[Returnanalytics-commits] r2145 - in pkg/PerformanceAnalytics/sandbox/Meucci: R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Jul 11 19:56:30 CEST 2012
Author: braverock
Date: 2012-07-11 19:56:29 +0200 (Wed, 11 Jul 2012)
New Revision: 2145
Removed:
pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd
Modified:
pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R
pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R
pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/robustBayesianPortfolioOptimization.Rd
pkg/PerformanceAnalytics/sandbox/Meucci/man/std.Rd
Log:
- changes to roxygen comments and a few manual edits to .Rd files so documentation will compile, more to do here.
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/DetectOutliersviaMVE.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -46,28 +46,33 @@
#' Compute the minimum volume ellipsoid for a given (multi-variate) time-series
#'
#' Function computes the minimum volume ellipsoid for a given time series
+#'
#' via the expectations-minimization algorithm
-#' The location and scatter parameters that define the ellipsoid are
-#' multivariate high-breakdown estimators of location and scatter
-#'
-#' @param data a matrix time-series of data. Each row is a observation (date). Each column is an asset
-#' @return list a list with
-#' MVE_Location a numeric with the location parameter of minimum volume ellipsoid
-#' MVE_Dispersion a numeric with the covariance matrix of the minimum volume ellipsoid
-#' \deqn { w_{t} = \frac{1}{T} , t = 1,...,T
+#'
+#' \deqn{ w_{t} = \frac{1}{T} , t = 1,...,T
#' \\ m \equiv \frac{1}{ \sum_{s=1}^T w_{s} } \sum_{t=1}^T w_{t} x_{t}
#' \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big) \big(x_{t} - m\big)'
#' \\ Ma_{t}^{2} \equiv \big(x-m\big)' S^{-1} \big(x-m\big), t=1,...,T
#' \\ w_{t} \mapsto w_{t} Ma_{t}^{2}
#' \\ U = \big(x_{1}' - \hat{E}',...,x_{T}' - \hat{E}' \big)
#' \\ \hat{Cov} \equiv \frac{1}{T} U'U }
+#'
+#' The location and scatter parameters that define the ellipsoid are
+#' multivariate high-breakdown estimators of location and scatter
+#'
+#' @param data a matrix time-series of data. Each row is a observation (date). Each column is an asset
#' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
+#' @return list a list with
+#' MVE_Location a numeric with the location parameter of minimum volume ellipsoid
+#' MVE_Dispersion a numeric with the covariance matrix of the minimum volume ellipsoid
+#'
#' @references
-#' \url{http://www.symmys.com/sites/default/files/Risk%20and%20Asset%20Allocation%20-%20Springer%20Quantitative%20Finance%20-%20Estimation.pdf}
+#' \url{http://www.symmys.com/sites/default/files/Risk\%20and\%20Asset\%20Allocation\%20-\%20Springer\%20Quantitative\%20Finance\%20-\%20Estimation.pdf}
#' See Sec. 4.6.1 of "Risk and Asset Allocation" - Springer (2005), by A. Meucci
#' for the theory and the routine implemented below
#' See Meucci script for "ComputeMVE.m"
#' @export
+#'
ComputeMVE = function ( data )
{
library( matlab )
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/EntropyProg.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -31,7 +31,7 @@
#' p_ revised probabilities based on entropy pooling
#' optimizationPerformance a list with status of optimization, value, number of iterations and sum of probabilities.
