[Returnanalytics-commits] r3505 - in pkg/PortfolioAnalytics: man vignettes

Mon Aug 11 04:39:13 CEST 2014

Author: rossbennett34
Date: 2014-08-11 04:39:12 +0200 (Mon, 11 Aug 2014)
New Revision: 3505

Modified:
   pkg/PortfolioAnalytics/man/PortfolioAnalytics-package.Rd
   pkg/PortfolioAnalytics/vignettes/PA.bib
   pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.Rnw
   pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.pdf
Log:
adding reference information

Modified: pkg/PortfolioAnalytics/man/PortfolioAnalytics-package.Rd
===================================================================

--- pkg/PortfolioAnalytics/man/PortfolioAnalytics-package.Rd	2014-08-10 15:30:38 UTC (rev 3504)
+++ pkg/PortfolioAnalytics/man/PortfolioAnalytics-package.Rd	2014-08-11 02:39:12 UTC (rev 3505)
@@ -68,7 +68,7 @@
 }
 
 \section{Advanced Optimization}{
-In addition to the more standard optimizations described above, \kdb{PortfolioAnalytics} also supports multi-layer optimization and regime switching optimization. 
+In addition to the more standard optimizations described above, \kbd{PortfolioAnalytics} also supports multi-layer optimization and regime switching optimization. 
 
 Support for multi-layer optimization allows one to construct a top level portfolio and several sub-portfolios with potentially different assets, constraints, and objectives. First, each sub-portfolio is optimized out-of-sample which creates a time series of returns. One can think of the out of sample returns for each sub-portfolio as the returns for a synthetic instrument. Finally, the out-of-sample returns of each sub-portfolio are then used as inputs for the top level optimization. The top level portfolio and sub-portfolios are created as normal using \code{portfolio.spec}, \code{add.constraint}, and \code{add.objective}. The multi-layer portfolio specification object is first initialized by passing the top level portfolio to \code{mult.portfolio.spec}. Sub-portfolios are then added with \code{add.sub.portfolio}. The multi-layer portfolio specification object can then be passed to \code{optimize.portfolio} and \code{optimize.portfolio.rebalancing}. See \code{demo(multi_layer_optimization)}.
 
@@ -76,7 +76,7 @@
 }
 
 \section{Portfolio Moments}{
-The \kdb{PortfolioAnalytics} framework to estimate solutions to constrained optimization problems is implemented in such a way that the moments of the returns are set once for use in lower level optimization functions. The \code{set.portfolio.moments} function computes the first, second, third, and fourth moments depending on the objective function(s) in the \code{portfolio} object. For example, if the third and fourth moments do not need to be calculated for a given objective, then \code{set.portfolio.moments} will try to detect this and not compute those moments. Currently, \code{set.portfolio.moments} implements methods to compute moments based on sample estimates, higher moments from fitting a statistical factor model based on the work of Kris Boudt, the Black Litterman model, and the Fully Flexible Framework based on the work of Attilio Meucci (NEED REFERENCE HERE). See the Custom Moment and Objective Functions vignette for a more detailed description and examples. 
+The \kbd{PortfolioAnalytics} framework to estimate solutions to constrained optimization problems is implemented in such a way that the moments of the returns are set once for use in lower level optimization functions. The \code{set.portfolio.moments} function computes the first, second, third, and fourth moments depending on the objective function(s) in the \code{portfolio} object. For example, if the third and fourth moments do not need to be calculated for a given objective, then \code{set.portfolio.moments} will try to detect this and not compute those moments. Currently, \code{set.portfolio.moments} implements methods to compute moments based on sample estimates, higher moments from fitting a statistical factor model based on the work of Kris Boudt, the Black Litterman model, and the Fully Flexible Framework based on the work of Attilio Meucci (NEED REFERENCE HERE). See the Custom Moment and Objective Functions vignette for a more detailed description and examples. 
 }
 
 \section{Charts and Graphs}{
@@ -90,7 +90,7 @@
 }
 
 \section{Demos}{
-\kdb{PortfolioAnalytics} contains a comprehensive collection of demos to demonstrate the functionality from very basic optimization problems such as estimating the solution to a minimum variance portfolio to more complex optimization problems with custom moment and objective functions.
+\kbd{PortfolioAnalytics} contains a comprehensive collection of demos to demonstrate the functionality from very basic optimization problems such as estimating the solution to a minimum variance portfolio to more complex optimization problems with custom moment and objective functions.
 }
 
