Book Image

RStudio for R Statistical Computing Cookbook

By : Andrea Cirillo
Book Image

RStudio for R Statistical Computing Cookbook

By: Andrea Cirillo

Overview of this book

The requirement of handling complex datasets, performing unprecedented statistical analysis, and providing real-time visualizations to businesses has concerned statisticians and analysts across the globe. RStudio is a useful and powerful tool for statistical analysis that harnesses the power of R for computational statistics, visualization, and data science, in an integrated development environment. This book is a collection of recipes that will help you learn and understand RStudio features so that you can effectively perform statistical analysis and reporting, code editing, and R development. The first few chapters will teach you how to set up your own data analysis project in RStudio, acquire data from different data sources, and manipulate and clean data for analysis and visualization purposes. You'll get hands-on with various data visualization methods using ggplot2, and you will create interactive and multidimensional visualizations with D3.js. Additional recipes will help you optimize your code; implement various statistical models to manage large datasets; perform text analysis and predictive analysis; and master time series analysis, machine learning, forecasting; and so on. In the final few chapters, you'll learn how to create reports from your analytical application with the full range of static and dynamic reporting tools that are available in RStudio so that you can effectively communicate results and even transform them into interactive web applications.
Table of Contents (15 chapters)
RStudio for R Statistical Computing Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Optimizing portfolio composition and maximising returns with the Portfolio Analytics package


Portfolio optimization is basically composed of four main steps:

  • Definition of portfolio components and past quotations

  • Definition of portfolio constrains, for instance, in term of diversification or maximum loss

  • Definition of objective to be optimized, usually in terms of returns

  • Definition of optimal percentage composition, given constraints and objectives

In this recipe, we will employ PortfolioAnaltycs and some other packages by joining together functionalities from different packages in order to provide a convenient and straightforward way to compose a financial portfolio.

The recipe workflow will be as follows:

  • Downloading stock prices

  • Definition of portfolio constraints and objectives

  • Actual portfolio optimization

Getting ready

In this recipe, we will join together powerful functions from different packages.

First of all, we will download stock quotations from Yahoo Finance by leveraging the quantmod...