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>Alex and Bob, would you guys provide a technical analysis and critique of
>this XMA function using the filter concepts in your previous posts? How
>does it compare to the functions you've posted? Do you see anyway to make
>it "better" in terms of lag and overshoot? How would you improve it
>according to your ways of thinking?
>
>Inputs: Price(NumericSeries),Leng(NumericSimple);
>Vars: EMA(0),n(leng),K(2/(n+1)),x((n-1)/2);
>
>EMA = K*(2*Price - Price[x])+(1-K)*EMA[1];
>
>XAverage_ZeroLag = EMA;
K is the normal EMA smoothing factor
x is the Lag of the EMA
The (2*Price - Price[x]) term is then a projected price "Lag" bars into the future extrapolating the slope of price from the current point back "Lag" bars.
Interesting.
The transient response looks pretty decent also. The attached chart (BobR.01.gif) uses Jurik's test pattern. The red curve is your filter and the blue curve is one of my "good" filters - similar recovery from the sharp step and a bit more noise, but very little lag.
On real data the added noise shows up. I will post a second chart in a second message to hopefully avoid the file size limit.
I suspect it can be improved some by adding a high-frequency cut-off. I will play with it.
Bob Fulks
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BobR.01.gif
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