#' @export
-#' \deqn { \tilde{p} \equiv argmin_{Fx \leq f, Hx \equiv h} \big\{ \sum_1^J x_{j} \big(ln \big( x_{j} \big) - ln \big( p_{j} \big) \big) \big\}
+#' \deqn{ \tilde{p} \equiv argmin_{Fx \leq f, Hx \equiv h} \big\{ \sum_1^J x_{j} \big(ln \big( x_{j} \big) - ln \big( p_{j} \big) \big) \big\}
#' \\ \ell \big(x, \lambda, \nu \big) \equiv x' \big(ln \big(x\big) - ln \big(p\big) \big) + \lambda' \big(Fx - f\big) + \nu' \big(Hx - h\big)}
#' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
#' @references
@@ -188,13 +188,13 @@
#' @param S_G a numeric with the expectation associated with the covariance of the linear combination GX
#'
#' @return a list with
-#' M_ a numeric vector with the full-confidence posterior distribution of Mu
-#' S_ a covariance matrix with the full-confidence posterior distribution of Sigma
+#' M_ a numeric vector with the full-confidence posterior distribution of \Mu
+#' S_ a covariance matrix with the full-confidence posterior distribution of \Sigma
#'
#' @references
#' \url{http://www.symmys.com}
#' \url{http://ssrn.com/abstract=1213325}
-#' \deqn { \tilde{ \mu } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q' \big)}^{-1} \big( \tilde{\mu}_{Q} - Q \mu \big),
+#' \deqn{ \tilde{ \mu } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q' \big)}^{-1} \big( \tilde{\mu}_{Q} - Q \mu \big),
#' \\ \tilde{ \Sigma } \equiv \Sigma + \Sigma G' \big({\big(G \Sigma G' \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma G' \big)}^{-1} - {\big(G \Sigma G' \big)}^{-1} \big) G \Sigma }
#' A. Meucci - "Fully Flexible Views: Theory and Practice". See formula (21) and (22) on page 7
#' See Meucci script Prior2Posterior.m attached to Entropy Pooling Paper
@@ -256,4 +256,4 @@
barplot( f , x , 1 )
return( list( f = f , x = x ) )
-}
\ No newline at end of file
+}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/FullyFlexibleBayesNets.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,9 +1,12 @@
-# Input views
-# statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g. {[2 3] [1 3 5]})
-# optional conditional statement: View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g. {[1]})
-# amount of stress is quantified as Prob(statement) <= View(k).v if View(k).sgn = 1;
-# Prob(statement) >= View(k).v if View(k).sgn = -1;
-# confidence in stress is quantified in View(k).c in (0,1)
+#' Input conditional views
+#'
+#' statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g. {[2 3] [1 3 5]})
+#' optional conditional statement: View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g. {[1]})
+#' amount of stress is quantified as Prob(statement) <= View(k).v if View(k).sgn = 1;
+#' Prob(statement) >= View(k).v if View(k).sgn = -1;
+#'
+#' confidence in stress is quantified in View(k).c in (0,1)
+#'
#' @param View TBD
#' @param X TBD
#'
@@ -11,6 +14,7 @@
#' @return b TBD
#' @return g TBD
#' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
+#' @export
CondProbViews = function( View , X )
{
# initialize parameters
@@ -64,6 +68,7 @@
return( list( A = A , b = b , g = g ) )
}
+#' tweak a matrix
#' @param A matrix A consisting of inequality constraints ( Ax <= b )
#' @param b matrix b consisting of inequality constraint vector b ( Ax <= b )
#' @param g TODO: TBD
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/InvariantProjection.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,11 +1,16 @@
#' Transforms the first n raw moments into the first n central moments
#'
-#' step 6 of projection process: compute multi-period central moments. Note the first central moment defined as expectation.
+#' step 6 of projection process:
+#'
+#' compute multi-period central moments.
+#'
+#' Note the first central moment defined as expectation.
