Portfolio Construction and Optimization with R

Kyle Balkissoon

KKB Research and Development

2016-10-26

Introduction

At the end of this presentation you will know how to the following

Get Data
Process Data
Create Portfolio objectives
Optimize Portfolios
Analyse Portfolios
Case Study: Stance Equity

Get Data

Before we can do anything we need data, some good R libraries for getting data are:

library(Quandl) # see Quandl.com for more info
library(quantmod) #Has preconfigured api with yahoo info

##Quandl - Note requires assignment, type xts is xtensible time series
SPTSXComp=Quandl("YAHOO/INDEX_GSPTSE",type='xts')

##quantmod - assigns to object named GSPTSE - automatically in xts/zoo
 getSymbols("^GSPTSE")

A realistic case - US SP500 Sectors

symbol_list = c('XLF','XLE','XLU','XLK','XLB','XLP','XLY','XLI','XLV')

getSymbols(symbol_list, from = '1990-01-01')
getSymbols("SPY",from='1990-01-01')

Preprocess Data into Returns

library(PerformanceAnalytics)

securities_matrix = NULL
for( sym in symbol_list){
  securities_matrix = merge.xts(securities_matrix,
                     Return.calculate(Ad(get(paste(sym))),
                                                 method='discrete'))}
securities_matrix=securities_matrix[complete.cases(securities_matrix)]
SPYReturn=Return.calculate(Ad(SPY),method='discrete')

Introduction to PerformanceAnalytics

Library to compute many functions in return space
Used by hedge funds, proprietary trading firms, mutual funds, SMA's and banks
Robust tools for measuring portfolio and security performance with all the standard risk metrics.

Have a look at our data

chart.CumReturns(securities_matrix)