Introduction to R for Quantitative Finance
Language: English
Published by Packt Publishing Limited, GB, 2013
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 44.05
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Add to basketItem description from seller
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.Key FeaturesUse time series analysis to model and forecast house pricesEstimate the term structure of interest rates using prices of government bondsDetect systemically important financial institutions by employing financial network analysisBook DescriptionIntroduction 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.What you will learnHow to model and forecast house prices and improve hedge ratios using cointegration and model volatilityHow to understand the theory behind portfolio selection and how it can be applied to real-world dataHow to utilize the Capital Asset Pricing Model and the Arbitrage Pricing TheoryHow to understand the basics of fixed income instrumentsYou will discover how to use discrete- and continuous-time models for pricing derivative securitiesHow to successfully work with credit default models and how to model correlated defaults using copulasHow to understand the uses of the Extreme Value Theory in insurance and fi nance, model fitting, and risk measure calculationWho this book is forIf 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.…
Seller Inventory # LU-9781783280933
- Title
- Introduction to R for Quantitative Finance
- Author
- Peter Csoka, Marton Michaletzky, Zsolt Tulassay, Agnes Vidovics-Dancs, Gergely Daróczi, Michael Phule, Kata Váradi, Edina Berlinger (EURO), Daniel Daniel Havran, Agnes Vidovics Dancs
- Publisher
- Packt Publishing Limited, GB
- Publication year
- 2013
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 178328093X
- ISBN 13
- 9781783280933
- Item weight
- 300 grams
- Dimensions
- 23.5 x 19.1 x 0.9 cm
"Synopsis" may belong to another edition of this title.
About the Author
Michael Puhle obtained a Ph.D. in Finance from the University of Passau in Germany. He worked for several years as a Senior Risk Controller at Allianz Global Investors in Munich, and as an Assistant Manager at KPMG's Financial Risk Management practice, where he was advising banks on market risk models. Michael is also the author of Bond Portfolio Optimization published by Springer Publishing.
Edina Berlinger has a PhD in economics from the Corvinus University of Budapest. She is an associate professor, teaching corporate finance, investments, and financial risk management. She is the head of the Finance department of the university, and is also the chair of the finance subcommittee of the Hungarian Academy of Sciences. Her expertise covers loan systems, risk management, and more recently, network analysis. She has led several research projects in student loan design, liquidity management, heterogeneous agent models, and systemic risk.
Péter Csóka is an Associate Professor at the Department of Finance, Corvinus University of Budapest, and a research fellow in the Game Theory Research Group, Centre For Economic and Regional Studies, Hungarian Academy of Sciences. He received his Ph.D. in Economics from Maastricht University in 2008. His research topics include risk measures, risk capital allocation, game theory, corporate finance, and general equilibrium theory. He is currently focused on analyzing risk contributions for systemic risk and for illiquid portfolios. He has papers published in journals such as Mathematical Methods of Operational Research, European Journal of Operational Research, Games and Economic Behaviour, and Journal of Banking and Finance. He is the Chair of the organizing committee of the Annual Financial Market Liquidity Conference in Budapest.
Dániel Havran is a postdoctoral research fellow at Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences. He also holds a part-time assistant professor position at the Corvinus University of Budapest, where he teaches corporate finance (BA, PhD) and credit risk management (MSc). He obtained his PhD in economics at Corvinus University of Budapest in 2011.
"About the title" may belong to another edition of this title.
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