{_xStdDev Exponential moving standard deviation
 by Alex Matulich alex@unicorn.us.com 5/2003

 _xStdDev(x,n) returns a good approximation of the standard deviation
 of n values of x.  In _xStdDev the terms have exponential weight so
 the function reacts faster, and recovers from outliers more quickly
 than the traditional standard deviation.  This makes it well-suited
 for use in time series analysis.
}

Inputs:
    x(NumericSeries),       {price data}
    length(NumericSimple);  {"lookback" length; can change mid-stream}

Vars:
    w0(0), w1(0),   {exponential weights}
    n(0),           {used as sample size}
    avx(0);         {average of x and average of x^2}

if n <> length or CurrentBar <= 1 then begin {initialize things}
    n = length;
    w0 = 2/(n+1);
    w1 = 1 - w0;
    if Currentbar <= 1 then avx = x;
end;

avx = w0*x + w1*avx[1];
_xStdDev = SquareRoot(w0*(x-avx)*(x-avx) + w1*_xStdDev[1]*_xStdDev[1])