Sparse And Robust Normal And T Portfolios By Penalized Lq Likelihood Minimization

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Financial Risk Modelling and Portfolio Optimization with R

Author : Bernhard Pfaff
Publisher : John Wiley & Sons
ISBN 13 : 1119119685
Total Pages : 448 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Financial Risk Modelling and Portfolio Optimization with R by : Bernhard Pfaff

Download or read book Financial Risk Modelling and Portfolio Optimization with R written by Bernhard Pfaff and published by John Wiley & Sons. This book was released on 2016-08-16 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Proximal Algorithms

Author : Neal Parikh
Publisher : Now Pub
ISBN 13 : 9781601987167
Total Pages : 130 pages
Book Rating : 4.9/5 (871 download)

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Book Synopsis Proximal Algorithms by : Neal Parikh

Download or read book Proximal Algorithms written by Neal Parikh and published by Now Pub. This book was released on 2013-11 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proximal Algorithms discusses proximal operators and proximal algorithms, and illustrates their applicability to standard and distributed convex optimization in general and many applications of recent interest in particular. Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed versions of these problems. They are very generally applicable, but are especially well-suited to problems of substantial recent interest involving large or high-dimensional datasets. Proximal methods sit at a higher level of abstraction than classical algorithms like Newton's method: the base operation is evaluating the proximal operator of a function, which itself involves solving a small convex optimization problem. These subproblems, which generalize the problem of projecting a point onto a convex set, often admit closed-form solutions or can be solved very quickly with standard or simple specialized methods. Proximal Algorithms discusses different interpretations of proximal operators and algorithms, looks at their connections to many other topics in optimization and applied mathematics, surveys some popular algorithms, and provides a large number of examples of proximal operators that commonly arise in practice.

Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

Author : Stephen Boyd
Publisher : Now Publishers Inc
ISBN 13 : 160198460X
Total Pages : 138 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers by : Stephen Boyd

Download or read book Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers written by Stephen Boyd and published by Now Publishers Inc. This book was released on 2011 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.

Statistical Foundations of Data Science

Author : Jianqing Fan
Publisher : CRC Press
ISBN 13 : 0429527616
Total Pages : 974 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan

Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

Optimization Methods in Finance

Author : Gerard Cornuejols
Publisher : Cambridge University Press
ISBN 13 : 9780521861700
Total Pages : 358 pages
Book Rating : 4.8/5 (617 download)

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Book Synopsis Optimization Methods in Finance by : Gerard Cornuejols

Download or read book Optimization Methods in Finance written by Gerard Cornuejols and published by Cambridge University Press. This book was released on 2006-12-21 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimization with Sparsity-Inducing Penalties

Author : Francis Bach
Publisher :
ISBN 13 : 9781601985101
Total Pages : 124 pages
Book Rating : 4.9/5 (851 download)

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Book Synopsis Optimization with Sparsity-Inducing Penalties by : Francis Bach

Download or read book Optimization with Sparsity-Inducing Penalties written by Francis Bach and published by . This book was released on 2011-12-23 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extensions have now emerged such as structured sparsity or kernel selection. It turns out that many of the related estimation problems can be cast as convex optimization problems by regularizing the empirical risk with appropriate nonsmooth norms. Optimization with Sparsity-Inducing Penalties presents optimization tools and techniques dedicated to such sparsity-inducing penalties from a general perspective. It covers proximal methods, block-coordinate descent, reweighted ?2-penalized techniques, working-set and homotopy methods, as well as non-convex formulations and extensions, and provides an extensive set of experiments to compare various algorithms from a computational point of view. The presentation of Optimization with Sparsity-Inducing Penalties is essentially based on existing literature, but the process of constructing a general framework leads naturally to new results, connections and points of view. It is an ideal reference on the topic for anyone working in machine learning and related areas.

Bandit Algorithms

Author : Tor Lattimore
Publisher : Cambridge University Press
ISBN 13 : 1108486827
Total Pages : 537 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Bandit Algorithms by : Tor Lattimore

Download or read book Bandit Algorithms written by Tor Lattimore and published by Cambridge University Press. This book was released on 2020-07-16 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.

Financial Signal Processing and Machine Learning

Author : Ali N. Akansu
Publisher : John Wiley & Sons
ISBN 13 : 1118745639
Total Pages : 312 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Linear and Mixed Integer Programming for Portfolio Optimization

Author : Renata Mansini
Publisher : Springer
ISBN 13 : 3319184822
Total Pages : 131 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Linear and Mixed Integer Programming for Portfolio Optimization by : Renata Mansini

Download or read book Linear and Mixed Integer Programming for Portfolio Optimization written by Renata Mansini and published by Springer. This book was released on 2015-06-10 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Robust Portfolio Optimization and Management

Author : Frank J. Fabozzi
Publisher : John Wiley & Sons
ISBN 13 : 0470164891
Total Pages : 513 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Robust Portfolio Optimization and Management by : Frank J. Fabozzi

