[Returnanalytics-commits] r2719 - pkg/PerformanceAnalytics/sandbox/pulkit/week6

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

Author: pulkit
Date: 2013-08-05 15:56:28 +0200 (Mon, 05 Aug 2013)
New Revision: 2719

Added:
   pkg/PerformanceAnalytics/sandbox/pulkit/week6/Drawdownalpha.R
Modified:
   pkg/PerformanceAnalytics/sandbox/pulkit/week6/DrawdownBeta.R
Log:
Added files for alpha drawdown

Modified: pkg/PerformanceAnalytics/sandbox/pulkit/week6/DrawdownBeta.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/week6/DrawdownBeta.R	2013-08-05 10:51:30 UTC (rev 2718)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/week6/DrawdownBeta.R	2013-08-05 13:56:28 UTC (rev 2719)
@@ -40,7 +40,7 @@
 #'
 #'@examples
 #'
-#'BetaDrawdown(edhec[,1],edhec[,2]) #expected value 
+#'BetaDrawdown(edhec[,1],edhec[,2]) #expected value 0.5390431
 
 BetaDrawdown<-function(R,Rm,h=0,p=0.95,weights=NULL,geometric=TRUE,...){
 
@@ -82,7 +82,18 @@
             }
             else q=c(q,0)
         }
-        beta_dd = sum((as.numeric(x[which(cumul_xm==max(cumul_xm))])-x)*q)/CDaR(Rm,p=p)
+        boolean = (cummax(cumul_xm)==cumul_xm)
+        index = NULL
+        for(j in 1:nrow(Rm)){
+            if(boolean[j] == TRUE){
+                index = c(index,j)
+                b = j
+            }
+            else{
+                index = c(index,b)
+            }
+        }
+        beta_dd = sum((as.numeric(x[index])-x)*q)/CDaR(Rm,p=p)
         return(beta_dd)
     }
 
@@ -99,7 +110,6 @@
     if(columns==1){
         return(beta)
     }
-    print(beta)
     colnames(beta) = columnnames
     rownames(beta) = paste("Drawdown Beta (p =",p*100,"%)")
     beta = reclass(beta,R)

Added: pkg/PerformanceAnalytics/sandbox/pulkit/week6/Drawdownalpha.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/week6/Drawdownalpha.R	                        (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/week6/Drawdownalpha.R	2013-08-05 13:56:28 UTC (rev 2719)
@@ -0,0 +1,71 @@
+#' @title
+#' Drawdown alpha
+#'
+#' @description
+#' Then the difference between the actual rate of return and the rate of
+#' return of the instrument estimated by \eqn{\beta_DD{w_T}} is called CDaR
+#' alpha and is given by
+#'
+#' \deqn{\alpha_DD = w_T - \beta_DD{w_T^M}}
+#'
+#' here \eqn{\beta_DD} is the beta drawdown. The code for beta drawdown can 
+#' be found here \code{BetaDrawdown}.
+#'
+#' Postive \eqn{\alpha_DD} implies that the instrument did better than it was
+#' predicted, and consequently, \eqn{\alpha_DD} can be used as a performance
+#' measure to rank instrument and to identify those that outperformed their 
+#' CAPM predictions
+#'
+#'
+#'@param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
+#'@param Rm Return series of the optimal portfolio an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
+#'@param p confidence level for calculation ,default(p=0.95)
+#'@param weights portfolio weighting vector, default NULL, see Details
+#' @param geometric utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns, default TRUE
+#'@param \dots any passthru variable
+#'@references
+#'Zabarankin, M., Pavlikov, K., and S. Uryasev. Capital Asset Pricing Model 
+#'(CAPM) with Drawdown Measure.Research Report 2012-9, ISE Dept., University 
+#'of Florida,September 2012.
+#'
+#'@examples
+#'
+#'
+AlphaDrawdown<-function(R,Rm,p=0.95,weights = NULL,geometric = TRUE,...){
+    # DESCRIPTION:
+    # This function calculates the drawdown alpha given the return series 
+    # and the optimal return series
+    # 
+    # INPUTS:
+    # The return series of the portfolio , the return series of the optimal portfolio
+    # The confidence level, the weights and the type of cumulative returns
+
+    # OUTPUT:
+    # The drawdown alpha is given as the output
+
+
+    # ERROR HANDLING !!
+    x = checkData(R)
+    xm = checkData(Rm)
+    beta = BetaDrawdown(R,Rm,p = p,weights=weights,geometric=geometric,...)
+    if(!is.null(weights)){
+        x = Returns.portfolio(R,weights)
+    }
+    if(geometric){
+        cumul_x = cumprod(x+1)-1
+        cumul_xm = cumprod(xm+1)-1
+    }
+    else{
+        cumul_x = cumsum(x)
+        cumul_xm = cumsum(xm)
+    }
+    x_expected = mean(cumul_x)
+    xm_expected = mean(cumul_xm)
+    alpha = x_expected - beta*xm_expected
+    return(alpha)
+}
+
+
+
+
+