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Thanks Gary,
thats a far more sensible way to do it -- I get very different av
prices for the cash compared with your continuos futures for 1998
though.
range avyear %
1992 3.51 415.12 0.85%
1993 3.28 451.96 0.73%
1994 3.76 460.56 0.82%
1995 4.01 541.23 0.74%
1996 6.76 669.88 1.01%
1997 12.62 873.79 1.44%
1998 17.02 1085.50 1.57%
1999 20.38 1327.33 1.54%
2000 25.53 1447.45 1.76%
2001 22.24 1228.43 1.81%
2002 20.56 1017.01 2.02%
>> Can you also provide more statistically valid ranges expressed as a
>> percentage of average annual price level ?
GF> Run this indicator on daily data:
GF> vars: sum(0), sumprice(0), num(0);
GF> if year(date)>year(date[1]) or lastbaronchart then begin
GF> print(year(date[1])+1900:4:0,": #days = ",num:3:0,
GF> ", Avg range = ",sum/num:2:2,
GF> ", Avg price: ", sumprice/num:4:2,
GF> ", % = ",100*(sum/num) / (sumprice / num):1:2);
GF> sum = 0;
GF> sumprice = 0;
GF> num = 0;
GF> end;
GF> sum = sum + H-L;
GF> sumprice = sumprice + (H+L)/2;
GF> num = num + 1;
GF> plot1(100*(H-L)/((H+L)/2), "Range%");
GF> plot2(xaverage(100*(H-L)/((H+L)/2), 40), "Range avg");
GF> When I run it on continuous SP, I get:
GF> 1998: #days = 249, Avg range = 17.64, Avg price: 1293.38, % = 1.36
GF> 1999: #days = 245, Avg range = 20.79, Avg price: 1485.69, % = 1.40
GF> 2000: #days = 252, Avg range = 26.11, Avg price: 1519.05, % = 1.72
GF> 2001: #days = 250, Avg range = 20.93, Avg price: 1213.28, % = 1.72
GF> 2002: #days = 202, Avg range = 20.49, Avg price: 1019.06, % = 2.01
GF> So according to this measure, the volatility has been going UP on
GF> a yearly basis, as a percentage of average price.
GF> Furthermore, if you look at the plot1/2 values, you'll see the
GF> daily ranges were running in the 1.25-1.50% range for the first
GF> half of the year, but have been over 2.50 for the last several
GF> months. So by this measure, the recent volatility is
GF> historically quite high.
GF> Gary
--
Best regards,
Michael mailto:michaelstewart@xxxxxxxxxxxxx
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