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Financial Risk Modelling and Portfolio Optimization with R

Author: Bernhard Pfaff

Publisher: John Wiley & Sons

Published: 2016-10-03

Total Pages: 448

ISBN-13: 1119119669

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

Author: Bernhard Pfaff

Publisher: John Wiley & Sons

Published: 2016-08-22

Total Pages: 448

ISBN-13: 1119119677

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Portfolio Optimization with R/Rmetrics

Author:

Publisher: Rmetrics

Published:

Total Pages: 455

ISBN-13:

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Numerical Methods and Optimization in Finance

Author: Manfred Gilli

Publisher: Academic Press

Published: 2019-08-30

Total Pages: 638

ISBN-13: 0128150653

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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

Stochastic Optimization

Author: Stanislav Uryasev

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 438

ISBN-13: 1475765940

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Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic programming applications and other related topics. Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.

Portfolio Risk Analysis

Author: Gregory Connor

Publisher: Princeton University Press

Published: 2010-03-15

Total Pages: 400

ISBN-13: 1400835291

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Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium. Portfolio Risk Analysis provides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.

Recent Applications of Financial Risk Modelling and Portfolio Management

Author: Škrinjari?, Tihana

Publisher: IGI Global

Published: 2020-09-25

Total Pages: 432

ISBN-13: 1799850846

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In today’s financial market, portfolio and risk management are facing an array of challenges. This is due to increasing levels of knowledge and data that are being made available that have caused a multitude of different investment models to be explored and implemented. Professionals and researchers in this field are in need of up-to-date research that analyzes these contemporary models of practice and keeps pace with the advancements being made within financial risk modelling and portfolio control. Recent Applications of Financial Risk Modelling and Portfolio Management is a pivotal reference source that provides vital research on the use of modern data analysis as well as quantitative methods for developing successful portfolio and risk management techniques. While highlighting topics such as credit scoring, investment strategies, and budgeting, this publication explores diverse models for achieving investment goals as well as improving upon traditional financial modelling methods. This book is ideally designed for researchers, financial analysts, executives, practitioners, policymakers, academicians, and students seeking current research on contemporary risk management strategies in the financial sector.

Financial Risk Management and Modeling

Author: Constantin Zopounidis

Publisher: Springer Nature

Published: 2021-09-13

Total Pages: 480

ISBN-13: 3030666913

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Risk is the main source of uncertainty for investors, debtholders, corporate managers and other stakeholders. For all these actors, it is vital to focus on identifying and managing risk before making decisions. The success of their businesses depends on the relevance of their decisions and consequently, on their ability to manage and deal with the different types of risk. Accordingly, the main objective of this book is to promote scientific research in the different areas of risk management, aiming at being transversal and dealing with different aspects of risk management related to corporate finance as well as market finance. Thus, this book should provide useful insights for academics as well as professionals to better understand and assess the different types of risk.

Applied Probabilistic Calculus for Financial Engineering

Author: Bertram K. C. Chan

Publisher: John Wiley & Sons

Published: 2017-10-16

Total Pages: 532

ISBN-13: 1119387612

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Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a "Random Walk" Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.

Optimization Methods in Finance

Author: Gerard Cornuejols

Publisher: Cambridge University Press

Published: 2006-12-21

Total Pages: 358

ISBN-13: 9780521861700

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Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.