Portfolio Optimization With R Rmetrics
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Portfolio Optimization With R Rmetrics
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Author :
language : en
Publisher: Rmetrics
Release Date :
Portfolio Optimization With R Rmetrics written by and has been published by Rmetrics this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Financial Risk Modelling And Portfolio Optimization With R
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Author : Bernhard Pfaff
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-16
Financial Risk Modelling And Portfolio Optimization With R written by Bernhard Pfaff and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-16 with Mathematics categories.
Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Financial Risk Modelling And Portfolio Optimization With R
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Author : Bernhard Pfaff
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-22
Financial Risk Modelling And Portfolio Optimization With R written by Bernhard Pfaff and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-22 with Mathematics categories.
Financial Risk Modelling and Portfolio Optimization with R, 2nd Edition Bernhard Pfaff, Invesco Global Asset Allocation, Germany A must have text for risk modelling and portfolio optimization using R. This book introduces the latest techniques advocated for measuring financial market risk and portfolio optimization, and provides a plethora of R code examples that enable the reader to replicate the results featured throughout the book. This edition has been extensively revised to include new topics on risk surfaces and probabilistic utility optimization as well as an extended introduction to R language. Financial Risk Modelling and Portfolio Optimization with R: Demonstrates techniques in modelling financial risks and applying portfolio optimization techniques as well as recent advances in the field. Introduces stylized facts, loss function and risk measures, conditional and unconditional modelling of risk; extreme value theory, generalized hyperbolic distribution, volatility modelling and concepts for capturing dependencies. Explores portfolio risk concepts and optimization with risk constraints. Is accompanied by a supporting website featuring examples and case studies in R. Includes updated list of R packages for enabling the reader to replicate the results in the book. Graduate and postgraduate students in finance, economics, risk management as well as practitioners in finance and portfolio optimization will find this book beneficial. It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
Computational Finance
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Author : Argimiro Arratia
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-05-08
Computational Finance written by Argimiro Arratia and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-08 with Computers categories.
The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.
The Use Of Risk Budgets In Portfolio Optimization
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Author : Albina Unger
language : en
Publisher: Springer
Release Date : 2014-09-10
The Use Of Risk Budgets In Portfolio Optimization written by Albina Unger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-10 with Business & Economics categories.
Risk budgeting models set risk diversification as objective in portfolio allocation and are mainly promoted from the asset management industry. Albina Unger examines the portfolios based on different risk measures in several aspects from the academic perspective (Utility, Performance, Risk, Different Market Phases, Robustness, and Factor Exposures) to investigate the use of these models for asset allocation. Beside the risk budgeting models, alternatives of risk-based investment styles are also presented and examined. The results show that equalizing the risk across the assets does not prevent losses, especially in crisis periods and the performance can mainly be explained by exposures to known asset pricing factors. Thus, the advantages of these approaches compared to known minimum risk portfolios are doubtful.
Introduction To R For Quantitative Finance
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Author : Gergely Daróczi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-11-22
Introduction To R For Quantitative Finance written by Gergely Daróczi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-22 with Computers categories.
This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.
Numerical Methods And Optimization In Finance
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Author : Manfred Gilli
language : en
Publisher: Academic Press
Release Date : 2019-08-30
Numerical Methods And Optimization In Finance written by Manfred Gilli and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-30 with categories.
Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance. Introduces numerical methods to readers with economics backgrounds Emphasizes core simulation and optimization problems Includes MATLAB and R code for all applications, with sample code in the text and freely available for download
Portfolio Construction And Analytics
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Author : Frank J. Fabozzi
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-11
Portfolio Construction And Analytics written by Frank J. Fabozzi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-11 with Business & Economics categories.
A detailed, multi-disciplinary approach to investment analytics Portfolio Construction and Analytics provides an up-to-date understanding of the analytic investment process for students and professionals alike. With complete and detailed coverage of portfolio analytics and modeling methods, this book is unique in its multi-disciplinary approach. Investment analytics involves the input of a variety of areas, and this guide provides the perspective of data management, modeling, software resources, and investment strategy to give you a truly comprehensive understanding of how today's firms approach the process. Real-world examples provide insight into analytics performed with vendor software, and references to analytics performed with open source software will prove useful to both students and practitioners. Portfolio analytics refers to all of the methods used to screen, model, track, and evaluate investments. Big data, regulatory change, and increasing risk is forcing a need for a more coherent approach to all aspects of investment analytics, and this book provides the strong foundation and critical skills you need. Master the fundamental modeling concepts and widely used analytics Learn the latest trends in risk metrics, modeling, and investment strategies Get up to speed on the vendor and open-source software most commonly used Gain a multi-angle perspective on portfolio analytics at today's firms Identifying investment opportunities, keeping portfolios aligned with investment objectives, and monitoring risk and performance are all major functions of an investment firm that relies heavily on analytics output. This reliance will only increase in the face of market changes and increased regulatory pressure, and practitioners need a deep understanding of the latest methods and models used to build a robust investment strategy. Portfolio Construction and Analytics is an invaluable resource for portfolio management in any capacity.
Hands On Matrix Algebra Using R
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Author : Hrishikesh D. Vinod
language : en
Publisher: World Scientific
Release Date : 2011
Hands On Matrix Algebra Using R written by Hrishikesh D. Vinod and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Mathematics categories.
Teaches matrix algebra, allowing the student to learn the material by actually working with matrix objects in modern computer environment of R. This book provides an overview of matrix theory without being bogged down in proofs or tedium.
Quantitative Investment Portfolio Analytics In R
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Author : James Picerno
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-06-18
Quantitative Investment Portfolio Analytics In R written by James Picerno and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-18 with categories.
R is a free, open source programming language that's become a popular standard for financial and economic analysis. Quantitative Investment Portfolio Analytics In R is your guide to getting started with modeling portfolio risk and return in R. Even if you have no experience with the software, you'll be fluent in R at a basic level after reading this short primer. The chapters provide step-by-step instructions for tapping into R's powerful capabilities for portfolio analytics.