[Returnanalytics-commits] r2535 - pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4

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

Author: shubhanm
Date: 2013-07-10 14:52:15 +0200 (Wed, 10 Jul 2013)
New Revision: 2535

Added:
   pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarNumberofObservations.R
Modified:
   pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarJames.R
Log:
Stage : Development

Replication of Fig 3 and 4 Arcar and Shane

Modified: pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarJames.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarJames.R	2013-07-10 10:48:30 UTC (rev 2534)
+++ pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarJames.R	2013-07-10 12:52:15 UTC (rev 2535)
@@ -40,11 +40,10 @@
       x = y[,column]
       mu = musig.ratio[ratio] *.01
       sig= .01
-      r <- matrix(0,T+1,n)  # matrix to hold stock path
+      r <- matrix(0,T+1,n)  # matrix to hold Asset Path
       r[1,] <- s0  
-      drawdown <- matrix(0,length(musig.ratio,n)
-      #  return(Ed)
-      
+      drawdown <- matrix(0,length(musig.ratio),n)
+  
       for(j in 1:n){
         for(i in 2:(T+1)){
           
@@ -86,6 +85,6 @@
 # This R package is distributed under the terms of the GNU Public License (GPL)
 # for full details see the file COPYING
 #
-# $Id: EMaxDDGBM
+# $Id: chart.ArcarJames
 #
 ###############################################################################

Added: pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarNumberofObservations.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarNumberofObservations.R	                        (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/Shubhankit/Week4/chart.ArcarNumberofObservations.R	2013-07-10 12:52:15 UTC (rev 2535)
@@ -0,0 +1,114 @@
+#' Expected Drawdown using Brownian Motion Assumptions
+#' 
+#' Works on the model specified by Maddon-Ismail
+#' 
+#' 
+#' 
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of
+#' asset returns
+
+#' @author R
+#' @keywords Expected Drawdown Using Brownian Motion Assumptions
+#'
+#' @export 
+chart.ArcarJames <-
+  function (R,digits =4)
+  {# @author 
+    
+    # DESCRIPTION:
+    # Downside Risk Summary: Statistics and Stylized Facts
+    
+    # Inputs:
+    # R: a regular timeseries of returns (rather than prices)
+    # Output: Table of Estimated Drawdowns 
+    
+    y = checkData(R, method = "xts")
+    columns = ncol(y)
+    rows = nrow(y)
+    columnnames = colnames(y)
+    rownames = rownames(y)
+    T= 36;
+    n <- 1000
+    #tlength <- 36
+    musig.ratio=seq(-2,2,by=.1)
+    dt <- 1/T;
+    s0 <- 100;
+      for(column in 1:columns) {
+        x = y[,column]
+        mu = musig.ratio[ratio] *.01
+        sig= .01
+        r <- matrix(0,T+1,n)  # matrix to hold Asset Path
+        r[1,] <- s0  
+        drawdown <- matrix(0,length(musig.ratio),n)
+        # Generate k random walks across time {0, 1, ... , T}
+        T <- 100
+        k <- 250
+        initial.value <- 100
+        GetRandomWalk <- function() {
+          # Add a standard normal at each step
+          initial.value + c(0, cumsum(rnorm(T)))
+        
+        }
+        # Matrix of random walks
+        values <- replicate(k, GetRandomWalk())
+        # Create an empty plot
+        dev.new(height=8, width=12)
+        plot(0:T, rep(NA, T + 1), main=sprintf("%s Random Walks", k),
+             xlab="time", ylab="value",
+             ylim=100 + 4.5 * c(-1, 1) * sqrt(T))
+        mtext(sprintf("%s%s} with initial value of %s",
+                      "Across time {0, 1, ... , ", T, initial.value))
+        for (i in 1:k) {
+          lines(0:T, values[ , i], lwd=0.25)
+        }
+        for (sign in c(-1, 1)) {
+          curve(initial.value + sign * 1.96 * sqrt(x), from=0, to=T,
+                n=2*T, col="darkred", lty=2, lwd=1.5, add=TRUE)
+        }
+        legend("topright", "1.96 * sqrt(t)",
+               bty="n", lwd=1.5, lty=2, col="darkred")
+        
+        for(j in 1:n){
+          for(i in 2:(T+1)){
+            
+            dr <- mu*dt + sig*sqrt(dt)*rnorm(1,0,1)
+            r[i,j] <- r[i-1,j] + dr
+          }
+          drawdown[ratio,j] = maxDrawdown(r[ratio,j])
+        }
+        z = c((mu*100),
+              (sig*100),
+              ((mean(drawdown)*100)))
+        znames = c(
+          "Annual Returns in %",
+          "Std Devetions in %",
+          "Normalized Drawdown Drawdown in %"
+        )
+        if(column == 1) {
+          resultingtable = data.frame(Value = z, row.names = znames)
+        }
+        else {
+          nextcolumn = data.frame(Value = z, row.names = znames)
+          resultingtable = cbind(resultingtable, nextcolumn)
+        }
+      }
+    
+    colnames(resultingtable) = columnnames
+    ans = base::round(resultingtable, digits)
+    ans
+    t <- seq(0, T, dt)
+    matplot(t, r[1,1:T], type="l", lty=1, main="Short Rate Paths", ylab="rt")
+    
+  }
+
+###############################################################################
+# R (http://r-project.org/) 
+#
+# Copyright (c) 2004-2013 
+#
+# This R package is distributed under the terms of the GNU Public License (GPL)
+# for full details see the file COPYING
+#
+# $Id: chart.ArcarNumberofObservations
+#
+###############################################################################