Statistical Decision Problems

Author: Michael Zabarankin
Publisher: Springer Science & Business Media
ISBN: 1461484715
Format: PDF, Kindle
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Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

Modeling Dynamics Optimization and Bioeconomics II

Author: Alberto A. Pinto
Publisher: Springer
ISBN: 3319552368
Format: PDF, ePub, Mobi
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The concepts and techniques presented in this volume originated from the fields of dynamics, statistics, control theory, computer science and informatics, and are applied to novel and innovative real-world applications. Over the past few decades, the use of dynamic systems, control theory, computing, data mining, machine learning and simulation has gained the attention of numerous researchers from all over the world. Admirable scientific projects using both model-free and model-based methods coevolved at today’s research centers and are introduced in conferences around the world, yielding new scientific advances and helping to solve important real-world problems. One important area of progress is the bioeconomy, where advances in the life sciences are used to produce new products in a sustainable and clean manner. In this book, scientists from all over the world share their latest insights and important findings in the field. The majority of the contributed papers for this volume were written by participants of the 3rd International Conference on Dynamics, Games and Science, DGSIII, held at the University of Porto in February 2014, and at the Berkeley Bioeconomy Conference at the University of California at Berkeley in March 2014. The aim of the project of this book “Modeling, Dynamics, Optimization and Bioeconomics II” follows the same aim as its companion piece, “Modeling, Dynamics, Optimization and Bioeconomics I,” namely, the exploration of emerging and cutting-edge theories and methods for modeling, optimization, dynamics and bioeconomy.

Financial Signal Processing and Machine Learning

Author: Ali N. Akansu
Publisher: John Wiley & Sons
ISBN: 1118745647
Format: PDF, Mobi
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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.

Multi Criteria Decision Analysis to Support Healthcare Decisions

Author: Kevin Marsh
Publisher: Springer
ISBN: 3319475401
Format: PDF, Mobi
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Representing the first collection on the topic, this book builds from foundations to case studies, to future prospects, providing the reader with a rich and comprehensive understanding of the use of multi-criteria decision analysis (MCDA) in healthcare. The first section of the collection presents the foundations of MCDA as it is applied to healthcare decisions, providing guidance on the ethical and theoretical underpinnings of MCDA and how to select MCDA methods appropriate to different decision settings. Section two comprises a collection of case studies spanning the decision continuum, including portfolio development, benefit–risk assessment, health technology assessment, priority setting, resource optimisation, clinical practice and shared decision making. Section three explores future directions in the application of MCDA to healthcare and identifies opportunities for further research to support these.

Fuzzy Multi Criteria Decision Making

Author: Cengiz Kahraman
Publisher: Springer Science & Business Media
ISBN: 0387768130
Format: PDF, ePub, Docs
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This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.

Optimization Theory Decision Making and Operations Research Applications

Author: Athanasios Migdalas
Publisher: Springer Science & Business Media
ISBN: 1461451345
Format: PDF, ePub
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These proceedings consist of 30 selected research papers based on results presented at the 10th Balkan Conference & 1st International Symposium on Operational Research (BALCOR 2011) held in Thessaloniki, Greece, September 22-24, 2011. BALCOR is an established biennial conference attended by a large number of faculty, researchers and students from the Balkan countries but also from other European and Mediterranean countries as well. Over the past decade, the BALCOR conference has facilitated the exchange of scientific and technical information on the subject of Operations Research and related fields such as Mathematical Programming, Game Theory, Multiple Criteria Decision Analysis, Information Systems, Data Mining and more, in order to promote international scientific cooperation. The carefully selected and refereed papers present important recent developments and modern applications and will serve as excellent reference for students, researchers and practitioners in these disciplines. ​

Smart City Networks

Author: Stamatina Th. Rassia
Publisher: Springer
ISBN: 3319613138
Format: PDF, ePub, Docs
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This book both analyzes and synthesizes new cutting-edge theories and methods for future design implementations in smart cities through interdisciplinary synergizing of architecture, technology, and the Internet of Things (IoT). Implementation of IoT enables the collection and data exchange of objects embedded with electronics, software, sensors, and network connectivity. Recently IoT practices have moved into uniquely identifiable objects that are able to transfer data directly into networks. This book features new technologically advanced ideas, highlighting properties of smart future city networks. Chapter contributors include theorists, computer scientists, mathematicians, and interdisciplinary planners, who currently work on identifying theories, essential elements, and practices where the IoT can impact the formation of smart cities and sustainability via optimization, network analyses, data mining, mathematical modeling and engineering. Moreover, this book includes research-based theories and real world practices aimed toward graduate researchers, experts, practitioners and the general public interested in architecture, engineering, mathematical modeling, industrial design, computer science technologies, and related fields.

Portfolio Decision Analysis

Author: Ahti Salo
Publisher: Springer Science & Business Media
ISBN: 9781441999436
Format: PDF, ePub
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Portfolio Decision Analysis: Improved Methods for Resource Allocation provides an extensive, up-to-date coverage of decision analytic methods which help firms and public organizations allocate resources to 'lumpy' investment opportunities while explicitly recognizing relevant financial and non-financial evaluation criteria and the presence of alternative investment opportunities. In particular, it discusses the evolution of these methods, presents new methodological advances and illustrates their use across several application domains. The book offers a many-faceted treatment of portfolio decision analysis (PDA). Among other things, it (i) synthesizes the state-of-play in PDA, (ii) describes novel methodologies, (iii) fosters the deployment of these methodologies, and (iv) contributes to the strengthening of research on PDA. Portfolio problems are widely regarded as the single most important application context of decision analysis, and, with its extensive and unique coverage of these problems, this book is a much-needed addition to the literature. The book also presents innovative treatments of new methodological approaches and their uses in applications. The intended audience consists of practitioners and researchers who wish to gain a good understanding of portfolio decision analysis and insights into how PDA methods can be leveraged in different application contexts. The book can also be employed in courses at the post-graduate level.

Enhanced Methods in Computer Security Biometric and Artificial Intelligence Systems

Author: Jerzy Pejas
Publisher: Springer Science & Business Media
ISBN: 0387234845
Format: PDF, Mobi
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Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems contains over 30 contributions from leading European researchers showing the present state and future directions of computer science research. "Methods of Artificial Intelligence and Intelligent Agents" contains 13 contributions analyzing such areas of AI as fuzzy set theory, predicate logic, neural networks, clustering, data mining and others. It also presents applications of AI as possible solutions for problems like firm bankruptcy, soil erosion, flight control and others. "Information Technology Security" covers three important areas of security engineering in information systems: software security, public key infrastructure and the design of new cryptographic protocols and algorithms. "Biometric Systems" comprises 11 contributions dealing with face picture analysis and recognition systems. This chapter focuses on known methods of biometric problem solution as well as the design of new models.

Financial Risk Modelling and Portfolio Optimization with R

Author: Bernhard Pfaff
Publisher: John Wiley & Sons
ISBN: 1119119685
Format: PDF, Docs
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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.