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Reproducible Finance with R (Chapman & Hall/CRC The R Series) 1st Edition

by Jonathan K. Regenstein (Author)

45 ratings

Part of: Chapman & Hall/CRC The R (66 books)

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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.

ISBN-10

1138484032
ISBN-13

978-1138484030
Edition

1st
Publisher

Chapman and Hall/CRC
Publication date

September 25, 2018
Language

English
Dimensions

6.14 x 0.56 x 9.21 inches
Print length

248 pages
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Editorial Reviews

Review

"There are two major selling points from my perspective. First, Shiny web applications are a new technology that is in high demand. It enables users to communicate data science (including financial analytics) to managers and executives. I believe this alone is a big benefit that separates this book from others. The second is that (he) takes a modern approach to using three different frameworks: xts, tidyverse, and tidyquant/tibbletime. This is refreshing because it shows that there are multiple ways to accomplish the same tasks, and it exposes the user to options that they otherwise might not have considered. Because of these two aspects, I believe that the market is for financial analysts that are seeking to learn these tools. The typical reader will have some knowledge of R (not a complete beginner) and will be hungry to use Shiny in their organization…I enjoyed reading it. I found the prose approachable and not overly technical or formal." ~Matt Dancho, Founder, Business Science, LLC

About the Author

Jonathan K. Regenstein, Jr. is the Director of Financial Services at RStudio. He studied international relations at Harvard and law at NYU, worked at JP Morgan, and did graduate work in political economy at Emory.

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Product details

Publisher ‏ : ‎ Chapman and Hall/CRC; 1st edition (September 25, 2018)
Language ‏ : ‎ English
Paperback ‏ : ‎ 248 pages
ISBN-10 ‏ : ‎ 1138484032
ISBN-13 ‏ : ‎ 978-1138484030
Item Weight ‏ : ‎ 1.01 pounds
Dimensions ‏ : ‎ 6.14 x 0.56 x 9.21 inches

Best Sellers Rank: #301,351 in Books (See Top 100 in Books)
- #165 in Business Investments
- #366 in Statistics (Books)
- #578 in Probability & Statistics (Books)

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CapRiskMan

Excellent Source for First Principles of R Finance

Reviewed in the United States on May 10, 2019

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The book covers basic concepts in Finance and deployment through Shiny in an easy to follow and comprehensive manner. How comprehensive? The author goes through great efforts to show three different ways (xts, tidyverse, and tidyquant/tibbletime) to implement each application. This enables the user to deploy a problem along their own workflow. As a comparative tool, the three methods provides insight into efficient code, a necessary condition when the data size expands. While the implementation is of introductory models in finance, it is easy for the knowledgeable reader to extend these first principles to more complex implementations. This should be the first book an aspiring financial analyst seeks, after having leaned the theory. Commendable for design and pedagogy.

4 people found this helpful

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Greg F

Very helpful

Reviewed in the United States on April 25, 2022

Verified Purchase

I'm an MBA candidate going into the financial services industry. I bought this book hoping to learn how to use my existing R knowledge to build interactive dashboards and more efficiently code up financial projects using existing packages. With how many packages are out there it can be difficult to know where to target effort. This book does an incredible job selecting and explaining packages and showing workflows through multiple lenses. It explains which functions are available from each package to accomplish the task at hand and lets the reader decide which lens to approach the project through while explaining the other lenses. Super helpful. Definitely worth the money.

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Tom McCrohan

Equity Research Perspective - Extremely valuable

Reviewed in the United States on January 28, 2019

Verified Purchase

An extremely valuable tool to apply the principals of portfolio management through the lens of the R programming language. R is a proven workhorse for data and financial analysis, and this book includes all the code needed to perform frequently used functions related to constructing an equity portfolio. I'm an early user of the R programming language and found this book easy to understand; the code related to CAPM and beta were extremely helpful. An invaluable resource for individuals with backgrounds in equity research with an interest in R. Should be required reading for anyone pursuing a CFA.