#'
+#' #' \deqn{\tilde{ \mu } ^ {\big(n\big)} _{X} \equiv E \big\{ X^{n} \big\},
+#' \\ \mu ^{ \big(n\big) }_{X} \equiv \sum_0^{n-1} \big(-1\big)^{n-k} \mu ^{n-k}_{X} \tilde{ \mu }^{k}_{X} + \tilde{ \mu }_{X}^{n} }
+#'
#' @param mu_ the raw (multi-period) non-central moment of Y-t
#' @return mu (multi-period) central moment of Y-t
-#' \deqn {\tilde{ \mu } ^ {\big(n\big)} _{X} \equiv E \big\{ X^{n} \big\},
-#' \\ \mu ^{ \big(n\big) }_{X} \equiv \sum_0^{n-1} \big(-1\big)^{n-k} \mu ^{n-k}_{X} \tilde{ \mu }^{k}_{X} + \tilde{ \mu }_{X}^{n} }
#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
#' @references
#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management". See page 9
@@ -30,12 +35,20 @@
#' Transforms cumulants of Y-t into raw moments
#'
-#' step 5 of the projection process: From the cumulants of Y we compute the raw non-central moments of Y
+#' step 5 of the projection process:
+#'
+#' From the cumulants of Y we compute the raw non-central moments of Y
+#'
#' We do so recursively by the identity in formula (24) which follows from applying (21) and re-arranging terms
#'
+#' \deqn{ \tilde{ \mu } ^{ \big(n\big) }_{Y}
+#' \\ \equiv \kappa^{ \big(n\big) }_{Y} + \sum_{k=1}^{n-1} %BPremoved $ $^{n-1}
+#' C_{k-1}
+#' \\ \kappa_{Y}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{Y} }
+#'
#' @param ka cumulants of Y
#' @return mu_ the raw non-central moments of Y
-#' \deqn {\tilde{ \mu } ^{ \big(n\big) }_{Y} \equiv \kappa^{ \big(n\big) }_{Y} + \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{Y}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{Y} }
+#'
#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
#' @references
#' A. Meucci - "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics" - formula (24)
@@ -59,13 +72,16 @@
#' Transforms raw moments into cumulants
#'
#' Step 3 of the projection process: From the non-central moments of X-t, we compute the cumulants.
+#'
+#'
#' This process follows from the Taylor approximations for any small z and ln(1+x)~x for any small x,
#' and from the definition of the first cumulant in (17). The we apply recursively the identity
#' in formula (21). See Kendall and Stuart (1969)
#'
+#' \deqn{ \kappa^{ \big(n\big) }_{X} \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} - \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{X}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
+#'
#' @param mu_ non-central moments of the invariant X-t
#' @return ka cumulants of X-t
-#' \deqn { \kappa^{ \big(n\big) }_{X} \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} - \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{X}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
#' @references
#' A. Meucci - "Annualization and General Projection of Skewness, Kurtosis and All Summary Statistics" - formula (21)
@@ -92,11 +108,13 @@
#' step 2 of projection process: From the central moments of step 1, we compute the non-central moments. To do so we start
#' with the first non-central moment and apply recursively an identity (formula 20)
#'
+#' \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
+#' \\ \tilde{ \mu }^{ \big(n\big) }_{X} \equiv \mu ^{n}_{X} \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1} \mu ^{n-k}_{X} \tilde{ \mu }^{\big(k\big)}_{X} }
+
#' @param mu a vector of central moments
#' @return mu_ a vector of non-central moments
#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
-#' \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
-#' \\ \tilde{ \mu }^{ \big(n\big) }_{X} \equiv \mu ^{n}_{X} \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1} \mu ^{n-k}_{X} \tilde{ \mu }^{\big(k\big)}_{X} }
+#' @references
#' A. Meucci - "Exercises in Advanced Risk and Portfolio Management". See page 10.
