# timelyportfolio / onepager with knitR.rnw Created February 19, 2013

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 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 \documentclass[nohyper,justified]{tufte-handout} %\documentclass{article} %\usepackage[absolute,showboxes]{textpos} \usepackage[absolute]{textpos} \usepackage{sidecap} %\usepackage{color} %\usepackage[usenames,dvipsnames,svgnames,table]{xcolor} \begin{document}   <>= opts_chunk\$set(concordance=TRUE) @     \begin{wide} \section{\Huge Performance Summary with knitR and R} {\Large Here is a little experiment with R and Sweave to produce a performance report. I have done some samples in the past, but I wanted to iterate through a couple more, especially to evaluate other options for what has been started in the PApages package. Of course, this text could be easily replaced with some commentary from a manager about opportunities, thoughts, or current allocation. A dashboard set of charts also might be very helpful here.}   \hrulefill   \end{wide}         <>= #do requires and set up environment for reporting require(xtable) require(ggplot2) require(directlabels) require(reshape2) require(latticeExtra) require(quantmod) require(PerformanceAnalytics) data(managers) #get xts in df form so that we can melt with the reshape package #will use just manager 1, sp500, and 10y treasury managers <- managers[,c(1,8,9)] #add 0 at beginning so cumulative returns start at 1 #also cumulative will match up datewise with returns managers <- as.xts(rbind(rep(0,NCOL(managers)),coredata(managers)), order.by=c(as.Date(format(index(managers)[1],"%Y-%m-01"))-1,index(managers))) managers.df <- as.data.frame(cbind(index(managers),coredata(managers)),stringsAsFactors=FALSE) #melt data which puts in a form that lattice and ggplot enjoy managers.melt <- melt(managers.df,id.vars=1) colnames(managers.melt) <- c("date","account","return") managers.melt[,1] <- as.Date(managers.melt[,1])   #get cumulative returns starting at 1 managers.cumul <- as.xts( apply(managers+1,MARGIN=2,FUN=cumprod), #add end of first month to accommodate the 1 that we add order.by=index(managers)) managers.cumul.df <- as.data.frame(cbind(index(managers.cumul), coredata(managers.cumul)), stringsAsFactors=FALSE) managers.cumul.melt <- melt(managers.cumul.df,id.vars=1) colnames(managers.cumul.melt) <- c("date","account","return") managers.cumul.melt[,1] <- as.Date(managers.cumul.melt[,1])   #get rolling returns for 1y, 3y, 5y, since inception trailing <- table.TrailingPeriods(managers, periods=c(12,36,60,NROW(managers)),FUNCS=c("mean"),funcs.names=c("return")) trailing.df <- as.data.frame(cbind(c("1y","3y","5y","SinceIncep"), c(rep("return",4)), coredata(trailing)), stringsAsFactors=FALSE) trailing.melt <- melt(trailing.df,id.vars=1:2) colnames(trailing.melt) <- c("period","measure","account","return")   #function to get numbers in percent format #will use \\ to play well with tikz percent <- function(x, digits = 2, format = "f", ...) { paste(formatC(100 * x, format = format, digits = digits, ...), "%", sep = "") } @   \begin{textblock*}{105mm}(15mm,70mm) \begin{figure} \vspace{0pt} <>= charts.PerformanceSummary(managers, colorset=c(brewer.pal(9,"Blues")[6],brewer.pal(8,"Greys")[c(5,4)]), xlab=NULL) @ \end{figure} \end{textblock*}   \begin{textblock*}{75mm}(120mm,100mm) \small Cumulative returns offer one of the best methods to evaluate the ability of a manager to achieve long term returns. Ultimately, the cumulative return is often one of the primary objectives of our clients. \normalsize \newline \begin{figure} \vspace{0pt} <>= trailingtable <- apply(trailing,MARGIN=2,FUN=percent) rownames(trailingtable) <- c("1y","3y","5y",paste("Since Inception ",format(index(managers)[1],"%b %Y"))) print(xtable(trailingtable), floating=FALSE, scalebox=0.7) @ \end{figure} \end{textblock*}   \begin{textblock*}{75mm}(120mm,152mm) \small However, cumulative returns must also be evaluated with reference to the risks incurred to generate those returns. Below are multiple risk measures. We are most concerned with limiting drawdowns shown in the bottom left chart. \normalsize \newline \begin{figure} \vspace{0pt} <>= risktable <- table.DownsideRisk(managers) print(xtable(risktable), floating=FALSE, scalebox=0.6) @ \end{figure} \end{textblock*}   \end{document} 

Needs "require(RColorBrewer)"