Linear Regression

((15*(sum(cum(1)*C,10))-(sum(cum(1),10)*(sum(C,10)))) /
((10*sum(pwr(cum(1),2),10))-pwr(sum(cum(1),2),10))-pwr(sum(cum(1),10),2))

Linear Regression (14)

(14 * Sum(Cum(1) * C,14) - Sum(Cum(1),14)* Sum(C,14)) /
(14 * Sum(Pwr(Cum(1),2),14) - Pwr(Sum(Cum(1),14),2)) *
Cum(1) + (Mov(C,14,S) - Mov(Cum(1),14,S) *
(14 * Sum(Cum(1) * C,14) - Sum(Cum(1),14) * Sum(C,14)) /
(14 * Sum(Pwr(Cum(1),2),14) - Pwr(Sum(Cum(1),14),2)))

Linear Regression Channel

DLR:= Input("linear regression",10,100,55);
DOSt:= Input("standard deviation",5,50,20);
;LinearReg( CLOSE ,DLR ) + ( 2 * ( Std( C,20 ))) {Up}
;LinearReg( CLOSE ,DLR ) - ( 2 * ( Std( C,20 ))) {Down}

Linear Regression Slope

nio:=Input("Number of points taken to calculate the ROCs",3,1000,14);

rll:=ROC(O,nio-1,%)/(nio-1);
rl:=ROC(O,nio,%)/nio;
rh:=ROC(O,nio+1,%)/(nio+1);
rhh:=ROC(O,nio+2,%)/(nio+2);

xio:=Input("Distances of ROCs from interpolation point XIO ",0.01,1,0.5);

rit:=(rll / (1+xio) +
rl / (xio+.0001)+
rh / (1-xio) +
rhh / (2-xio)) /
( 1 / (1+xio) + 1 / (xio+.0001) + 1 / (1-xio) + 1 / (2-xio));

ro:=LinRegSlope(LinRegSlope(rit,nio),nio);
ro

Linear Regression Slope - Normalized

Period:=Input("Periods",3,200,10);
ZeroKiller:=If(C=Ref(C,-1),0,C/(C-Ref(C,-1)));
NormalSlope:=LinRegSlope(ZeroKiller,Period);
NormalSlope;
0;

LinRegOscillator - CCT

(LinearReg(C,13)/Ref(LinearReg(C,13),-13))-1

LinRegSlope & Standard Deviation of Daily ROC's

watch:= 63; {lookback period}
ttt:=252; {projection periods}
mmm:=LinRegSlope( Log(C), watch ); {LinRegSlope}
sss:=Stdev(ROC(Log(C),1,$),watch); {StandardDeviation of daily ROCs}
ra:=(Exp(mmm*ttt-2*sss*Sqrt(ttt))-1)*100; {Projection -2SD;"risk averse"}
pe:=(Exp(mmm*ttt- sss*Sqrt(ttt))-1)*100; {Projection -1SD;"pessimistic"}
ne:=(Exp(mmm*ttt )-1)*100; {neutral}
op:=(Exp(mmm*ttt+ sss*Sqrt(ttt))-1)*100; {Projection +1SD;"optimistic"}
ra; {to display}

Looking for Trend

UpTrend:=Sum(C >= Ref(Mov(Typical(),3,S),-1),3)=3;
DownTrend:=Sum(C <= Ref(Mov(Typical(),3,S),-1),3)=3;
UpTrend;
DownTrend;