November 2013
Beginner
164 pages
3h 46m
English
book
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
Overview
Explore how to use the statistical computing language R to solve complex quantitative finance problems with "Introduction to R for Quantitative Finance." This book offers a blend of theory and practice, empowering readers with both the foundational understanding and practical skills to tackle real-world challenges using R, making it an ideal resource for beginners and seasoned professionals alike.
What this Book will help me do
- Utilize time series analysis in R to model and forecast financial and economic data.
- Apply key portfolio selection theories to analyze and optimize investment portfolios.
- Understand and implement a variety of pricing models, including the Capital Asset Pricing Model in R.
- Analyze and interpret fixed income instruments and derivatives, focusing on practical applications in finance.
- Leverage R for risk analysis through techniques such as Extreme Value Theory and copula-based modeling.
Author(s)
The authors of "Introduction to R for Quantitative Finance" are seasoned experts in the fields of quantitative finance and computational statistics. They bring a wealth of industry and academic experience to the table, having applied R to solve intricate financial problems in practical settings. Their approachable writing style ensures complex subjects remain accessible and engaging.
Who is it for?
This book is ideal for quantitative analysts, data scientists, or finance professionals eager to leverage R for financial analysis. It caters to individuals with a foundation in finance but new to the R programming language. Readers who aim to model, predict, and interpret financial phenomena using advanced statistical tools will particularly benefit from this guide.
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