Introduction to R for Quantitative Finance
by Gergely Daróczi, Michael Phule, Edina Berlinger (EURO), Peter Csoka, Daniel Daniel Havran, Marton Michaletzky, Zsolt Tulassay, Kata Váradi, Agnes Vidovics-Dancs, Agnes Vidovics Dancs
Preface
Introduction to R for Quantitative Finance will show you how to solve real-world quantitative finance problems using the statistical computing languages R and QF. In this book, we will cover diverse topics ranging from Time Series Analysis to Financial Networks. Each chapter will briefly present the theory and deal with solving a specific problem using R.
What this book covers
Chapter 1, Time Series Analysis (Michael Puhle), explains working with time series data in R. Furthermore, you will learn how to model and forecast house prices, improve hedge ratios using cointegration, and model volatility.
Chapter 2, Portfolio Optimization (Péter Csóka, Ferenc Illés, Gergely Daróczi), covers the theoretical idea behind portfolio selection and shows ...
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