Thanks for catching this mistake - yes, I want to take the square root of the sum of values, not the square root of each one. Again I'll try to be more careful in the future about posting mistakes. Please, don't back off, any input is good input!
Clustering is just periods of high vola followed by more high vola and vice versa. The aim to use some brute force method to identify periods of extended high vola. The idea behind using a "rolling window" is that we have a lag associated with the number, meaning some history is included in the calc. We don't need a full on ARCH type model, just something simple to capture this effect.
Well, the goal is not trade filtering for now, but, I will eventually show you a use for this model in a filter in the future. I'm hoping people here would come up with it on thier own knowing what the characteristics of vola are, but, if worse comes to worse I'll spoon feed it.
Thanks for your input. TS code provided below. Also, I'm using TS because its easy to understand and quick, if someone could do it, I'd appreciate they would do this in Amibroker and post it as well.
Mike
var:
ssr(0),
j(0);
array:
return[11](0);
if time >= 605 and time <= 1400 then begin
for j=0 to 11 begin
return[0] = (Square(h[0] -l[0]));
return[1] = (Square(h[1] -l[1]));
return[2] = (Square(h[2] -l[2]));
return[3] = (Square(h[3] -l[3]));
return[4] = (Square(h[4] -l[0]));
return[5] = (Square(h[5] -l[5]));
return[6] = (Square(h[6] -l[6]));
return[7] = (Square(h[7] -l[7]));
return[8] = (Square(h[8] -l[8]));
return[9] = (Square(h[9] -l[9]));
return[10] = (Square(h[10]-l[10]));
return[11] = (Square(h[11]-l[11]));
end;
end;
ssr = squareroot(return[0]+return[1]+return[2]+return[3]+return[4]+return[5]+return[6]+return[7]+return[8]+return[9]+return[10]+return[11]);
Value1 = ssr;
Plot1( Value1, "SSR" ) ;
), thus creating an opening gap, quite often volatility dries up the next day, at least for a good part of the trading session, as if the large overnight price move needed to be "digested" by the market.