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Mastering R for Quantitative Finance Edina Berlinger

Mastering R for Quantitative Finance By Edina Berlinger

Mastering R for Quantitative Finance by Edina Berlinger


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Mastering R for Quantitative Finance Summary

Mastering R for Quantitative Finance by Edina Berlinger

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About 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. Ferenc Illes has an MSc degree in mathematics from Eotvos Lorand 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. Milan 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. Adam 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. Gergely Daroczi is an enthusiast R package developer and founder/CTO of an R-based web application at Rapporter. He is also a PhD candidate in sociology and is currently working as the lead R developer at CARD.com in Los Angeles. Besides teaching statistics and doing data analysis projects for several years, he has around 10 years of experience with the R programming environment. Gergely is the coauthor of Introduction to R for Quantitative Finance, and is currently working on another Packt book, Mastering Data Analysis with R, apart from a number of journal articles on social science and reporting topics. He contributed to the book by reviewing and formatting the R source code. Barbara Domotor 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. 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. Daniel 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. Peter Juhasz 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. Istvan 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.

Additional information

GOR012612753
9781783552078
1783552077
Mastering R for Quantitative Finance by Edina Berlinger
Used - Very Good
Hardback
Packt Publishing Limited
20230402
362
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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