(Chapman & Hall/CRC The R Series) 1st Edition
by Jonathan K. Regenstein Jr. (Author)
Reproducible Finance with R: Code Flows and Shiny Apps for Portfolio Analysis
is a unique introduction to data science for investment management that
explores the three major R/finance coding paradigms, emphasizes data
visualization, and explains how to build a cohesive suite of functioning
Shiny applications. The full source code, asset price data and live
Shiny applications are available at reproduciblefinance.com. The ideal
reader works in finance or wants to work in finance and has a desire to
learn R code and Shiny through simple, yet practical real-world
examples.
The book begins with the first step in data science:
importing and wrangling data, which in the investment context means
importing asset prices, converting to returns, and constructing a
portfolio. The next section covers risk and tackles descriptive
statistics such as standard deviation, skewness, kurtosis, and their
rolling histories. The third section focuses on portfolio theory,
analyzing the Sharpe Ratio, CAPM, and Fama French models. The book
concludes with applications for finding individual asset contribution to
risk and for running Monte Carlo simulations. For each of these tasks,
the three major coding paradigms are explored and the work is wrapped
into interactive Shiny dashboards.
