optimalf: Optimal f In LSPM: The Leverage Space Portfolio Modeler

Description

Find optimal f for a set of trades

Usage

 1 2 optimalf(lsp, constrFun=NULL, constrVal=NULL, margin=NULL, equity=NULL, upper, lower, ...)

Arguments

 lsp A lsp object. constrFun A string naming the constraint function. constrVal The value of the constraint function that should not be exceeded. margin A vector of inital margin values for each event series. equity Current account equity. upper Upper f-value bounds (recycled, if necessary). lower Lower f-value bounds (recycled, if necessary). ... Parameters to be passed to constrFun.

Value

 f Optimal f G GHPR at the optimal f

Joshua Ulrich

References

Vince, Ralph (2007) The Handbook of Portfolio Mathematics. New York: John Wiley & Sons, Inc.
Vince, Ralph (2009) The Leverage Space Trading Model. New York: John Wiley & Sons, Inc.

Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 data(port) # DEoptim parameters (see ?DEoptim) DEctrl <- list(NP=30, itermax=100) # Unconstrainted Optimal f res <- optimalf(port, control=DEctrl) # Margin-constrainted Optimal f resMargin <- optimalf(port, control=DEctrl, equity=1e5, margin=-port\$maxLoss*2) ## Not run: # Ruin-constrained Optimal f resRuin <- optimalf(port, probRuin, 0.1, DD=0.2, horizon=4, control=DEctrl) # Drawdown-constrained Optimal f resDrawdown <- optimalf(port, probDrawdown, 0.1, DD=0.2, horizon=4, control=DEctrl) # Create snow socket cluster for two cores library(snow) clust <- makeSOCKcluster(2) # Drawdown-constrained Optimal f using two cores resSnow <- optimalf(port, probDrawdown, 0.1, DD=0.2, horizon=4, snow=clust, control=DEctrl) ## End(Not run)

LSPM documentation built on May 31, 2017, 4:15 a.m.