Reproducible Finance with R
Code Flows and Shiny Apps for Portfolio Analysis
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"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
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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. Les mer
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.
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.
Detaljer
- Forlag
- CRC Press
- Innbinding
- Innbundet
- Språk
- Engelsk
- Sider
- 248
- ISBN
- 9781138484221
- Utgivelsesår
- 2018
- Format
- 23 x 16 cm
Anmeldelser
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"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
»
«
"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
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