Charting in R - Part I

The toughest step to doing things like quantitative analysis for trading and backtesting is to understand how to use the tools available in the market. The choices available are as follows:

1. Excel
2. R
3. Python
4.  C/C++

Excel allows you to see and manipulate data easily but you cannot see trend properly. For example, if you wish to chart data in Excel, this is what you will get:

This graph looks acceptable for simple presentation. But if you want to do analysis, you would want to be able to add a complex indicator easily. In Excel, you can only do that by manipulate all the data in excel and plot another graph on it. To do complex analysis of data it will be much better to do it with scripting API available in the market. If you know your stuff, you can do things pretty fast. But it takes a hell lot of effort to even get started. To illustrate the advantage of using API, the following is created using GOOGLE prices and R.

As someone who had tried both Python and R, my opinion is that the later is a better tool to do charting. So I documented some tips to get you started on R.

What you need to install
R(Here you will find the latest version but I am using version 2.15)
Quantmod (To quickly install, follow instruction here to download and install all that you need)

Once you are done, you can quickly load data with the following sample code (modified from code taken from here) and data.

Code:

library(quantmod)
require (zoo)
dataFile_strip2 <- "testinput.csv"
dataDir <- "C:/Users/Ken/Documents/R/CSV Data"
file2 <- paste(dataDir,"/",dataFile_strip2,sep="")
zz <- read.zoo(file2,header = TRUE,sep=",",index.column=1, format = "%d/%m/%Y %H:%M")
xx<- as.xts(zz)
chartSeries(xx)


testinput.csv:
DateTime,Close,High,Low,Open,Volume
12/08/2015 21:30:00,112.53,112.61,112.5,112.5,877727

Other Reference:
https://cran.r-project.org/web/packages/zoo/vignettes/zoo-read.pdf