Author: István Maros
Publisher:
ISBN:
Category : Decision support systems
Languages : en
Pages : 556
Book Description
Applied Mathematical Programming and Modeling II (APMOD93)
Author: István Maros
Publisher:
ISBN:
Category : Decision support systems
Languages : en
Pages : 556
Book Description
Publisher:
ISBN:
Category : Decision support systems
Languages : en
Pages : 556
Book Description
Index of Conference Proceedings
Author:
Publisher:
ISBN:
Category : Conference proceedings
Languages : en
Pages : 976
Book Description
Publisher:
ISBN:
Category : Conference proceedings
Languages : en
Pages : 976
Book Description
Nonlinear Methods in Economic Dynamics and Optimal Control
Author: Gustav Feichtinger
Publisher:
ISBN:
Category : Chaotic behavior in systems
Languages : en
Pages : 466
Book Description
Publisher:
ISBN:
Category : Chaotic behavior in systems
Languages : en
Pages : 466
Book Description
Collegium Logicum
Author:
Publisher:
ISBN:
Category : Automatic theorem proving
Languages : en
Pages : 408
Book Description
Publisher:
ISBN:
Category : Automatic theorem proving
Languages : en
Pages : 408
Book Description
Mathematical Reviews
Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 748
Book Description
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 748
Book Description
Advances in Portfolio Construction and Implementation
Author: Alan Scowcroft
Publisher: Elsevier
ISBN: 0080471846
Category : Business & Economics
Languages : en
Pages : 384
Book Description
Modern Portfolio Theory explores how risk averse investors construct portfolios in order to optimize market risk against expected returns. The theory quantifies the benefits of diversification.Modern Portfolio Theory provides a broad context for understanding the interactions of systematic risk and reward. It has profoundly shaped how institutional portfolios are managed, and has motivated the use of passive investment management techniques, and the mathematics of MPT is used extensively in financial risk management.Advances in Portfolio Construction and Implementation offers practical guidance in addition to the theory, and is therefore ideal for Risk Mangers, Actuaries, Investment Managers, and Consultants worldwide. Issues are covered from a global perspective and all the recent developments of financial risk management are presented. Although not designed as an academic text, it should be useful to graduate students in finance.*Provides practical guidance on financial risk management*Covers the latest developments in investment portfolio construction*Full coverage of the latest cutting edge research on measuring portfolio risk, alternatives to mean variance analysis, expected returns forecasting, the construction of global portfolios and hedge portfolios (funds)
Publisher: Elsevier
ISBN: 0080471846
Category : Business & Economics
Languages : en
Pages : 384
Book Description
Modern Portfolio Theory explores how risk averse investors construct portfolios in order to optimize market risk against expected returns. The theory quantifies the benefits of diversification.Modern Portfolio Theory provides a broad context for understanding the interactions of systematic risk and reward. It has profoundly shaped how institutional portfolios are managed, and has motivated the use of passive investment management techniques, and the mathematics of MPT is used extensively in financial risk management.Advances in Portfolio Construction and Implementation offers practical guidance in addition to the theory, and is therefore ideal for Risk Mangers, Actuaries, Investment Managers, and Consultants worldwide. Issues are covered from a global perspective and all the recent developments of financial risk management are presented. Although not designed as an academic text, it should be useful to graduate students in finance.*Provides practical guidance on financial risk management*Covers the latest developments in investment portfolio construction*Full coverage of the latest cutting edge research on measuring portfolio risk, alternatives to mean variance analysis, expected returns forecasting, the construction of global portfolios and hedge portfolios (funds)
Computational Intelligence. Theory and Applications
Author: Bernd Reusch
Publisher: Springer Science & Business Media
ISBN: 9783540628682
Category : Computers
Languages : en
Pages : 632
Book Description
This book constitutes the refereed proceedings of the International Conference on Computational Intelligence held in Dortmund, Germany, as the 5th Fuzzy Days, in April 1997. Besides three invited contributions, the book presents 53 revised full papers selected from a total of 130 submissions. Also included are 35 posters documenting a broad scope of applications of computational intelligence techniques in a variety of areas. The volume addresses all current issues in computational intelligence, e.g. fuzzy logic, fuzzy control, neural networks, evolutionary algorithms, genetic programming, neuro-fuzzy systems, adaptation and learning, machine learning, etc.
Publisher: Springer Science & Business Media
ISBN: 9783540628682
Category : Computers
Languages : en
Pages : 632
Book Description
This book constitutes the refereed proceedings of the International Conference on Computational Intelligence held in Dortmund, Germany, as the 5th Fuzzy Days, in April 1997. Besides three invited contributions, the book presents 53 revised full papers selected from a total of 130 submissions. Also included are 35 posters documenting a broad scope of applications of computational intelligence techniques in a variety of areas. The volume addresses all current issues in computational intelligence, e.g. fuzzy logic, fuzzy control, neural networks, evolutionary algorithms, genetic programming, neuro-fuzzy systems, adaptation and learning, machine learning, etc.
Applications of Stochastic Programming
Author: Stein W. Wallace
Publisher: SIAM
ISBN: 9780898718799
Category : Mathematics
Languages : en
Pages : 724
Book Description
Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
Publisher: SIAM
ISBN: 9780898718799
Category : Mathematics
Languages : en
Pages : 724
Book Description
Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
Mathematical Models for Decision Support
Author: Harvey J. Greenberg
Publisher: Springer Science & Business Media
ISBN: 3642835554
Category : Computers
Languages : en
Pages : 740
Book Description
It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation.
Publisher: Springer Science & Business Media
ISBN: 3642835554
Category : Computers
Languages : en
Pages : 740
Book Description
It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation.
Introduction to Stochastic Programming
Author: John R. Birge
Publisher: Springer Science & Business Media
ISBN: 0387226184
Category : Mathematics
Languages : en
Pages : 427
Book Description
This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.
Publisher: Springer Science & Business Media
ISBN: 0387226184
Category : Mathematics
Languages : en
Pages : 427
Book Description
This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.