[GSoC-PortA] GSoC Timeline/Kickoff

[Doug Martin]

Two initial comments about regime switching models and their use, keeping mind that I haven’t looked at the proposal in a long time (maybe send it along):

 

1)      There are a lot of models and they tend to be complex.  The good news is that this PortfolioAnalytics development will support people to more (badly needed) research on what models are really worth using.

 

2)      As for use in portfolio optimization a main feature needed is allow the user to specify how to blend 

data from a prior regime (or regimes) and the new  regime for which you at first have very little data (maybe you already included this in the proposal?)

 

Doug

 

 

From: gsoc-porta-bounces at lists.r-forge.r-project.org [mailto:gsoc-porta-bounces at lists.r-forge.r-project.org] On Behalf Of Ross Bennett
Sent: Monday, May 19, 2014 8:20 AM
To: PortfolioAnalytics
Subject: [GSoC-PortA] GSoC Timeline/Kickoff

 

Mentors (and others on the list),

 

It was great seeing you all at R/Finance last week.

 

Here are the first 3 tasks in the timeline in my original proposal.

5/19 - 5/30: Multilayer Optimization

5/31 - 6/13: Regime Switching Optimization

6/14 - 6/27: Factor Portfolio Optimization

 

I would like to modify the timeline as follows:

5/19 - 5/30: Regime Switching Optimization

5/31 - 6/13: Factor Portfolio Optimization

6/14 - 6/27: Multilayer Optimization

 

Regime Switching Optimization

My code example for the proposal was for regime switching. I kept it pretty general so that the user can just pass in a time series of what portfolio to use depending on the regime for any arbitrary regime switching model. Do you have any comments or feedback on my proposed way for supporting regime switching?

The regime switching example is in the following code gist

https://gist.github.com/rossb34/9645489

Factor Models to Estimate Moments

I reached out to Kris Boudt a few weeks ago and he shared some of the code he used for his paper. I put together a small package as a prototype. One thing to note is that Kris sent me C++ code (using Rcpp) for computing the cokurtosis error matrix. I would prefer not to rewrite the code in R, but this does mean introducing a dependency on Rcpp.  Along these same lines, we could also write functions to compute the 3rd and 4th moments in C++. The Armadillo library has a kron() function to compute the kronecker product making the higher moments an easy computation using RcppArmadillo. We could do this as a prototype in PortfolioAnalytics and eventually move to PerformanceAnalytics so M3.MM and M4.MM are compiled code. Thoughts?

Here is the source code of the prototype package for moment estimates.

https://bitbucket.org/rossbennett34/momentestimation/src

 

Best,

Ross

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