#' Symmys site containing original MATLAB source code \url{http://www.symmys.com}
@@ -154,7 +172,7 @@
#' Calculates the population standard deviation
#'
-#' Calculates the population standard deviaiton dividing by 'n' instead of 'n-1' equivalent to Matlab
+#' Calculates the population standard deviation dividing by 'n' instead of 'n-1' equivalent to Matlab
#'
#' @param x a generic numeric vector
#' @return std a numeric with the population standard deviaiton of the generic numeric
@@ -162,7 +180,9 @@
#' @author Ram Ahluwalia \email{rahluwalia@@gmail.com}
std = function( x ) { ( sum( ( x - mean( x ) ) ^ 2 ) / length( x ) ) ^.5 }
-#' Generate arbitrary distribution of a shifted-lognormal invariant: X-t + a ~ LogN(m,s^2) (formula 14)
+#' Generate arbitrary distribution of a shifted-lognormal invariant
+#'
+#' %\deqn{X-t + a ~ LogN(m,s^2)} (formula 14)
#'
#' @param J a numeric with the number of scenarios
#' @param a a numeric with the location shift parameter. Mean of distribution will be exp(a)
@@ -178,4 +198,5 @@
X = a + exp( m + s * Z ) # a Jx1 numeric vector
return( X = X )
-}
\ No newline at end of file
+}
+
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/Prior2Posterior.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,3 +1,4 @@
+#' plot dists
#' @param X
#' @param p
#' @param Mu
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/RankingInformation.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -17,6 +17,7 @@
return( p )
}
+#' view the rankings
#' @param Lower a vector of indexes indicating which column is lower than the corresponding column number in Upper
#' @param Upper a vector of indexes indicating which column is lower than the corresponding column number in Upper
#' @export EntropyProg
@@ -48,7 +49,7 @@
return( p_ )
}
-#' Generates an efficient frontier based on the Meucci's Ranking Information version with the following inputs
+#' Generates an efficient frontier based on Meucci's Ranking Information version with the following inputs
#' @param X a matrix with the joint-scenario probabilities by asset (rows are joint-scenarios, columns are assets)
#' @param p a vector of probabilities associated with each scenario in matrix X
#' @param Options a list of options....TBD
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/RobustBayesianAllocation.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -185,7 +185,7 @@
#' @return cov_post a covariance matrix the confidence weighted posterior covariance matrix of asset returns blended from the prior and sample covariance matrix
#' @return time_post a numeric
#' @return nu_pst a numeric
-#' \deqn { T_{1} \equiv T_{0} + T
+#' \deqn{ T_{1} \equiv T_{0} + T
#' \\ \mu_{1} \equiv \frac{1}{ T_{1} } \big( T_{0} \mu_{0} + T \hat{ \mu } \big)
#' \\ \nu_{1} \equiv \nu_{0} + T
#' \\ \Sigma_{1} \equiv \big( \nu_{0} \Sigma_{0} + T \hat{ \Sigma } + \frac{ \big(\mu_{0} - \hat{\mu} \big) \big(\mu_{0} - \hat{\mu} \big)' }{ \big( \frac{1}{T} + \frac{1}{T_{0} } \big) }
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/R/logToArithmeticCovariance.R 2012-07-11 17:56:29 UTC (rev 2145)
@@ -6,7 +6,7 @@
#' @return a list containing two elements:
#' @return arithmeticMean a numeric containing the mean arithmetic returns
#' @return arithmeticCovariance a variance-covariance matrix in simple arithmetic return terms
-#' \deqn { M_{ \tau }^{i} = e^{ \mu ^{\tau} _{i} + \frac{1}{2} \Sigma^{ii} _{\tau} },
+#' \deqn{ M_{ \tau }^{i} = e^{ \mu ^{\tau} _{i} + \frac{1}{2} \Sigma^{ii} _{\tau} },
#' \\ S^{ij} = e^{ \mu ^{\tau} _{i} + \mu ^{\tau} _{j} + \frac{1}{2} \big(\Sigma^{ii} _{\tau} + \Sigma^{jj} _{\tau}\big) } \big(e^{\Sigma^{ij} _{\tau}} - 1\big) }
#' @author Ram Ahluwalia \email{ram@@wingedfootcapital.com}
#' @export
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Central2Raw.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -16,14 +16,18 @@
start with the first non-central moment and apply
recursively an identity (formula 20)
}
+\details{
+% \deqn{ \tilde{ \mu }^{ \big(1\big) }_{X} \equiv \mu^{\big(1\big)}_{X}
+%\\ \tilde{ \mu }^{ \big(n\big) }_{X}
+% \equiv \mu^{n}_{X} \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1}
+% \mu^{n-k}_{X} \tilde{ \mu }^{\big(k\big)}_{X} }
+}
\author{
- Ram Ahluwalia \email{rahluwalia at gmail.com} \deqn{ \tilde{
- \mu }^{ \big(1\big) }_{X} \equiv \mu ^{\big(1\big)}_{X}
- \\ \tilde{ \mu }^{ \big(n\big) }_{X} \equiv \mu ^{n}_{X}
- \sum_{k=0}^{n-1} \big(-1\big)^{n-k+1} \mu ^{n-k}_{X}
- \tilde{ \mu }^{\big(k\big)}_{X} } A. Meucci - "Exercises
- in Advanced Risk and Portfolio Management". See page 10.
