[Returnanalytics-commits] r3439 - pkg/PortfolioAnalytics/sandbox

[noreply at r-forge.r-project.org]

Author: rossbennett34
Date: 2014-06-25 00:26:12 +0200 (Wed, 25 Jun 2014)
New Revision: 3439

Added:
   pkg/PortfolioAnalytics/sandbox/scriptFFV.R
Log:
Adding basic fully flexible views script

Added: pkg/PortfolioAnalytics/sandbox/scriptFFV.R
===================================================================
--- pkg/PortfolioAnalytics/sandbox/scriptFFV.R	                        (rev 0)
+++ pkg/PortfolioAnalytics/sandbox/scriptFFV.R	2014-06-24 22:26:12 UTC (rev 3439)
@@ -0,0 +1,51 @@
+library(PortfolioAnalytics)
+data(edhec)
+R <- edhec[,1:5]
+
+# compute the probabilities
+probs <- rep(1 / nrow(R), nrow(R))
+# probabilities should always sum to 1
+sum(probs)
+
+# suppose that I express a bearish view on R[,1] - R[,2]
+# lambda is the ad-hoc multiplier
+# Meucci recommends -2 (very bearish), -1 (bearish), 1 (bullish), 2 (very bullish)
+lambda <- -2
+V <- coredata(R[,1] - R[,2])
+m <- mean(V)
+s <- sd(V)
+b <- matrix(m + lambda * s, 1)
+
+# set up matrix for equality constraints
+# constrain such that probabilities sum to 1
+Aeq <- matrix(1, nrow=1, ncol=nrow(R))
+beq <- matrix(1, 1, 1)
+
+# set up matrix for inequality constraints
+A <- t(V)
+
+# Compute posterior probabilities
+# The EntryProg optimization handles inequality constraints as A < b
+# If I hav 
+posterior_probs <- Meucci::EntropyProg(probs, A, b, Aeq, beq)$p_
+dim(posterior_probs)
+sum(posterior_probs)
+
+# why do the probs equal the posterior probs?
+all.equal(as.numeric(posterior_probs), probs)
+
+# Now I have my posterior probabilities
+# What is a general approach I can use for any arbitrary optimization
+all.equal(as.numeric(t(coredata(R)) %*% posterior_probs),as.numeric(matrix(colMeans(R), ncol=1)))
+
+# This is pretty close to sample cov
+Exps <- t(R) %*% posterior_probs
+Scnd_Mom = t(R) %*% (R * (posterior_probs %*% matrix( 1,1,ncol(R)) ) )
+Scnd_Mom = ( Scnd_Mom + t(Scnd_Mom) ) / 2
+Covs = Scnd_Mom - Exps %*% t(Exps)
+Covs
+cov(R)
+
+
+all.equal(coredata(R[,1] - R[,2]), A, check.attributes=FALSE)
+