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Quantitative Finance applications in R - 8

The latest in a series by Daniel Hanson Introduction Correlations between holdings in a portfolio are of course a key component in financial risk management. Borrowing a tool common in fields such as bioinformatics and genetics, we will look at how to use heat maps in R for visualizing correlations among financial returns, and examine behavior in both a stable and down market. While base R contains its own heatmap(.) function, the reader will likely find the heatmap.2(.) function in the R package gplots to be a bit more user friendly.  A very nicely written companion article entitled A short tutorial for decent heat maps in R (Sebastian Raschka, 2013), which covers more details and features, is available on the web; we will also refer to it in the discussion below. We will present the topic in the form of an example. Sample Data As in previous articles, we will make use of R packages Quandl and xts to acquire and manage our market data.  Here, in a simple example, we will use returns from the following global equity indices over the period 1998-01-05 to the present, and then examine correlations between them: S&P 500 (US)RUSSELL 2000 (US Small Cap)NIKKEI (Japan)HANG SENG (Hong Kong)DAX (Germany)CAC (France)KOSPI (Korea) First, we gather the index values and convert to returns: library(xts) library(Quandl)   my_start_date <- "1998-01-05" sp500.q >

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More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid