mr_movlinreg2.efs
EFSLibrary - Discussion Board
File Name: mr_movlinreg2.efs
Description:
Moving Linear Regression by. Dr. Mel Raiman
Formula Parameters:
- LR Periods : 3
- LR1 Channels StDev : 1
- LR2 Channels StDev : 2
- MA Periods : 4
- MA Price Source : Close
- MA Type : Exponential
- LR Thickness : 2
- LR Color : Lime
- MA Color : Red
Notes:
Version 2.0 - Added second set of regression lines at +/- 2 standard deviations.
Download File:
mr_movlinreg2.efs
EFS Code:
/*********************************
Provided By:
eSignal (Copyright c eSignal), a division of Interactive Data
Corporation. 2009. All rights reserved. This sample eSignal
Formula Script (EFS) is for educational purposes only and may be
modified and saved under a new file name. eSignal is not responsible
for the functionality once modified. eSignal reserves the right
to modify and overwrite this EFS file with each new release.
Description:
Moving Linear Regression by. Dr. Mel Raiman
Version: 3.0 04/16/2009
Formula Parameters: Defaults:
LR Periods 3
LR1 Channels StDev 1
LR2 Channels StDev 2
MA Periods 4
MA Price Source Close
MA Type Exponential
LR Thickness 2
LR Color Lime
MA Color Red
Notes:
Version 2.0 - Added second set of regression lines at +/-
2 standard deviations.
*****************************************************************/
var fpArray = new Array();
var bInit = true;
function preMain() {
setPriceStudy(true);
setStudyTitle("Moving LR 2");
setCursorLabelName("Mov LR", 0);
setCursorLabelName("MA", 1);
setDefaultBarFgColor(Color.lime, 0);
setDefaultBarFgColor(Color.red, 1);
setDefaultBarThickness(1, 0);
setDefaultBarThickness(1, 1);
setShowTitleParameters(false);
var x = 0;
fpArray[x] = new FunctionParameter("nLRlen", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("LR Periods");
setLowerLimit(1);
setDefault(3);
}
fpArray[x] = new FunctionParameter("nLRstdev1", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("LR1 Channels StDev");
setLowerLimit(0);
setDefault(1);
}
fpArray[x] = new FunctionParameter("nLRstdev2", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("LR2 Channels StDev");
setLowerLimit(0);
setDefault(2);
}
fpArray[x] = new FunctionParameter("nMAlen", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("MA Periods");
setLowerLimit(2);
setDefault(4);
}
fpArray[x] = new FunctionParameter("sMAPriceSource", FunctionParameter.STRING);
with(fpArray[x++]) {
setName("MA Price Source");
addOption("open");
addOption("high");
addOption("low");
addOption("close");
addOption("hl2");
addOption("hlc3");
addOption("ohlc4");
setDefault("close");
}
fpArray[x] = new FunctionParameter("sMAType", FunctionParameter.STRING);
with(fpArray[x++]) {
setName("MA Type");
addOption("sma");
addOption("ema");
addOption("wma");
addOption("vwma");
setDefault("ema");
}
fpArray[x] = new FunctionParameter("nLRThickness", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("LR Thickness");
setLowerLimit(1);
setDefault(2);
}
fpArray[x] = new FunctionParameter("nMAThickness", FunctionParameter.NUMBER);
with(fpArray[x++]) {
setName("MA Thickness");
setLowerLimit(1);
setDefault(2);
}
fpArray[x] = new FunctionParameter("nLRColor", FunctionParameter.COLOR);
with(fpArray[x++]) {
setName("LR Color");
