Book Image

Mastering R for Quantitative Finance

Book Image

Mastering R for Quantitative Finance

Overview of this book

Table of Contents (20 chapters)
Mastering R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Collecting data


Building the required database could be one of the biggest challenges. Here, we do not only need dividend-adjusted price quotes but also financial statements data. Chapter 4, Big Data – Advanced Analytics described how to access some of the open data sources, but those rarely offer you all the required information in a package.

Another option might be to use professional financial data providers as a source. These platforms allow you to create tailor-made tables that can be exported to Microsoft Excel. For the sake of this chapter, we used a Bloomberg terminal. As a first step, we exported the data to Microsoft Excel.

Spreadsheets may be an excellent tool to build a database of data collected from different sources. No matter how you got your data ready on a spreadsheet, you need to notice that due to the changing output formats (xls, xlsx, xlsm, xlsb) and the advanced formatting features (for example, merging cells), this is not the best form to feed R with your data. Instead...