- Symmys site containing original MATLAB source code
- \url{http://www.symmys.com}
+ Ram Ahluwalia \email{rahluwalia at gmail.com}
}
+\references{
+ A. Meucci - "Exercises in Advanced Risk and Portfolio
+ Management". See page 10. Symmys site containing original
+ MATLAB source code \url{http://www.symmys.com}
+}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/ComputeMVE.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -12,26 +12,32 @@
list a list with MVE_Location a numeric with the location
parameter of minimum volume ellipsoid MVE_Dispersion a
numeric with the covariance matrix of the minimum volume
- ellipsoid \deqn { w_{t} = \frac{1}{T} , t = 1,...,T \\ m
- \equiv \frac{1}{ \sum_{s=1}^T w_{s} } \sum_{t=1}^T w_{t}
- x_{t} \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big)
+ ellipsoid
+}
+\description{
+ Function computes the minimum volume ellipsoid for a
+ given time series
+}
+\details{
+ via the expectations-minimization algorithm
+
+ \deqn{ w_{t} = \frac{1}{T} , t = 1,...,T \\ m \equiv
+ \frac{1}{ \sum_{s=1}^T w_{s} } \sum_{t=1}^T w_{t} x_{t}
+ \\ S \equiv \sum_{t=1}^T w_{t} \big(x_{t} - m\big)
\big(x_{t} - m\big)' \\ Ma_{t}^{2} \equiv \big(x-m\big)'
S^{-1} \big(x-m\big), t=1,...,T \\ w_{t} \mapsto w_{t}
Ma_{t}^{2} \\ U = \big(x_{1}' - \hat{E}',...,x_{T}' -
\hat{E}' \big) \\ \hat{Cov} \equiv \frac{1}{T} U'U }
+
+ The location and scatter parameters that define the
+ ellipsoid are multivariate high-breakdown estimators of
+ location and scatter
}
-\description{
- Function computes the minimum volume ellipsoid for a
- given time series via the expectations-minimization
- algorithm The location and scatter parameters that define
- the ellipsoid are multivariate high-breakdown estimators
- of location and scatter
-}
\author{
Ram Ahluwalia \email{ram at wingedfootcapital.com}
}
\references{
- \url{http://www.symmys.com/sites/default/files/Risk%20and%20Asset%20Allocation%20-%20Springer%20Quantitative%20Finance%20-%20Estimation.pdf}
+ \url{http://www.symmys.com/sites/default/files/Risk\%20and\%20Asset\%20Allocation\%20-\%20Springer\%20Quantitative\%20Finance\%20-\%20Estimation.pdf}
See Sec. 4.6.1 of "Risk and Asset Allocation" - Springer
(2005), by A. Meucci for the theory and the routine
implemented below See Meucci script for "ComputeMVE.m"
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/CondProbViews.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
\name{CondProbViews}
\alias{CondProbViews}
+\title{Input conditional views}
\usage{
CondProbViews(View, X)
}
@@ -15,6 +16,17 @@
g TBD
}
+\description{
+ statement: View(k).Who (e.g. [1 3])= View(k).Equal (e.g.
