Hi All,
Been learning J for a bout a year now and very impressed - although it's a
mind bend. I feel my understanding of complex problem is clearer however i
have yet to actual code something interesting in J.
Here is an interesting problem that I'd like some input on......
I'm trying to implement an Expected Volatility equation 4.20 from the book
(by the Olson group) High Frequency Finance
in J and I'm curious if this is the correct J-way of solving a simplified
subset of the problem:
ExpectedVolatility = (A + B) * C + D
so super simple problem reduction:
data =: 1 2 3 4
goal (non j notation): (1+2)*3 + 4
1st-cut: (0{data + 1{data) * 2{data + 3{data
2nd-cut: +/ 0 1 & { data * 2{data + 3{data
3rd-cut: I'm sure there is a more elegent way to do this, maybe using forks
????
I'm curious if the following is the correct way to go about solving problems
in a J-way:
The actuality data matrix would be something like:
(datetime,px,a,b,c,d,e,f,g,h,i,j,k,l,m,n,o)
I need a verb to transform this noun
(datetime,px,a,b,c,d,e,f,g,h,i,j,k,l,m,n,o)
into this (easy to digest noun)
(A B C D)
where i have not defined the relation,
then I'd need another verb to transform the easy to digest noun into the
Expected Volatility noun where i have defined the relation above (but
probably not in an elegant j-way).
Am i on the right path for thinking in J, thoughts, comments...greatly
appreciated.
Thanks,
Joe
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