Supporting my on-going research into the value of pivots for forecasting market direction, Cucca recently sent me a link to one of Henry Carstens pivot based trading systems. Cucca also posted the code for a little MeClellan based system (in comments section of his blog) that produces some impressive results. Henry's pivot aproach is worth a look and I'll probably be deconstructing the system later in the week as I explore more pivot based mean regression systems. Henry doesn't explain exactly how "volatility" is defined, so I'll just jump in and offers some suggestions.
Today's offering is a variation of my earlier SD signal line study and simply looks at the value of the PP buffered by a lookback at a Len1 moving average of the PP and converted to a zero line value by dividing the resultant by the standard deviation of the range.
Later this week I'll look at the same theme using the R1-S1 pivot range as well as several other permutations.
If nothing else, this study again confirms the 9 day period as the most profitable for Qs fixed bar short exits (covers) once the system triggers.
1 comment:
Bob,
My guess is that you're seeing if anyone is paying attention, as each iteration of this formula gets closer and closer to the definition of the CCI.
I started to post a spoiler comment when you were using closing prices, but now that you've switched to the PP (what CCI calculations call the "typical price"), I can't resist.
It'd be interesting to compare the difference in results between using the "mean deviation" in the formal CCI calculation to the good 'ole standard deviation as above.
Cheers, and as always, enjoy following your work.
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