In this chapter, we applied R to access data from open sources and perform various analyses on large datasets. The examples presented here aimed to be a practical guide to empirical researchers who handle a large amount of data.

First, we introduced useful methods for open source data integration. R has powerful options to directly access data for financial analysis without any prior data-management requirement. Second, we discussed how to handle big data in an R environment. Although R has fundamental limitations in handling large datasets and performing computationally intensive analyses and simulations, we introduced specific tools and packages that can bridge this gap. We presented two examples on how to perform K-means clustering and how to fit linear regression models on big data. This is the last chapter of the first part in this book. Next we will look at FX derivatives.