+ {[2 3] [1 3 5]}) optional conditional statement:
+ View(k).Cond_Who (e.g. [2])= View(k).Cond_Equal (e.g.
+ {[1]}) amount of stress is quantified as Prob(statement)
+ <= View(k).v if View(k).sgn = 1; Prob(statement) >=
+ View(k).v if View(k).sgn = -1;
+}
+\details{
+ confidence in stress is quantified in View(k).c in (0,1)
+}
\author{
Ram Ahluwalia \email{ram at wingedfootcapital.com}
}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Cumul2Raw.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -8,17 +8,23 @@
\item{ka}{cumulants of Y}
}
\value{
- mu_ the raw non-central moments of Y \deqn {\tilde{ \mu }
- ^{ \big(n\big) }_{Y} \equiv \kappa^{ \big(n\big) }_{Y} +
- \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{Y}^{
- \big(k\big) } \tilde{ \mu } ^{n-k}_{Y} }
+ mu_ the raw non-central moments of Y
}
\description{
- step 5 of the projection process: From the cumulants of Y
- we compute the raw non-central moments of Y We do so
- recursively by the identity in formula (24) which follows
- from applying (21) and re-arranging terms
+ step 5 of the projection process:
}
+\details{
+ From the cumulants of Y we compute the raw non-central
+ moments of Y
+
+ We do so recursively by the identity in formula (24)
+ which follows from applying (21) and re-arranging terms
+
+ \deqn{ \tilde{ \mu } ^{ \big(n\big) }_{Y} \\ \equiv
+ \kappa^{ \big(n\big) }_{Y} + \sum_{k=1}^{n-1} % ^{n-1}
+ C_{k-1} \\ \kappa_{Y}^{ \big(k\big) } \tilde{ \mu }
+ ^{n-k}_{Y} }
+}
\author{
Ram Ahluwalia \email{rahluwalia at gmail.com}
}
Deleted: pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/EfficientFrontier.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,28 +0,0 @@
-\name{EfficientFrontier}
-\alias{EfficientFrontier}
-\usage{
- EfficientFrontier(X, p, Options)
-}
-\arguments{
- \item{X}{a matrix with the joint-scenario probabilities
- by asset (rows are joint-scenarios, columns are assets)}
-
- \item{p}{a vector of probabilities associated with each
- scenario in matrix X}
-
- \item{Options}{a list of options....TBD}
-}
-\value{
- A list with NumPortf efficient portfolios whos returns
- are equally spaced along the whole range of the efficient
- frontier Exps the NumPortf x 1 vector of expected returns
- for each asset Covs the NumPortf x N vector of security
- volatilities along the efficient frontier w the NumPortf
- x N matrix of compositions (security weights) for each
- portfolio along the efficient frontier e the NumPortf x 1
- matrix of expected returns for each portfolio along the
- efficient frontier s the NumPortf x 1 matrix of standard
- deviation of returns for each portfolio along the
- efficient frontier
-}
-
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/GenerateLogNormalDistribution.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,6 +1,6 @@
\name{GenerateLogNormalDistribution}
\alias{GenerateLogNormalDistribution}
-\title{Generate arbitrary distribution of a shifted-lognormal invariant: X-t + a ~ LogN(m,s^2) (formula 14)}
+\title{Generate arbitrary distribution of a shifted-lognormal invariant}
\usage{
GenerateLogNormalDistribution(J, a, m, s)
}
@@ -20,8 +20,7 @@
parameters J, a, m, and s where X = a + exp( m + s * Z )
}
\description{
- Generate arbitrary distribution of a shifted-lognormal
- invariant: X-t + a ~ LogN(m,s^2) (formula 14)
+ %\deqn{X-t + a ~ LogN(m,s^2)} (formula 14)
}
\author{
Ram Ahluwalia \email{rahluwalia at gmail.com}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/PartialConfidencePosterior.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -42,13 +42,13 @@
time_post a numeric
- nu_pst a numeric \deqn { T_{1} \equiv T_{0} + T \\
- \mu_{1} \equiv \frac{1}{ T_{1} } \big( T_{0} \mu_{0} + T
- \hat{ \mu } \big) \\ \nu_{1} \equiv \nu_{0} + T \\
- \Sigma_{1} \equiv \big( \nu_{0} \Sigma_{0} + T \hat{
- \Sigma } + \frac{ \big(\mu_{0} - \hat{\mu} \big)
- \big(\mu_{0} - \hat{\mu} \big)' }{ \big( \frac{1}{T} +
- \frac{1}{T_{0} } \big) }
+ nu_pst a numeric \deqn{ T_{1} \equiv T_{0} + T \\ \mu_{1}
+ \equiv \frac{1}{ T_{1} } \big( T_{0} \mu_{0} + T \hat{
+ \mu } \big) \\ \nu_{1} \equiv \nu_{0} + T \\ \Sigma_{1}
+ \equiv \big( \nu_{0} \Sigma_{0} + T \hat{ \Sigma } +
+ \frac{ \big(\mu_{0} - \hat{\mu} \big) \big(\mu_{0} -
+ \hat{\mu} \big)' }{ \big( \frac{1}{T} + \frac{1}{T_{0} }
+ \big) }
}
\description{
Constructs the partial confidence posterior based on
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/PlotDistributions.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
\name{PlotDistributions}
\alias{PlotDistributions}
+\title{plot dists}
\usage{
PlotDistributions(X, p, Mu, Sigma, p_, Mu_, Sigma_)
}
@@ -18,6 +19,9 @@
\item{Sigma_}{}
}
+\description{
+ plot dists
+}
\author{
Ram Ahluwalia \email{ram at wingedfootcapital.com}
}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Prior2Posterior.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -25,8 +25,8 @@
}
\value{
a list with M_ a numeric vector with the full-confidence
- posterior distribution of Mu S_ a covariance matrix with
- the full-confidence posterior distribution of Sigma
+ posterior distribution of \Mu S_ a covariance matrix with
+ the full-confidence posterior distribution of \Sigma
}
\description{
Calculate the full-confidence posterior distributions of
@@ -37,12 +37,12 @@
}
\references{
\url{http://www.symmys.com}
- \url{http://ssrn.com/abstract=1213325} \deqn { \tilde{
- \mu } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q'
- \big)}^{-1} \big( \tilde{\mu}_{Q} - Q \mu \big), \\
- \tilde{ \Sigma } \equiv \Sigma + \Sigma G' \big({\big(G
- \Sigma G' \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma
- G' \big)}^{-1} - {\big(G \Sigma G' \big)}^{-1} \big) G
+ \url{http://ssrn.com/abstract=1213325} \deqn{ \tilde{ \mu
+ } \equiv \mu + \Sigma Q' {\big(Q \Sigma Q' \big)}^{-1}
+ \big( \tilde{\mu}_{Q} - Q \mu \big), \\ \tilde{ \Sigma }
+ \equiv \Sigma + \Sigma G' \big({\big(G \Sigma G'
+ \big)}^{-1} \tilde{ \Sigma }_G {\big(G \Sigma G'
+ \big)}^{-1} - {\big(G \Sigma G' \big)}^{-1} \big) G
\Sigma } A. Meucci - "Fully Flexible Views: Theory and
Practice". See formula (21) and (22) on page 7 See Meucci
script Prior2Posterior.m attached to Entropy Pooling
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Central.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -9,17 +9,21 @@
Y-t}
}
\value{
- mu (multi-period) central moment of Y-t \deqn {\tilde{
- \mu } ^ {\big(n\big)} _{X} \equiv E \big\{ X^{n} \big\},
- \\ \mu ^{ \big(n\big) }_{X} \equiv \sum_0^{n-1}
- \big(-1\big)^{n-k} \mu ^{n-k}_{X} \tilde{ \mu }^{k}_{X} +
- \tilde{ \mu }_{X}^{n} }
+ mu (multi-period) central moment of Y-t
}
\description{
- step 6 of projection process: compute multi-period
- central moments. Note the first central moment defined as
- expectation.
+ step 6 of projection process:
}
+\details{
+ compute multi-period central moments.
+
+ Note the first central moment defined as expectation.
+
+% \deqn{\tilde{ \mu } ^ {\big(n\big)} _{X} \equiv E
+% \big\{ X^{n} \big\}, \\ \mu^{ \big(n\big) }_{X} \equiv
+% \sum_0^{n-1} \big{ -1 \big}^{n-k} \mu^{n-k}_{X} \tilde{
+% \mu }^{k}_{X} + \tilde{ \mu }_{X}^{n} }
+}
\author{
Ram Ahluwalia \email{rahluwalia at gmail.com}
}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Raw2Cumul.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -8,19 +8,23 @@
\item{mu_}{non-central moments of the invariant X-t}
}
\value{
- ka cumulants of X-t \deqn { \kappa^{ \big(n\big) }_{X}
- \equiv \tilde{ \mu } ^{ \big(n\big) }_{X} -
- \sum_{k=1}^{n-1} $^{n-1} C_{k-1}$ \kappa_{X}^{
- \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
+ ka cumulants of X-t
}
\description{
Step 3 of the projection process: From the non-central
- moments of X-t, we compute the cumulants. This process
- follows from the Taylor approximations for any small z
- and ln(1+x)~x for any small x, and from the definition of
- the first cumulant in (17). The we apply recursively the
- identity in formula (21). See Kendall and Stuart (1969)
+ moments of X-t, we compute the cumulants.
}
+\details{
+ This process follows from the Taylor approximations for
+ any small z and ln(1+x)~x for any small x, and from the
+ definition of the first cumulant in (17). The we apply
+ recursively the identity in formula (21). See Kendall and
+ Stuart (1969)
+
+% \deqn{ \kappa^{ \big(n\big) }_{X} \equiv \tilde{ \mu } ^{
+% \big(n\big) }_{X} - \sum_{k=1}^{n-1} $^{n-1} C_{k-1} %$
+% \kappa_{X}^{ \big(k\big) } \tilde{ \mu } ^{n-k}_{X} }
+}
\author{
Ram Ahluwalia \email{rahluwalia at gmail.com}
}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/StackedBarChart.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
\name{StackedBarChart}
\alias{StackedBarChart}
+\title{Generate a Stacked Bar Chart based on the frontier weights matrix}
\usage{
StackedBarChart(weightsMatrix)
}
@@ -9,4 +10,8 @@
\item{a}{string indicating the title of the chart}
}
+\description{
+ Generate a Stacked Bar Chart based on the frontier
+ weights matrix
+}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/Tweak.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
\name{Tweak}
\alias{Tweak}
+\title{tweak a matrix}
\usage{
Tweak(A, b, g)
}
@@ -15,6 +16,9 @@
\value{
db
}
+\description{
+ tweak a matrix
+}
\author{
Ram Ahluwalia \email{ram at wingedfootcapital.com}
}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/ViewRanking.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -1,5 +1,6 @@
\name{ViewRanking}
\alias{ViewRanking}
+\title{view the rankings}
\usage{
ViewRanking(X, p, Lower, Upper)
}
@@ -10,4 +11,7 @@
\item{Upper}{a vector of indexes indicating which column
is lower than the corresponding column number in Upper}
}
+\description{
+ view the rankings
+}
Modified: pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd 2012-07-10 02:39:12 UTC (rev 2144)
+++ pkg/PerformanceAnalytics/sandbox/Meucci/man/linreturn.Rd 2012-07-11 17:56:29 UTC (rev 2145)
@@ -17,7 +17,7 @@
returns
arithmeticCovariance a variance-covariance matrix in
- simple arithmetic return terms \deqn { M_{ \tau }^{i} =
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/returnanalytics -r 2145
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