Financial Risk Modelling And Portfolio Optimization With R

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Financial Risk Modelling and Portfolio Optimization with R

Author : Bernhard Pfaff
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 48,9 Mb
Release : 2016-10-03
Category : Mathematics
ISBN : 9781119119661

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Financial Risk Modelling and Portfolio Optimization with R by Bernhard Pfaff Pdf

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
Page : 448 pages
File Size : 44,8 Mb
Release : 2016-08-22
Category : Mathematics
ISBN : 9781119119678

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Financial Risk Modelling and Portfolio Optimization with R by Bernhard Pfaff Pdf

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.

Numerical Methods and Optimization in Finance

Author : Manfred Gilli,Dietmar Maringer,Enrico Schumann
Publisher : Academic Press
Page : 638 pages
File Size : 55,8 Mb
Release : 2019-08-30
Category : Electronic
ISBN : 9780128150658

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Numerical Methods and Optimization in Finance by Manfred Gilli,Dietmar Maringer,Enrico Schumann Pdf

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,Panos M. Pardalos
Publisher : Springer Science & Business Media
Page : 438 pages
File Size : 51,6 Mb
Release : 2013-03-09
Category : Technology & Engineering
ISBN : 9781475765946

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Stochastic Optimization by Stanislav Uryasev,Panos M. Pardalos Pdf

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.

Applied Probabilistic Calculus for Financial Engineering

Author : Bertram K. C. Chan
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 53,8 Mb
Release : 2017-10-16
Category : Mathematics
ISBN : 9781119387619

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Applied Probabilistic Calculus for Financial Engineering by Bertram K. C. Chan Pdf

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.

Portfolio Optimization with R/Rmetrics

Author : Anonim
Publisher : Rmetrics
Page : 455 pages
File Size : 40,9 Mb
Release : 2024-05-27
Category : Electronic
ISBN : 8210379456XXX

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Portfolio Optimization with R/Rmetrics by Anonim Pdf

Risk Analysis and Portfolio Modelling

Author : Elisa Luciano,David Allen
Publisher : MDPI
Page : 224 pages
File Size : 45,8 Mb
Release : 2019-10-16
Category : Business & Economics
ISBN : 9783039216246

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Risk Analysis and Portfolio Modelling by Elisa Luciano,David Allen Pdf

Financial Risk Measurement is a challenging task, because both the types of risk and the techniques evolve very quickly. This book collects a number of novel contributions to the measurement of financial risk, which address either non-fully explored risks or risk takers, and does so in a wide variety of empirical contexts.

Linear and Mixed Integer Programming for Portfolio Optimization

Author : Renata Mansini,Włodzimierz Ogryczak,M. Grazia Speranza
Publisher : Springer
Page : 119 pages
File Size : 47,7 Mb
Release : 2015-06-10
Category : Business & Economics
ISBN : 9783319184821

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Linear and Mixed Integer Programming for Portfolio Optimization by Renata Mansini,Włodzimierz Ogryczak,M. Grazia Speranza Pdf

This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.

Analyzing Financial Data and Implementing Financial Models Using R

Author : Clifford S. Ang
Publisher : Springer Nature
Page : 465 pages
File Size : 42,6 Mb
Release : 2021-06-23
Category : Business & Economics
ISBN : 9783030641559

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Analyzing Financial Data and Implementing Financial Models Using R by Clifford S. Ang Pdf

This advanced undergraduate/graduate textbook teaches students in finance and economics how to use R to analyse financial data and implement financial models. It demonstrates how to take publically available data and manipulate, implement models and generate outputs typical for particular analyses. A wide spectrum of timely and practical issues in financial modelling are covered including return and risk measurement, portfolio management, option pricing and fixed income analysis. This new edition updates and expands upon the existing material providing updated examples and new chapters on equities, simulation and trading strategies, including machine learnings techniques. Select data sets are available online.

Portfolio Risk Analysis

Author : Gregory Connor,Lisa R. Goldberg,Robert A. Korajczyk
Publisher : Princeton University Press
Page : 400 pages
File Size : 45,5 Mb
Release : 2010-03-15
Category : Business & Economics
ISBN : 9781400835294

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Portfolio Risk Analysis by Gregory Connor,Lisa R. Goldberg,Robert A. Korajczyk Pdf

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.

Optimization Methods in Finance

Author : Gerard Cornuejols
Publisher : Unknown
Page : 345 pages
File Size : 52,5 Mb
Release : 2007
Category : Finance
ISBN : 1107168295

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Optimization Methods in Finance by Gerard Cornuejols Pdf

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.

Financial Risk Forecasting

Author : Jon Danielsson
Publisher : John Wiley & Sons
Page : 307 pages
File Size : 45,6 Mb
Release : 2011-04-20
Category : Business & Economics
ISBN : 9781119977117

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Financial Risk Forecasting by Jon Danielsson Pdf

Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.

Introduction to Risk Parity and Budgeting

Author : Thierry Roncalli
Publisher : CRC Press
Page : 430 pages
File Size : 46,9 Mb
Release : 2016-04-19
Category : Business & Economics
ISBN : 9781482207163

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Introduction to Risk Parity and Budgeting by Thierry Roncalli Pdf

Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global fina

Recent Applications of Financial Risk Modelling and Portfolio Management

Author : Škrinjari?, Tihana,?ižmešija, Mirjana,Christiansen, Bryan
Publisher : IGI Global
Page : 432 pages
File Size : 42,8 Mb
Release : 2020-09-25
Category : Business & Economics
ISBN : 9781799850847

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Recent Applications of Financial Risk Modelling and Portfolio Management by Škrinjari?, Tihana,?ižmešija, Mirjana,Christiansen, Bryan Pdf

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.

Optimal Portfolio Modeling

Author : Philip McDonnell
Publisher : John Wiley & Sons
Page : 314 pages
File Size : 41,9 Mb
Release : 2008-05-02
Category : Business & Economics
ISBN : 9780470260852

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Optimal Portfolio Modeling by Philip McDonnell Pdf

Optimal Portfolio Modeling is an easily accessible introduction to portfolio modeling for those who prefer an intuitive approach to this discipline. While early chapters provide engaging insights on the statistical properties of markets, this book quickly moves on to illustrate invaluable trading and risk control models based on popular programs such as Excel and the statistical modeling language R. This reliable resource presents modeling formulas that will allow you to effectively maximize the performance, minimize the drawdown, and manage the risk of your portfolio.