ECI is based on the FE algorithm
Original plot style by Mobius
Expansion Contraction Indicator (ECI): 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. ECI plots the areas where price becomes compressed with colored and clouded bands. The indicator also leaves legacy points in areas of past compression.
Code:
#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 = 14; #hint EciLength: Length for calculations.
input AvgLength = 10; #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;
}
# 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);
AddLabel(1, "Energy Level = " + ECI, color.white);
# End Code Modified ECI
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