Introduction to R for Quantitative Finance: R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

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3.2 (20 Ratings)

Paperback Nov 2013 164 pages 1st Edition

€32.99

Paperback Nov 2013 164 pages 1st Edition

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Introduction to R for Quantitative Finance

Chapter 2. Portfolio Optimization

By now we are familiar with the basics of the R language. We know how to analyze data, call its built-in functions, and apply them to the selected problems in a time series analysis. In this chapter we will use and extend this knowledge to discuss an important practical application: portfolio optimization, or in other words, security selection. This section covers the idea behind portfolio optimization: the mathematical models and theoretical solutions. To improve programming skills, we will implement an algorithm line by line using real data to solve a real-world example. We will also use the pre-written R packages on the same data set.

Imagine that we live in a tropical island and have only USD 100 to invest. Investment possibilities on the island are very limited; we can invest our entire fund into either ice creams or umbrellas. The payoffs that depend on the weather are as follows:

weather	ice cream	umbrella
sunny	120	90
rainy	90	120

Suppose...

Key benefits

Use time series analysis to model and forecast house prices
Estimate the term structure of interest rates using prices of government bonds
Detect systemically important financial institutions by employing financial network analysis

Description

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples.This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems.Starting with time series analysis, you will also learn how to optimize portfolios and how asset pricing models work. The book then covers fixed income securities and derivatives such as credit risk management.

Who is this book for?

If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.

What you will learn

How to model and forecast house prices and improve hedge ratios using cointegration and model volatility
How to understand the theory behind portfolio selection and how it can be applied to real-world data
How to utilize the Capital Asset Pricing Model and the Arbitrage Pricing Theory
How to understand the basics of fixed income instruments
You will discover how to use discrete- and continuous-time models for pricing derivative securities
How to successfully work with credit default models and how to model correlated defaults using copulas
How to understand the uses of the Extreme Value Theory in insurance and fi nance, model fitting, and risk measure calculation

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NazHus Jan 30, 2014

The book is ideal for those who are looking to use R to solve financial and statistical problems. However basic knowledge of financial theory is a needed. The authors do a great job on applying R to financial scenarios. Concepts are covered in a clear and concise manner. Perfect for beginners and Intermediates.

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Amazon Customer May 20, 2016

excellent

Mauricio E. Ruiz Font Feb 05, 2014

El autor aclara que no se necesita saber R, pero eso no quiere decir que el libro vaya a empezar dando una introducción, se aprende sobre la lectura. no esperes encontrar un capitulo de introducción a R.

D. Wong Jan 05, 2014

I really enjoyed this book. After working through the problems several times I realized how powerful R was and how many tools that are at my disposal. I think the author gives a great spread of very common financial calculations with repeatable examples. I am not am professional in any way but really felt it was good for someone who had a basic knowledge of quantitative finance and was looking to see how to apply that in R.Overall I think i got a great deal out of this book and it gives me much more confidence in working with R. Espeically for people just getting into either quant finance or working in RUsing the kindle version, i did have some annoying problems with the code. Because of 2 things. First off there are + signs on every line which is how its outputted in R, which you must remove. Also the kindle cut/paste function always gives the copyright and location. Which you have to delete out of every time you cut and paste. Its not really the authors fault just a quirk of the kindle cut and paste system. I did not subtract a star for this because of the kindle interface, however i can see where someone else would.

David O'Brien Jan 13, 2014

I have a lot of experience with R, but am just starting to get into quantitative finance, as such, I found it very difficult to comprehend a lot of the chapters. Typically each page would have at least 1 or 2 terms that I would end up having to google. So you can imagine that the going was pretty slow. But the book is designed for people with some finance background.Even though I didn't get as much as I was hoping to initially, I think it's going to be a very handy resource for me to have. When I'm going to do an analysis covered by this book, I'm going to look at the examples as a primer to get going on the task. One of the hardest parts about R is finding the right function or package for a specific task. This book lays everything out there for me. And even if I'm going alter the analysis somehow, it's a huge time saver to have all the main functions in one place with cool examples.I think this book is perfect for someone who is familiar with finance and wants to switch languages to R, or maybe for finance students who don't know a statistical language (with maybe another resource for the basics of R). I'm going to take a free coursera course in finance and then come back to this book. Once I have more background, the book should be a good primer for new ideas for me.

Introduction to R for Quantitative Finance: R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

What do you get with Print?

Introduction to R for Quantitative Finance

Chapter 2. Portfolio Optimization

Mean-Variance model

Solution concepts

Theorem (Lagrange)

Working with real data

Tangency portfolio and Capital Market Line

Noise in the covariance matrix

When variance is not enough

Summary

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Introduction to R for Quantitative Finance: R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

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