else Double.NaN;
plot ExpLine = if OnExpansion and
IsNaN(data[-1])
then cond1
else Double.NaN;
}
#Conditions
def sellerRegular = eci crosses below avg;
def buyerRegular = eci crosses below avg;
def lastbuy = highestall(if sellerRegular[1] and !sellerRegular then barnumber() else Double.NaN);
def lastsell = highestall(if buyerRegular[1] and !buyerRegular then barnumber() else Double.NaN);
def cond = max(lastbuy, lastsell);
#addlabel(1, lastbuy + " " + lastsell + " " + cond);
# Plots
plot SD_Pivot = LinePlot(data = PP, LineLimit = Mean_Limit, OnExpansion = OnExpansion, bar = StartBar).P;
plot SD_Pivot_X = LinePlot(data = PP, LineLimit = StartBar).ExpLine;
SD_Pivot.SetDefaultColor(Color.CYAN);
SD_Pivot_X.SetDefaultColor(Color.CYAN);
plot SD_R1 = LinePlot(data = SHigh, LineLimit = SHigh_Limit, OnExpansion = OnExpansion, bar = SHighBar).P;
plot SD_R1_X = LinePlot(data = SHigh, LineLimit = SHigh_Limit).ExpLine;
SD_R1.SetDefaultColor(Color.LIGHT_GREEN);
SD_R1_X.SetDefaultColor(Color.LIGHT_GREEN);
plot SD_S1 = LinePlot(data = SLow, LineLimit = SLow_Limit, OnExpansion = OnExpansion, bar = SLowBar).P;
plot SD_S1_X = LinePlot(data = SLow, LineLimit = SLow_Limit).ExpLine;
SD_S1.SetDefaultColor(Color.LIGHT_RED);
SD_S1_X.SetDefaultColor(Color.LIGHT_RED);
plot SPlot = if S
then S1 #l - (2 * TickSize())
else Double.NaN;
SPlot.SetHiding(!DisplayPoints);
SPlot.SetPaintingStrategy(PaintingStrategy.POINTS);
SPlot.SetLineWeight(1);
SPlot.SetDefaultColor(Color.YELLOW);
#addCloud(SD_pivot, SD_R1, CreateColor(50,150,75), CreateColor(50,150,70));
#addCloud(SD_S1, SD_pivot, CreateColor(175,0,50), CreateColor(175,0,50));
#addCloud(SD_pivot_X, SD_R1_X, CreateColor(50,150,75), CreateColor(50,150,70));
#addCloud(SD_S1_X, SD_pivot_X, CreateColor(175,0,50), CreateColor(175,0,50));
# Audible Alerts
#Alert(ECI crosses below Avg, "Exit", Alert.BAR, Sound.Bell);
#addverticalLine(ECI crosses above Avg, "Fire", color = Color.gray);
AddLabel(1, "ECI CHI Level = " + ECI, Color.YELLOW);
#AddVerticalLine(ECI crosses below Avg, "ECI down", color = Color.plum);
#AddVerticalLine(ECI crosses above Avg, "ECI up", color = Color.LIME);
# End Code Modified ECI
################
# Time Anchored Regression Channel
# Mobius
# V01.01.2016
#Modified to use zigzagHighLow as a cond anchor
#08:35 Mobius: Here's the anchored Regression Channel I use
#02.12.2019 10:49 Mobius: Just a note to the Anchored LRC. I usually change to 930 from 1800 about 11:00 EST. I don't change to 1800 till 2000 if I still have the program up and running. I could program it to do that automatically but am too lazy.
input y = close;
input Channel_1_Width = 0.70;
input Channel_2_Width = 1.00;
input LineWeight = 1;
script E
{
input y = close;
input n = 20;
def s = fold i = 0 to n
with j
do j + GetValue(y, i);
plot D = s;
}
# Variables
def o = open;
def h = high;
def l = low;
def c = close;
def x = BarNumber();
def nan = Double.NaN;
def xx = if IsNaN(c[-1]) and !IsNaN(c) then x else xx[1];
## code comment for line immediately above
## thinking from left to right.. xx = 0 until the curren tbar is reached
## at the current bar xx = x
## beyond the current bar xx = xx[1] the value of xx one bar back
def firstBar = if BarNumber() == cond
then x
else firstBar[1];
def S_y = if x == HighestAll(firstBar)
then y
else if x > HighestAll(firstBar)
then S_y[1] + y
else S_y[1];
def S_x = if x == HighestAll(firstBar)
then 1
else if x > HighestAll(firstBar)
then S_x[1] + 1
else S_x[1];
def x0_ = HighestAll(xx) - firstBar;
def x1 = HighestAll(if !IsNaN(y) and IsNaN(y[-1])
then x
else nan);
def x0 = HighestAll(if GetValue(x, -x0_) == x1
then x
else nan);
def x_ = if GetValue(x, -x0_) >= x1
then x - x0
else x_[1];
def Ex = E(x_, x0_);
def Ey = E(y, x0_);
def Exy = E(x_ * y, x0_);
def Exsq = E(Sqr(x_), x0_);
def b = (x0_ * Exy - (Ex * Ey)) / (x0_ * Exsq - (Ex * Ex));
def a = (GetValue(Ey, x - x1) - GetValue(b, x - x1) * GetValue(Ex, x - x1)) / x0_;
def LR = a + (GetValue(b, x - x1) * x_);
def r = Max(h, c[1]) - Min(l, c[1]);
def Er = E(r, x0_) / x0_;
def mean = S_y / S_x;
def SD = Sqrt((1 / S_x) * (E(Sqr(y - mean), S_x)));
# Plots
plot LRL = if x > x1 + 5 then nan else
if x >= x0 # x is defined as barnumber()
then LR
else nan; # from nube
#plot LRL = if x >= x0 # x is defined as barnumber()
# then LR
# else nan; # mobius original
LRL.SetStyle(Curve.FIRM);
LRL.SetLineWeight(LineWeight + 1);
LRL.AssignValueColor(if GetValue(a, x - x1) < LR
then Color.CYAN
else Color.ORANGE);
LRL.HideBubble();
LRL.HideTitle();
plot upper1 = LRL + (HighestAll(SD) * Channel_1_Width);
upper1.SetLineWeight(LineWeight);
upper1.SetDefaultColor(Color.LIGHT_GRAY);
upper1.HideBubble();
upper1.HideTitle();
plot lower1 = LRL - (HighestAll(SD) * Channel_1_Width);
lower1.SetLineWeight(LineWeight);
lower1.SetDefaultColor(Color.LIGHT_GRAY);
lower1.HideBubble();
lower1.HideTitle();
plot upper2 = LRL + (HighestAll(SD) * Channel_2_Width);
upper2.SetLineWeight(LineWeight);
upper2.SetDefaultColor(Color.LIGHT_GRAY);
upper2.HideBubble();
upper2.HideTitle();
plot lower2 = LRL - (HighestAll(SD) * Channel_2_Width);
lower2.SetLineWeight(LineWeight);
lower2.SetDefaultColor(Color.LIGHT_GRAY);
lower2.HideBubble();
lower2.HideTitle();
# End Code Time Anchored Regression Channel
#
