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Mastering R for Quantitative Finance

You're reading from   Mastering R for Quantitative Finance Use R to optimize your trading strategy and build up your own risk management system

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Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781783552078
Length 362 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (15) Chapters Close

Preface 1. Time Series Analysis FREE CHAPTER 2. Factor Models 3. Forecasting Volume 4. Big Data – Advanced Analytics 5. FX Derivatives 6. Interest Rate Derivatives and Models 7. Exotic Options 8. Optimal Hedging 9. Fundamental Analysis 10. Technical Analysis, Neural Networks, and Logoptimal Portfolios 11. Asset and Liability Management 12. Capital Adequacy 13. Systemic Risks Index

Getting data from open sources

Extraction of financial time series or cross-sectional data from open sources is one of the challenges of any academic analysis. While several years ago, the accessibility of public data for financial analysis was very limited, in recent years, more and more open access databases are available, providing huge opportunities for quantitative analysts in any field.

In this section, we will present the Quandl and quantmod packages, two specific tools that can be used to seamlessly access and load financial data in the R environment. We will lead you through two examples to showcase how these tools can help financial analysts to integrate data directly from sources without any prior data management.

Quandl is an open source website for financial time series, indexing over millions of financial, economic, and social datasets from 500 sources. The Quandl package interacts directly with the Quandl API to offer data in a number of formats usable in R. Besides downloading...

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