[Returnanalytics-commits] r2791 - pkg/PerformanceAnalytics/sandbox/pulkit/week7

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

Author: pulkit
Date: 2013-08-15 16:40:04 +0200 (Thu, 15 Aug 2013)
New Revision: 2791

Modified:
   pkg/PerformanceAnalytics/sandbox/pulkit/week7/ExtremeDrawdown.R
Log:
editing GPD for drawdowns

Modified: pkg/PerformanceAnalytics/sandbox/pulkit/week7/ExtremeDrawdown.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/pulkit/week7/ExtremeDrawdown.R	2013-08-15 10:30:02 UTC (rev 2790)
+++ pkg/PerformanceAnalytics/sandbox/pulkit/week7/ExtremeDrawdown.R	2013-08-15 14:40:04 UTC (rev 2791)
@@ -8,7 +8,7 @@
 #'
 #' Modified Generalized Pareto Distribution is given by the following formula
 #'
-#' \deqn{G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m^\gamma}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m^\gamma}{\psi}}, if \eta = 0,\end{array}}
+#' \dqeqn{G_{\eta}(m) = \begin{array}{l} 1-(1+\eta\frac{m^\gamma}{\psi})^(-1/\eta), if \eta \neq 0 \\ 1- e^{-frac{m^\gamma}{\psi}}, if \eta = 0,\end{array}}
 #'
 #' Here \eqn{\gamma{\epsilon}R} is the modifying parameter. When \eqn{\gamma<1} the corresponding densities are
 #' strictly decreasing with heavier tail; the GDP is recovered by setting \eqn{\gamma = 1} .\eqn{\gamma \textgreater 1}
@@ -27,7 +27,7 @@
 #'
 #'
 #' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset return 
-#' @param type The type of distribution "gpd","pd","weibull","exponential"
+#' @param type The type of distribution "gpd","pd","weibull"
 #' @param threshold The threshold beyond which the drawdowns have to be modelled
 #' 
 #'@references
@@ -35,14 +35,28 @@
 #'Available at SSRN: http://ssrn.com/abstract=477322 or http://dx.doi.org/10.2139/ssrn.477322.
 #'
 #'
-DrawdownGPD<-function(R,type=c("gpd","pd","weibull","exponential"),threshold=0.90){
+DrawdownGPD<-function(R,type=c("gpd","pd","weibull"),threshold=0.90){
     x = checkData(R)
     columns = ncol(R)
     columnnames = colnames(R)
     type = type[1]
     dr = -Drawdowns(R)
     dr_sorted = sort(as.vector(dr))
-    data = dr_sorted[0.9*nrow(R):nrow(r)]
+    data = dr_sorted[(0.9*nrow(R)):nrow(R)]
+    if(type=="gpd"){
+        gpd = fitgpd(data)
+        return(gpd)
+    }
+    if(type=="wiebull"){
+        weibull = fitdistr(data,"weibull")
+        return(weibull)
+    }
+    if(type=="pd"){
+        scale = min(data)
+        shape = length(data)/(sum(log(data))-length(data)*log(a))
+    }
+    
+
 }