setDefault(Color.lime);
}
fpArray[x] = new FunctionParameter("nMAColor", FunctionParameter.COLOR);
with(fpArray[x++]) {
setName("MA Color");
setDefault(Color.red);
}
}
var xMA = null;
var xLRvaluesIn_A = null;
var xLRvaluesIn_B = null;
var xLRvalues23_A = null;
var xLRvalues23_B = null;
var xStDev = null;
function main(nLRlen, nLRstdev1, nLRstdev2, nMAlen, sMAPriceSource, sMAType,
nLRThickness, nMAThickness, nLRColor, nMAColor) {
var nBarState = getBarState();
var vStDev = null;
var A = 0;
var B = 0;
var A2 = 0;
var B2 = 0;
var vMA = 0;
if (nBarState == BARSTATE_ALLBARS) {
if (nLRlen == null) nLRlen = 10;
if (nLRstdev1 == null) nLRstdev1 = 1;
if (nLRstdev2 == null) nLRstdev2 = 2;
if (nMAlen == null) nMAlen = 4;
if (sMAPriceSource == null) sMAPriceSource = "close";
if (sMAType == null) sMAType = "ema";
if (nLRThickness == null) nLRThickness = 2;
if (nMAThickness == null) nMAThickness = 2;
if (nLRColor == null) nLRColor = Color.lime;
if (nMAColor == null) nMAColor = Color.red;
}
if (bInit == true) {
xMA = eval(sMAType)(nMAlen, eval(sMAPriceSource)());
xLRvaluesIn_A = efsInternal("LinReg", nLRlen);
xLRvaluesIn_B = getSeries(xLRvaluesIn_A, 1);
xLRvalues23_A = efsInternal("LinReg", 23);
xLRvalues23_B = getSeries(xLRvalues23_A, 1);
xStDev = efsInternal("StDev", 23);
setDefaultBarThickness(nLRThickness, 0);
setDefaultBarThickness(nMAThickness, 1);
setDefaultBarFgColor(nLRColor, 0);
setDefaultBarFgColor(nMAColor, 1);
bInit = false;
}
vMA = xMA.getValue(0);
A = xLRvaluesIn_A.getValue(0);
B = xLRvaluesIn_B.getValue(0);
vStDev = xStDev.getValue(0);
A2 = xLRvalues23_A.getValue(0);
B2 = xLRvalues23_B.getValue(0);
if (vMA == null || B == null || B2 == null) return;
// Basis
drawLineRelative(0, B2, -(23 - 1), (A2 * (23 - 1)) + B2,
PS_SOLID, 2, Color.cyan, "Basis");
// LR1
drawLineRelative(0, B2 + (nLRstdev1 * vStDev), -(23 - 1), (A2 * (23 - 1)) + B2 + (nLRstdev1 * vStDev),
PS_SOLID, 2, Color.cyan, "Upr1");
drawLineRelative(0, B2 - (nLRstdev1 * vStDev), -(23 - 1), (A2 * (23 - 1)) + B2 - (nLRstdev1 * vStDev),
PS_SOLID, 2, Color.cyan, "Lwr1");
// LR2
drawLineRelative(0, B2 + (nLRstdev2 * vStDev), -(23 - 1), (A2 * (23 - 1)) + B2 + (nLRstdev2 * vStDev),
PS_SOLID, 2, Color.RGB(0, 140, 140), "Upr2");
drawLineRelative(0, B2 - (nLRstdev2 * vStDev), -(23 - 1), (A2 * (23 - 1)) + B2 - (nLRstdev2 * vStDev),
PS_SOLID, 2, Color.RGB(0, 140, 140), "Lwr2");
return new Array(B, vMA);
}
var xSMAy = null;
var bSecondInit = false;
function LinReg(nLRlen) {
var xSum = 0;
var yAvg = 0;
if (bSecondInit == false) {
xSMAy = sma(nLRlen);
bSecondInit = true;
}
yAvg = xSMAy.getValue(0);
if (yAvg == null) return;
var xAvg = ((0 + (nLRlen - 1)) * nLRlen / 2) / nLRlen;
var aSum1 = 0;
var aSum2 = 0;
i = 0;
for (i = 0; i < nLRlen; ++i) {
aSum1 += (i - xAvg) * (close( - i) - yAvg);
aSum2 += (i - xAvg) * (i - xAvg);
}
var A = (aSum1 / aSum2);
var B = yAvg - (A * xAvg);
return new Array(A, B);
}
function StDev(nLength) {
var sumX = 0;
var sumX2 = 0;
var nClose = close( - nLength);
if (nClose == null) return;
for (i = 0; i < nLength; ++i) {
nClose = close( - i);
sumX += nClose;
sumX2 += (nClose * nClose);
}
var meanX = (sumX / nLength);
var stdev = Math.sqrt((sumX2 / nLength) - (meanX * meanX));
return stdev;
}