Josh, Thanks for another great explanation. I migh…
Ralph Vince - Apr 5, 2010
Josh, Thanks for another great explanation. I might point out to that it is not just the optimization algorithms used, but in the case of mazimizing for greatest probability of profit, there are many posssible optimal sets (f1,..,fn,z+,z-). There are multiple sets which will result in an equivalent (and highest) probability of profit.
If I understand the optimization problem correctly, I think it may be possible to achieve similar results in just minutes of computation with a different optimization approach. How long does it take to evaluate the fitness of one LSPM allocation?
Here is an example optimizer that is designed to find pretty globally optimal allocations while you wait: http://www.riskcog.com/portfolio-theme2.jsp#5e80e8d
The link you posted finds optimal allocations, but I don’t see how to apply any constraints. An unconstrained LSPM geometric growth optimization only takes a few seconds.
Also, the example in this post doesn’t find the growth-optimal allocation. Instead, it finds one–of potentially many–allocations that maximizes the probability of profitability, which is very different than a growth-optimal allocation.
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Not yet up to speed with R myself could I ask if you are quickly able to pin point why the following error message is currently being produced:
> # Drawdown-constrained maximum probability of profit (results on p. 173)
> res <- maxProbProfit(port, 1e-6, 12, probDrawdown, 0.1,
+ DD=0.2, calc.max=4, snow=cl, control=DEctrl)
Error in function (VTR = -Inf, strategy = 2, bs = FALSE, NP = NA, itermax = 200, :
unused argument(s) (refresh = 1, digits = 6)
With thanks, Grant
The refresh parameter was renamed to trace, and the digits parameters was removed in recent versions of DEoptim.
Create the DEctrl object using this line of code instead:
DEctrl <- list(NP=np, itermax=11, trace=1, initial=initpop)
Spot on! My thanks Josh.