Details

Portfolio Optimization with R/Rmetrics Update 2015


Portfolio Optimization with R/Rmetrics Update 2015



from: Diethelm Würtz, Yohan Chalabi, William Chen, Tobias Setz, Andrew Ellis

Fr. 128.80

Publisher: Finance Online
Format PDF
ISBN/EAN: 9783906041018
Language: englisch

This book contains a watermark.

Descriptions

This is a book about portfolio optimization from the perspective of computational finance and financial engineering. Thus the main emphasis is to briefly introduce the concepts and to give the reader a set of powerful tools to solve the problems in the field of portfolio optimization. This book divides roughly into five parts. The first part, Chapters 1-10, is dedicated to the exploratory data analysis of financial assets, the second part, Chapters 11-14, to the framework of portfolio design, selection and optimization, the third part, Chapters 15-19, to the mean-variance portfolio approach, the fourth part, Chapters 20-23, to the mean-conditional value-at-risk portfolio approach, and the fifth part, Chapters 24-26, to portfolio backtesting and benchmarking.

The NEW Update 2015 supports R Version 3.2.
Contents

Introduction

Part I Managing Data Sets of Assets
Introduction
Generic Functions to Manipulate Assets
Financial Functions to Manipulate Assets
Basic Statistics of Financial Assets
Robust Mean and Covariance Estimates of Assets

Part II Exploratory Data Analysis of Assets
Introduction
Plotting Financial Time Series And Their Properties
Customization of Plots
Modelling Assets Returns
Selecting Similar or Dissimilar Assets
Comparing Multivariate Return and Risk Statistics
Pairwise Dependencies of Assets

Part III Portfolio Framework
Introduction
S4 Portfolio Specification Class
S4 Portfolio Data Class
S4 Portfolio Constraints Class
Portfolio Functions
Markowitz Portfolio Theory
Mean-Variance Portfolio Settings
Minimum Risk Mean-Variance Portfolios
Mean-Variance Portfolio Frontiers
Case Study: Dow Jones Index
Robust Portfolios and Covariance Estimation

Part V Mean-CVaR Portfolios
Introduction
Mean-CVaR Portfolio Theory
Mean-CVaR Portfolio Settings
Mean-CVaR Portfolios
Mean-CVaR Portfolio Frontiers

Part VI Portfolio Backtesting
Introduction
S4 Portfolio Backtest Class
Case Study: SPI Sector Rotation
Case Study: GCC Index Rotation
Part VII Appendix
DiethelmWurtz is professor at the Institute for Theoretical Physics,ITP, and for the Curriculum Computational Science and Engineering, CSE, at the Swiss Federal Institute of Technology in Zurich. He teaches Econophysics at ITP and supervises seminars in Financial Engineering at CSE.Diethelm is senior partner of Finance Online, an ETH spin-off company in Zurich, and co-founder of the Rmetrics Association.
Yohan Chalabi gained his PhD in the Econophysicsgroup at ETH Zurich at the Institute for Theoretical Physics. Yohan is a co-maintainer of the Rmetrics packages.
William Chen has a master in statistics from University of Auckland in New Zealand. In the summer of 2008, he did a Student Internship in the Econophysics group at ETH Zurich at the Institute for Theoretical Physics. During his three months internship,William contributed to the portfolio backtest package.
Andrew Ellis read neuroscience and mathematics at the University in Zurich. He did a Student Internship in the Econophysics group at ETH Zurich at the Institute for Theoretical Physics. Andrew is worked on the Rmetrics documentationproject and co-authored this ebook on portfolio optimization with Rmetrics.

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