3 people found this helpful

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nadodi

Timeliness

Reviewed in the United States on October 18, 2019

Verified Purchase

Came in time and book is good.

One person found this helpful

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lis

An easy introduction to advance R topics

Reviewed in the United States on January 29, 2020

I am a major user of R an have used it to develop all kinds of complex analytics tasks with applications to finance.
R is a phenomenal language for data analytics, superior to Python in some important aspects. However, R adoption is challenged by the initial steep learning curve, given R's non traditional syntax. This is where books like this one can make a big difference. The book provides a very clear introduction to some advanced and practically useful applications of R for Portfolio Analysis. Both the underlying financial theory and the subsequent R implementation are laid out very clearly, so that even a non specialized reader can become familiar with the finance and the coding. In fact, a fully functional version of the code is available to readers for direct practice.
One particularly interesting topic which is covered is the graphical presentation of the data using interactive tools like shiny. This is where R really stands out and proves its usefulness for real world application.
Once again, a highly recommendable book.

3 people found this helpful

Helpful

Excellent intro to finance and R book

Reviewed in the United States on December 24, 2018

Out of full disclosure, I received a copy of this book from the author. I am the author of Analyzing Financial Data and Implementing Financial Models Using R, which is somewhat in a similar space as this book but my book contains a broader range of topics. Having said that, my overall view is that this book by Jonathan Regenstein is an excellent introduction to financial applications using R. We share the same teaching philosophy in that we prioritize readability of the code over efficiency/theoretical brilliance. This book teaches students some of the fundamental financial concepts of returns, risk, and factor models. It is coherently written and easy to follow. The author systematically works through each topic in multiple ways, which is an interesting and instructive approach. Ultimately, you can pick and choose which approach allows you to get the job done best and I can see how different approaches could appeal to different people. The reader will definitely learn a lot from this book and should obtain solid fundamentals to build upon for more advanced finance work using R.

3 people found this helpful

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Duncan W. Robinson

most useful book I have seen on using R in the portfolio management space in quite some time

Reviewed in the United States on January 4, 2019

Reproducible Finance with R by Jonathan Regenstein is the most useful book I have seen on using R in the portfolio management space in quite some time. This is a practitioner’s book. It gives clear examples with code on the best practices for manipulating input data – coercing it into formats that are useful for analysis. One of the great strengths of this work is its use of the functionality of “tidyverse” to structure data using such packages as “dplyr” alongside the libraries of “xts” and “PerformanceAnalytics” that offer time-series, financial and portfolio management analytical capabilities. The book covers how to construct rolling metrics – rolling standard deviation, rolling skewness and rolling Fama-French factor betas. Jonathan then shows the reader in clear and concise language how to build Shiny dashboards to visualize these outputs. I think many practitioners will find Reproducible Finance with R a useful addition to their libraries.

2 people found this helpful

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James Long

very approachable and easy to understand

Reviewed in the United States on December 17, 2018

I've spent 20 years doing financial modeling and one of the things I'm always struck by is the gap between the formulas we read in textbooks, such as Hull, and then trying to program that into a computer. It's little things like, "do I have to normalize this before applying that function" that can really slow down the process of coding the things we read about. What Jonathan does with this book that is particularly great, in my opinion, is he gives step by step examples and illustrations of how to code ideas like, returns over some time period, CAPM, sharp ratio, and factor models. He even delvs into the differences between xts methods and tidyverse methods. This is important right now as we are in a phase when R where there are a couple of different ways to do these things.

The Shiny examples are interesting, but the finance examples are invaluable. This is an excellent intro on how to do financial risk calculations in R.

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Pitabas Mohanty

book website down permanently

Reviewed in India on May 1, 2019

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I tried visiting the website of the book several times. Each time, I get a message that it is down. The first set of codes do not run. I stopped reading after the first section itself.

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