Mastering R for Quantitative Finance
Use R to optimize your trading strategy and build up your own risk management system
Published on 13. January 2025
362 pages
978-1-78355-208-5 (ISBN)
Description
Key Features
Book DescriptionThis 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
Who this book is for
Book DescriptionThis 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
Who this book is for
All prices
More details
Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
3,80 MB
ISBN-13
978-1-78355-208-5 (9781783552085)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Edina Berlinger | Ferenc Illés | Tamás Vadász
Mastering R for Quantitative Finance
Book
02/2015
Packt Publishing
€63.60
Shipment within 3-4 weeks
Person
Gergely Gabler is the head of the Business Model Analysis department at the banking supervisory division of National Bank of Hungary (MNB) since 2014. Before this, he used to lead the Macroeconomic Research department at Erste Bank Hungary after being an equity analyst since 2008. He graduated from the Corvinus University of Budapest in 2009 with an MSc degree in financial mathematics. He has been a guest lecturer at Corvinus University of Budapest since 2010, and he also gives lectures in MCC College for advanced studies. He is about to finish the CFA program in 2015 to become a charterholder.
Content
Table of Contents
Time Series Analysis
Factor Models
Forecasting Volume for VWAP Trading
Big Data ? Advanced Analytics
FX Derivatives
Interest Rate Derivatives
Exotic Options
Optimal Hedging
Fundamental Analysis
Technical Analysis
Asset/Liability Management
Capital Adequacy
Systemic Risk
Time Series Analysis
Factor Models
Forecasting Volume for VWAP Trading
Big Data ? Advanced Analytics
FX Derivatives
Interest Rate Derivatives
Exotic Options
Optimal Hedging
Fundamental Analysis
Technical Analysis
Asset/Liability Management
Capital Adequacy
Systemic Risk
