Introduction to R for Quantitative Finance

Introduction to R for Quantitative Finance

By: Zsolt Tulassay (author), Michael Puhle (author), Vidovics-Dancs Vidovics-Dancs (author), Peter Csoka (author), Daniel Havran (author), Kata Varadi (author), Marton Michaletzky (author), Edina Berlinger (author), Gergely Daroczi (author)Paperback

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This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance. 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.

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About Author

Gergely Daroczi is a Ph.D. candidate in Sociology with around eight years' experience in data management and analysis tasks within the R programming environment. Besides teaching Statistics at different Hungarian universities and doing data analysis jobs for several years, Gergely has founded and coordinated a UK-based online reporting startup company recently. This latter software or platform as a service which is called will potentially provide an intuitive frontend and an interface to all the methods and techniques covered in the book. His role in the book was to provide R implementation of the QF problems and methods. 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 Ph.D. in Economics from the Corvinus University of Budapest. She is an Associate Professor, teaching corporate fi nance, investments, and fi nancial risk management. She is the Head of Department for Finance of the university and is also the Chair of the Finance Sub committee the Hungarian Academy of Sciences. Her expertise covers student loan systems, risk management, and, recently, network analysis. She has led several research projects in student loan design, liquidity management, heterogeneous agent models, and systemic risk. Peter Peter Csoka 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 fi nance, 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. Daniel Havran is a Post Doctoral Fellow at the Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences. He also holds a part-time Assistant Professorship position at the Corvinus University of Budapest, where he teaches Corporate Finance (BA and Ph.D. levels), and Credit Risk Management (MSc) courses. He obtained his Ph.D. in Economics at Corvinus University of Budapest in 2011. His research interests are corporate cash, funding liquidity management, and credit derivatives over-the-counter markets.

Product Details

  • publication date: 15/11/2013
  • ISBN13: 9781783280933
  • Format: Paperback
  • Number Of Pages: 164
  • ID: 9781783280933
  • weight: 294
  • ISBN10: 178328093X

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