Download or read book Robust Portfolio Optimization and Management written by Frank J. Fabozzi and published by John Wiley & Sons. This book was released on 2007-04-27 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Robust Portfolio Optimization and Management "In the half century since Harry Markowitz introduced his elegant theory for selecting portfolios, investors and scholars have extended and refined its application to a wide range of real-world problems, culminating in the contents of this masterful book. Fabozzi, Kolm, Pachamanova, and Focardi deserve high praise for producing a technically rigorous yet remarkably accessible guide to the latest advances in portfolio construction." --Mark Kritzman, President and CEO, Windham Capital Management, LLC "The topic of robust optimization (RO) has become 'hot' over the past several years, especially in real-world financial applications. This interest has been sparked, in part, by practitioners who implemented classical portfolio models for asset allocation without considering estimation and model robustness a part of their overall allocation methodology, and experienced poor performance. Anyone interested in these developments ought to own a copy of this book. The authors cover the recent developments of the RO area in an intuitive, easy-to-read manner, provide numerous examples, and discuss practical considerations. I highly recommend this book to finance professionals and students alike." --John M. Mulvey, Professor of Operations Research and Financial Engineering, Princeton University

Aimms Optimization Modeling

Author : Johannes Bisschop
Publisher : Lulu.com
ISBN 13 : 1847539122
Total Pages : 318 pages
Book Rating : 4.8/5 (475 download)

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Book Synopsis Aimms Optimization Modeling by : Johannes Bisschop

Download or read book Aimms Optimization Modeling written by Johannes Bisschop and published by Lulu.com. This book was released on 2006 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent.

Sparse Modeling for Image and Vision Processing

Author : Julien Mairal
Publisher : Now Publishers
ISBN 13 : 9781680830088
Total Pages : 216 pages
Book Rating : 4.8/5 (3 download)

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Book Synopsis Sparse Modeling for Image and Vision Processing by : Julien Mairal

Download or read book Sparse Modeling for Image and Vision Processing written by Julien Mairal and published by Now Publishers. This book was released on 2014-12-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sparse Modeling for Image and Vision Processing offers a self-contained view of sparse modeling for visual recognition and image processing. More specifically, it focuses on applications where the dictionary is learned and adapted to data, yielding a compact representation that has been successful in various contexts.

Teaching at Its Best

Author : Linda B. Nilson
Publisher : John Wiley & Sons
ISBN 13 : 0470612363
Total Pages : 401 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Teaching at Its Best by : Linda B. Nilson

Download or read book Teaching at Its Best written by Linda B. Nilson and published by John Wiley & Sons. This book was released on 2010-04-20 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Teaching at Its Best This third edition of the best-selling handbook offers faculty at all levels an essential toolbox of hundreds of practical teaching techniques, formats, classroom activities, and exercises, all of which can be implemented immediately. This thoroughly revised edition includes the newest portrait of the Millennial student; current research from cognitive psychology; a focus on outcomes maps; the latest legal options on copyright issues; and how to best use new technology including wikis, blogs, podcasts, vodcasts, and clickers. Entirely new chapters include subjects such as matching teaching methods with learning outcomes, inquiry-guided learning, and using visuals to teach, and new sections address Felder and Silverman's Index of Learning Styles, SCALE-UP classrooms, multiple true-false test items, and much more. Praise for the Third Edition of Teaching at Its BestEveryone veterans as well as novices will profit from reading Teaching at Its Best, for it provides both theory and practical suggestions for handling all of the problems one encounters in teaching classes varying in size, ability, and motivation." Wilbert McKeachie, Department of Psychology, University of Michigan, and coauthor, McKeachie's Teaching TipsThis new edition of Dr. Nilson's book, with its completely updated material and several new topics, is an even more powerful collection of ideas and tools than the last. What a great resource, especially for beginning teachers but also for us veterans!" L. Dee Fink, author, Creating Significant Learning ExperiencesThis third edition of Teaching at Its Best is successful at weaving the latest research on teaching and learning into what was already a thorough exploration of each topic. New information on how we learn, how students develop, and innovations in instructional strategies complement the solid foundation established in the first two editions." Marilla D. Svinicki, Department of Psychology, The University of Texas, Austin, and coauthor, McKeachie's Teaching Tips

Hedge Funds

Author : François-Serge Lhabitant
Publisher : John Wiley & Sons
ISBN 13 : 0470687770
Total Pages : 573 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis Hedge Funds by : François-Serge Lhabitant

