Mastering R for Quantitative Finance

More Information
  • Analyze high frequency financial data
  • Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, Black-Scholes, Margrabe, logoptimal portfolios, core-periphery, and contagion
  • Solve practical, real-world 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 trade-off between accuracy and the cost of your trading strategy

R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Its strength lies in data analysis, graphics, visualization, and data manipulation. R is becoming a widely used modeling tool in science, engineering, and business.

The book is organized as a step-by-step practical guide to using R. Starting with time series analysis, you will also learn how to forecast the volume for VWAP Trading. Among other topics, the book covers FX derivatives, interest rate derivatives, and optimal hedging. The last chapters provide an overview on liquidity risk management, risk measures, and more.

The book pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the book, you will be well versed with various financial techniques using R and will be able to place good bets while making financial decisions.

  • Learn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in R
  • Understand the concepts of financial engineering and create trading strategies for complex financial instruments
  • Explore R for asset and liability management and capital adequacy modeling
Page Count 362
Course Length 10 hours 51 minutes
ISBN 9781783552078
Date Of Publication 10 Mar 2015


Ágnes Vidovics-Dancs

Ágnes Vidovics-Dancs is a PhD candidate and an assistant professor at the Department of Finance, Corvinus University of Budapest. Previously, she worked as a junior risk manager in the Hungarian Government Debt Management Agency. Her main research areas are government debt management (in general) and sovereign crises and defaults (in particular). She is a CEFA and CIIA diploma holder.

Dániel Havran

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.

Edina Berlinger

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.

Gergely Daróczi

Gergely Daróczi is a former assistant professor of statistics and an enthusiastic R user and package developer. He is the founder and CTO of an R-based reporting web application at and a PhD candidate in sociology. He is currently working as the lead R developer/research data scientist at in Los Angeles.

Besides maintaining around half a dozen R packages, mainly dealing with reporting, Gergely has coauthored the books Introduction to R for Quantitative Finance and Mastering R for Quantitative Finance (both by Packt Publishing) by providing and reviewing the R source code. He has contributed to a number of scientific journal articles, mainly in social sciences but in medical sciences as well.

Kata Váradi

Kata Váradi is an assistant professor at the Department of Finance, Corvinus University of Budapest since 2013. Kata graduated in finance in 2009 from Corvinus University of Budapest and was awarded a PhD degree in 2012 for her thesis on the analysis of the market liquidity risk on the Hungarian stock market. Her research areas are market liquidity, fixed income securities, and networks in healthcare systems. Besides doing research, she is active in teaching as well. She mainly teaches corporate finance, investments, valuation, and multinational financial management.

Ferenc Illés

Ferenc Illés has an MSc degree in mathematics from Eötvös Loránd University. A few years after graduation, he started studying actuarial and financial mathematics, and he is about to pursue his PhD from Corvinus University of Budapest. In recent years, he has worked in the banking industry. Currently, he is developing statistical models with R. His interest lies in large networks and computational complexity.

Tamás Vadász

Tamás Vadász has an MSc degree in economics from the Corvinus University of Budapest. After graduation, he was working as a consultant in the financial services industry. Currently, he is pursuing his PhD in finance, and his main research interests are financial economics and risk management in banking. His teaching experience at Corvinus University includes financial econometrics, investments, and corporate finance.

Barbara Dömötör

Barbara Dömötör is an assistant professor of the department of Finance at Corvinus University of Budapest. Before starting her PhD studies in 2008, she worked for several multinational banks. She wrote her doctoral thesis about corporate hedging. She lectures on corporate finance, financial risk management, and investment analysis. Her main research areas are financial markets, financial risk management, and corporate hedging.

Balázs Árpád Szűcs

Balázs Árpád Szűcs is a PhD candidate in finance at the Corvinus University of Budapest. He works as a research assistant at the Department of Finance at the same university. He holds a master's degree in investment analysis and risk management. His research interests include optimal execution, market microstructure, and forecasting intraday volume.

Julia Molnár

Julia Molnár is a PhD candidate at the Department of Finance, Corvinus University of Budapest. Her main research interests include financial network, systemic risk, and financial technology innovations in retail banking. She has been working at McKinsey & Company since 2011, where she is involved in several digital and innovation studies in the area of banking.

Péter Medvegyev

Péter Medvegyev has an MSc degree in economics from the Marx Károly University Budapest. After completing his graduation in 1977, he started working as a consultant in the Hungarian Management Development Center. He got his PhD in Economics in 1985. He has been working for the Mathematics department of the Corvinus University Budapest since 1993. His teaching experience at Corvinus University includes stochastic processes, mathematical finance, and several other subjects in mathematics.

Balázs Márkus

Balázs Márkus has been working with financial derivatives for over 10 years. He has been trading many different kinds of derivatives, from carbon swaps to options on T-bond futures. He was the head of the Foreign Exchange Derivative Desk at Raiffesien Bank in Budapest. He is a member of the advisory board at Pallas Athéné Domus Scientiae Foundation, and is a part-time analyst at the National Bank of Hungary and the managing director of Nitokris Ltd, a small proprietary trading and consulting company. He is currently working on his PhD about the role of dynamic hedging at the Corvinus University of Budapest, where he is affiliated as a teaching assistant.

Péter Juhász

Péter Juhász holds a PhD degree in business administration from the Corvinus University of Budapest and is also a CFA charterholder. As an associate professor, he teaches corporate finance, business valuation, VBA programming in Excel, and communication skills. His research field covers the valuation of intangible assets, business performance analysis and modeling, and financial issues in public procurement and sports management. He is the author of several articles, chapters, and books mainly on the financial performance of Hungarian firms. Besides, he also regularly acts as a consultant for SMEs and is a senior trainer for EY Business Academy in the EMEA region.

Ágnes Tuza

Ágnes Tuza holds an applied economics degree from Corvinus University of Budapest and is an incoming student of HEC Paris in International Finance. Her work experience covers structured products' valuation for Morgan Stanley as well as management consulting for The Boston Consulting Group. She is an active forex trader and shoots a monthly spot for Gazdaság TV on an investment idea where she frequently uses technical analysis, a theme she has been interested in since the age of 15. She has been working as a teaching assistant at Corvinus in various finance-related subjects.

Milán Badics

Milán Badics has a master's degree in finance from the Corvinus University of Budapest. Now, he is a PhD student and a member of the PADS PhD scholarship program. He teaches financial econometrics, and his main research topics are time series forecasting with data-mining methods, financial signal processing, and numerical sensitivity analysis on interest rate models. He won the competition of the X. Kochmeister-prize organized by the Hungarian Stock Exchange in May 2014.

István Margitai

István Margitai is an analyst in the ALM team of a major banking group in the CEE region. He mainly deals with methodological issues, product modeling, and internal transfer pricing topics. He started his career with asset-liability management in Hungary in 2009. He gained experience in strategic liquidity management and liquidity planning. He majored in investments and risk management at Corvinus University of Budapest. His research interest is the microeconomics of banking, market microstructure, and the liquidity of order-driven markets.

Gergely Gabler

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.

Ádám Banai

Ádám Banai has received his MSc degree in investment analysis and risk management from Corvinus University of Budapest. He joined the Financial Stability department of the Magyar Nemzeti Bank (MNB, the central bank of Hungary) in 2008. Since 2013, he is the head of the Applied Research and Stress Testing department at the Financial System Analysis Directorate (MNB). He is also a PhD student at the Corvinus University of Budapest since 2011. His main research fields are solvency stress-testing, funding liquidity risk, and systemic risk.