 \section{Vignettes}{

Modified: pkg/PortfolioAnalytics/vignettes/PA.bib
===================================================================
--- pkg/PortfolioAnalytics/vignettes/PA.bib	2014-08-10 15:30:38 UTC (rev 3504)
+++ pkg/PortfolioAnalytics/vignettes/PA.bib	2014-08-11 02:39:12 UTC (rev 3505)
@@ -431,4 +431,33 @@
   author = {Scherer, Bernd. and Martin, Douglas},
   owner = {brian},
   timestamp = {2007.08.19}
-}
\ No newline at end of file
+}
+
+ at ARTICLE{Boudt2014,
+  author = {Boudt, Kris and Lu, Wanbo and Peeters, Benedict},
+  title = {Higher Order Comoments of Multifactor Models and Asset Allocation},
+  month = {June},
+  year = {2014},
+  url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2409603}
+}
+
+ at ARTICLE{Meucci2008,
+  author = {Meucci, Attilio},
+  title = {Fully Flexible Views: Theory and Practice},
+  journal = {Journal of Risk},
+  year = {2008},
+  volume = {21},
+  pages = {97-102},
+  number = {10},
+  url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1213325}
+}
+
+ at ARTICLE{MeucciBL2008,
+  author = {Meucci, Attilio},
+  title = {The Black-Litterman Approach: Original Model and Extensions},
+  journal = {Journal of Risk},
+  month = {August},
+  year = {2008},
+  url = {http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1117574}
+}
+

Modified: pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.Rnw
===================================================================
--- pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.Rnw	2014-08-10 15:30:38 UTC (rev 3504)
+++ pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.Rnw	2014-08-11 02:39:12 UTC (rev 3505)
@@ -37,7 +37,6 @@
 % \VignetteIndexEntry{Custom Moment and Objective Functions}
 
 \begin{document}
-\SweaveOpts{concordance=TRUE}
 
 \title{Custom Moment and Objective Functions}
 \author{Ross Bennett}
@@ -73,7 +72,7 @@
 @
 
 \section{Setting the Portfolio Moments}
-The PortfolioAnalytics framework to estimate solutions to constrained optimization problems is implemented in such a way that the moments of the returns are calculated only once and then used in lower level optimization functions. The \code{set.portfolio.moments} function computes the first, second, third, and fourth moments depending on the objective function(s) in the \code{portfolio} object. For example, if the third and fourth moments do not need to be calculated for a given objective, then \code{set.portfolio.moments} will try to detect this and not compute those moments. Currently, \code{set.portfolio.moments} implements methods to compute moments based on sample estimates, higher moments from fitting a statistical factor model based on the work of Kris Boudt, the Black Litterman model, and the Fully Flexible Framework based on the work of Attilio Meucci (NEED REFERENCE HERE).
+The PortfolioAnalytics framework to estimate solutions to constrained optimization problems is implemented in such a way that the moments of the returns are calculated only once and then used in lower level optimization functions. The \code{set.portfolio.moments} function computes the first, second, third, and fourth moments depending on the objective function(s) in the \code{portfolio} object. For example, if the third and fourth moments do not need to be calculated for a given objective, then \code{set.portfolio.moments} will try to detect this and not compute those moments. Currently, \code{set.portfolio.moments} implements methods to compute moments based on sample estimates, higher moments from fitting a statistical factor model based on the work of Kris Boudt \citep{Boudt2014}, the Black Litterman model \citep{MeucciBL2008}, and the Fully Flexible Framework based on the work of Attilio Meucci \citep{Meucci2008}.
 
 <<tidy=FALSE>>=
 # Construct initial portfolio with basic constraints.
@@ -186,7 +185,7 @@
 opt.pasd
 @
 
-We now consider an example with a more complicated objective function. Our objective to maximize the fourth order expansion of the Constant Relative Risk Aversion (CRRA) expected utility function as in the Boudt paper and Martellini paper (NEED REFERENCE).
+We now consider an example with a more complicated objective function. Our objective to maximize the fourth order expansion of the Constant Relative Risk Aversion (CRRA) expected utility function as in \citep{Boudt2014}.
 
 \begin{equation*}
 EU_{\lambda}(w) = - \frac{\lambda}{2} m_{(2)}(w) +
@@ -247,4 +246,6 @@
 
 TODO: add content to concluding paragraph
 
+\bibliography{PA}
+
 \end{document}

Modified: pkg/PortfolioAnalytics/vignettes/custom_moments_objectives.pdf
===================================================================
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