Download or read book Hedge Funds written by François-Serge Lhabitant and published by John Wiley & Sons. This book was released on 2009-08-20 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: "An excellent and comprehensive source of information on hedge funds! From a quantitative view Lhabitant has done it once again by meticulously looking at the important topics in the hedge fund industry. This book has a tremendous wealth of information and is a valuable addition to the hedge fund literature. In addition, it will benefit institutional investors, high net worth individuals, academics and anyone interested in learning more about this fascinating and often mysterious world of privately managed money. Written by one of the most respected practitioners and academics in the area of hedge funds." —Greg N. Gregoriou, Professor of finance and research coordinator in the School of Business and Economics at Plattsburgh State University of New York "This is a landmark book on quantitative approaches to hedge funds. All those with a stake in building hedge fund portfolios will highly profit from this exhaustive guide. A must read for all those involved in hedge fund investing." —Pascal Botteron, Ph.D., Head of Hedge Fund Product Development, Pictet Asset Management "François-Serge Lhabitant's second book will prove to be a bestseller too - just like Hedge Funds: Myths and Limits. He actually manages to make quantitative analysis 'approachable'- even for those less gifted with numbers. This book, like its predecessor, includes an unprecedented mix of common sense and sophisticated technique. A fantastic guide to the 'nuts and bolts' of hedge fund analysis and a 'must' for every serious investor." —Barbara Rupf Bee, Head of Alternative Fund Investment Group, HSBC Private Bank, Switzerland "An excellent book, providing deep insights into the complex quantitative analysis of hedge funds in the most lucid and intuitive manner. A must-have supplement to Lhabitant's first book dealing with the mystical and fascinating world of hedge funds. Highly recommended!" —Vikas Agarwal, Assistant Professor of Finance, J. Mack Robinson College of Business, Georgia State University "Lhabitant has done it again! Whereas most books on hedge funds are nothing more than glorified marketing brochures, Lhabitant's new book tells it how it is in reality. Accessible and understandable but at the same time thorough and critical." —Harry M. Kat, Ph.D., Professor of Risk Management and Director Alternative Investment Research Centre, Cass Business School, City University "Lhabitant's latest work on hedge funds yet again delivers on some ambitious promises. Successfully bridging theory and practice in a highly accessible manner, those searching for a thorough yet unintimidating introduction to the quantitative methods of hedge fund analysis will not be disappointed." —Christopher L. Culp, Ph.D., Adjunct Professor of Finance, Graduate School of Business, The University of Chicago and Principal, Chicago Partners LLC

Convex Optimization

Author : Stephen P. Boyd
Publisher : Cambridge University Press
ISBN 13 : 9780521833783
Total Pages : 744 pages
Book Rating : 4.8/5 (337 download)

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Book Synopsis Convex Optimization by : Stephen P. Boyd

Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Multivariate T-Distributions and Their Applications

Author : Samuel Kotz
Publisher : Cambridge University Press
ISBN 13 : 9780521826549
Total Pages : 296 pages
Book Rating : 4.8/5 (265 download)

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Book Synopsis Multivariate T-Distributions and Their Applications by : Samuel Kotz

Download or read book Multivariate T-Distributions and Their Applications written by Samuel Kotz and published by Cambridge University Press. This book was released on 2004-02-16 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Almost all the results available in the literature on multivariate t-distributions published in the last 50 years are now collected together in this comprehensive reference. Because these distributions are becoming more prominent in many applications, this book is a must for any serious researcher or consultant working in multivariate analysis and statistical distributions. Much of this material has never before appeared in book form. The first part of the book emphasizes theoretical results of a probabilistic nature. In the second part of the book, these are supplemented by a variety of statistical aspects. Various generalizations and applications are dealt with in the final chapters. The material on estimation and regression models is of special value for practitioners in statistics and economics. A comprehensive bibliography of over 350 references is included.

Nonsmooth Approach to Optimization Problems with Equilibrium Constraints

Author : Jiri Outrata
Publisher : Springer Science & Business Media
ISBN 13 : 1475728255
Total Pages : 281 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Nonsmooth Approach to Optimization Problems with Equilibrium Constraints by : Jiri Outrata

Download or read book Nonsmooth Approach to Optimization Problems with Equilibrium Constraints written by Jiri Outrata and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the early fifties, applied mathematicians, engineers and economists started to pay c10se attention to the optimization problems in which another (lower-Ievel) optimization problem arises as a side constraint. One of the motivating factors was the concept of the Stackelberg solution in game theory, together with its economic applications. Other problems have been encountered in the seventies in natural sciences and engineering. Many of them are of practical importance and have been extensively studied, mainly from the theoretical point of view. Later, applications to mechanics and network design have lead to an extension of the problem formulation: Constraints in form of variation al inequalities and complementarity problems were also admitted. The term "generalized bi level programming problems" was used at first but later, probably in Harker and Pang, 1988, a different terminology was introduced: Mathematical programs with equilibrium constraints, or simply, MPECs. In this book we adhere to MPEC terminology. A large number of papers deals with MPECs but, to our knowledge, there is only one monograph (Luo et al. , 1997). This monograph concentrates on optimality conditions and numerical methods. Our book is oriented similarly, but we focus on those MPECs which can be treated by the implicit programming approach: the equilibrium constraint locally defines a certain implicit function and allows to convert the problem into a mathematical program with a nonsmooth objective.