Reproducible Finance with R
CRC Press (Verlag)
978-1-138-48403-0 (ISBN)
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.
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.
Chapter 1
Introduction
Returns
Chapter 2
Asset Prices to Returns
Converting Daily Prices to Monthly Returns in the xts world
Converting Daily Prices to Monthly Returns in the tidyverse
Converting Daily Prices to Monthly Returns in the tidyquant world
Converting Daily Prices to Monthly Returns with tibbletime
Visualizing Asset Returns in the xts world
Visualizing Asset Returns in the tidyverse
Chapter 3
Building a Portfolio
Portfolio Returns in the xts world
Portfolio Returns in the tidyverse
Portfolio Returns in the tidyquant world
Visualizing Portfolio Returns in the xts world
Visualizing Portfolio Returns in the tidyverse
Shiny App Portfolio Returns
Concluding Returns
Risk
Chapter 4
Standard Deviation
Standard Deviation in the xts world
Standard Devation in the tidyverse
Standard Deviation in the tidyquant world
Visualizing Standard Deviation
Rolling Standard Deviation
Rolling Standard Deviation in the xts world
Rolling Standard Deviation in the tidyverse
Rolling Standard Devation with the tidyverse and tibbletime
Rolling Standard Deviation in the tidyquant world
Visualizing Rolling Standard Deviation in the xts world
Visualizing Rolling Standard Deviation in the tidyverse
Shiny App Standard Deviation
Chapter 5
Skewness
Skewness in the xts world
Skewness in the tidyverse
Visualizing Skewness
Rolling Skewness in the xts world
Rolling Skewness in the tidyverse with tibbletime
Rolling Skewness in the tidyquant world
Visualizing Rolling Skewness
Chapter 6
Kurtosis
Kurtosis in the xts world
Kurtosis in the tidyverse
Visualizing Kurtosis
Rolling Kurtosis in the xts world
Rolling Kurtosis in the tidyverse with tibbletime
Rolling Kurtosis in the tidyquant world
Visualizing Rolling Kurtosis
Shiny App Skewness and Kurtosis
Concluding Risk
Portfolio Theory
Chapter 7
Sharpe Ratio
Sharpe Ratio in the xts world
Sharpe Ratio in the tidyverse
Shape Ratio in the tidyquant world
Visualizing Sharpe Ratio
Rolling Sharpe Ratio in the xts World
Rolling Sharpe Ratio with the tidyverse and tibbletime
Rolling Sharpe Ratio with tidyquant
Visualizing the Rolling Sharpe Ratio
Shiny App Sharpe Ratio
Chapter 8
CAPM
CAPM and Market Returns
Calculating CAPM Beta
Calculating CAPM Beta in the xts world
Contents v
Calculating CAPM Beta in the tidyverse
Calculating CAPM Beta in the tidyquant world
Visualizing CAPM with ggplot
Augmenting Our Data
Visualizing CAPM with highcharter
Shiny App CAPM
Chapter 9
Fama French
Importing and Wrangling Fama French
Visualizing Fama French with ggplot
Rolling Fama French with the tidyverse and tibbletime
Visualizing Rolling Fama French
Shiny App Fama French
Concluding Portfolio Theory
Practice and Applications
Chapter 10
Component Contribution to Standard Deviation
Component Contribution Step-by-Step
Component Contribution with a Custom Function
Visualizing Component Contribution
Rolling Component Contribution to Volatility
Visualizing Rolling Component Contribution to Volatility
Shiny App Component Contribution
Chapter 11
Monte Carlo Simulation
Simulating Growth of a Dollar
Several Simulation Functions
Running Multiple Simulations
Visualizing Simulation Results
Visualizing with highcharter
Shiny App Monte Carlo
Concluding Practice Applications
| Erscheinungsdatum | 05.10.2018 |
|---|---|
| Reihe/Serie | Chapman & Hall/CRC The R Series |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 436 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra | |
| ISBN-10 | 1-138-48403-2 / 1138484032 |
| ISBN-13 | 978-1-138-48403-0 / 9781138484030 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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