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Mastering R for Quantitative Finance
Mastering R for Quantitative Finance

Mastering R for Quantitative Finance: Use R to optimize your trading strategy and build up your own risk management system

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Mastering R for Quantitative Finance

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Description

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

What you will learn

  • Analyze high frequency financial data
  • Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, BlackScholes, Margrabe, logoptimal portfolios, coreperiphery, and contagion
  • Solve practical, realworld financial problems in R related to big data, discrete hedging, transaction costs, and more.
  • Discover simulation techniques and apply them to situations where analytical formulas are not available
  • Create a winning arbitrage, speculation, or hedging strategy customized to your risk preferences
  • Understand relationships between market factors and their impact on your portfolio
  • Assess the tradeoff between accuracy and the cost of your trading strategy

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 10, 2015
Length: 362 pages
Edition : 1st
Language : English
ISBN-13 : 9781783552078
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Product Details

Publication date : Mar 10, 2015
Length: 362 pages
Edition : 1st
Language : English
ISBN-13 : 9781783552078
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total $ 153.97
Introduction to R for Quantitative Finance
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Table of Contents

14 Chapters
1. Time Series Analysis Chevron down icon Chevron up icon
2. Factor Models Chevron down icon Chevron up icon
3. Forecasting Volume Chevron down icon Chevron up icon
4. Big Data – Advanced Analytics Chevron down icon Chevron up icon
5. FX Derivatives Chevron down icon Chevron up icon
6. Interest Rate Derivatives and Models Chevron down icon Chevron up icon
7. Exotic Options Chevron down icon Chevron up icon
8. Optimal Hedging Chevron down icon Chevron up icon
9. Fundamental Analysis Chevron down icon Chevron up icon
10. Technical Analysis, Neural Networks, and Logoptimal Portfolios Chevron down icon Chevron up icon
11. Asset and Liability Management Chevron down icon Chevron up icon
12. Capital Adequacy Chevron down icon Chevron up icon
13. Systemic Risks Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
(11 Ratings)
5 star 54.5%
4 star 18.2%
3 star 9.1%
2 star 9.1%
1 star 9.1%
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Top Reviews

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bleu Sep 21, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a good book. I would recommend this to anyone who are are just starting to learn and implement financial models
Amazon Verified review Amazon
Amazon Customer May 26, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is a sequel of "Introduction to R for Quantitative Finance". It is a great book if you know R and want to learn how to perform advanced quantitative analytics in R. The book is packed with advanced quantitative topics such as:Time series analysisArbitrage pricing theory and Fama-French three-factor modelPractical examples on BIG Data Analytics using the Quandl and qualtmod packagesGeneralization of the basic Black-Scholes model and how to price a simple European call or put currency optionHow to apply the Black model to price an interest rate capHedging of derivatives in a static as well as a dynamic settingInterest rate risk measurementLiquidity risk measurementModeling non-maturity deposits
Amazon Verified review Amazon
Amazon Customer Dec 03, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book has been very instrumental in helping me to apply quantitative methods taught in the book to actual live trading. In addition to the book, the author has posted code for all of the formulas on his Github page. A lot is to be learned and gained through reading this book and applying it to your own trading environment!
Amazon Verified review Amazon
Fabio D Noronha Jan 04, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great book to get acquainted with the various R packages available in the finance realm.I suggest going through the book and later subscribing to r-bloggers.com and learning the diverse publicly available databases (yahoo, quandl, etc...) to apply it to your own portfolio.
Amazon Verified review Amazon
Christian S. May 20, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
First I should acknowledge that I'm just starting to get familiar with Quantitative Finance. I was always wondering what kind of topics I would need to learn if I wanted to go deeper. This book has answered that. Just look at the TOC.All thirteen chapters are well organized and self-contained; you can pick up one and start working on it.Each chapter gives you a clear introduction and explanation of the model and terminology that is required for further reading.I appreciate that there is no waste of space and time trying to teach you R. It is assumed that you have previous exposure to R.I still have not completed the book though, I’m half way thru, but I’m enjoying the exercises.There is math (grad level) but it is not overwhelming or too dry like reading some financial math papers. Also each chapter gives you several references for further reading.The R examples are enough to give you hands on experience in each topic.For example the chapter on Big Data gives you really good practical examples on how to handle large amount of data in R.In summary I would recommend this book if you want to dig deeper into Quantitative Finance and R. It will introduce you several R libraries with clear explanations and examples. Just don't expect to complete the whole book in a few weeks!
Amazon Verified review Amazon
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