Solver for a generic optimal portfolio
The diversification return is a side effect of rebalancing. To 'optimize' for diversification return, you'll still need some other objectives and constraints. In any complex feasible space for optimization with a non-trivial number of assets, you can often find multiple portfolios with similar base properties (like return and variance). You could, in theory, maximize diversification return by finding neighboring 'near-optimal' portfolios on your other objectives and constraints and then choosing among them with a preference for higher turnover. This, of course, will incur significant rebalancing costs. These associated costs are why a continuously rebalanced portfolio is unrealistic, and why most portfolio construction methodologies try to minimize turnover. (There are other reasons for minimizing turnover too, but those are the ones most often discussed). We still don't know enough about what the other objectives and constraints you have for your portfolio to recommend a specific solver. Regards, Brian
On 03/12/2016 07:47 PM, Alec Schmidt wrote:
Brian/Mark/Patrick, Thanks for answering my curiosity on Saturday night. I just come across the Willenbrock's paper http://arxiv.org/abs/1109.1256 and wonder if it makes sense to optimize so-called diversification return (eq 13) and, if yes, what tool you might suggest. Best, Alec
________________________________________ From: R-SIG-Finance <r-sig-finance-bounces at r-project.org> on behalf of Brian G. Peterson <brian at braverock.com> Sent: Saturday, March 12, 2016 8:38 PM To: r-sig-finance at r-project.org Subject: Re: [R-SIG-Finance] Solver for a generic optimal portfolio On 03/12/2016 07:30 PM, Alec Schmidt wrote: I'd like to estimate weights of an optimal portfolio other than min variance portfolio by replacing covariance matrix with something else. Is there an R package that can do this (my understanding is that solve.QP is not helpful for this task). Alec, You'll need to be a little more specific about what your target objectives and constraints are if someone is going to be able to help you. For some objectives and constraints, quadratic, linear, or conical solvers can be used. For other objective and constraint combinations, you'll need a global stochastic solver. Without understanding precisely what you're trying to do, no one can give you an answer about which package(s) will be best for your problem. I can say that I think of any portfolio formulation I can come up with may be solved with R. Regards, Brian -- Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock _______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go. _______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.
Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock