Algorithms for Worst-Case Design and Applications to Risk Management

Algorithms for Worst-Case Design and Applications to Risk Management

Author: Berç Rustem

Publisher: Princeton University Press

Published: 2009-02-09

Total Pages: 405

ISBN-13: 1400825113

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Recognizing that robust decision making is vital in risk management, this book provides concepts and algorithms for computing the best decision in view of the worst-case scenario. The main tool used is minimax, which ensures robust policies with guaranteed optimal performance that will improve further if the worst case is not realized. The applications considered are drawn from finance, but the design and algorithms presented are equally applicable to problems of economic policy, engineering design, and other areas of decision making. Critically, worst-case design addresses not only Armageddon-type uncertainty. Indeed, the determination of the worst case becomes nontrivial when faced with numerous--possibly infinite--and reasonably likely rival scenarios. Optimality does not depend on any single scenario but on all the scenarios under consideration. Worst-case optimal decisions provide guaranteed optimal performance for systems operating within the specified scenario range indicating the uncertainty. The noninferiority of minimax solutions--which also offer the possibility of multiple maxima--ensures this optimality. Worst-case design is not intended to necessarily replace expected value optimization when the underlying uncertainty is stochastic. However, wise decision making requires the justification of policies based on expected value optimization in view of the worst-case scenario. Conversely, the cost of the assured performance provided by robust worst-case decision making needs to be evaluated relative to optimal expected values. Written for postgraduate students and researchers engaged in optimization, engineering design, economics, and finance, this book will also be invaluable to practitioners in risk management.


The Science of Algorithmic Trading and Portfolio Management

The Science of Algorithmic Trading and Portfolio Management

Author: Robert Kissell

Publisher: Academic Press

Published: 2013-10-01

Total Pages: 492

ISBN-13: 0124016936

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The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems. This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. - Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. - Helps readers design systems to manage algorithmic risk and dark pool uncertainty. - Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.


Work in the Gig Economy

Work in the Gig Economy

Author: James Duggan

Publisher: Routledge

Published: 2021-07-01

Total Pages: 77

ISBN-13: 1000440206

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Throughout the last decade, the ‘gig economy’ has emerged as one of the most significant developments in the world of work. As a novel, hyper-flexible form of labour, gig work features a uniquely fragmented working arrangement wherein independent workers partner with digital platform organisations to provide a range of on-demand services to customers. Work in the Gig Economy: A Research Overview provides a concise overview to the key themes and debate that encompass the gig economy literature. It covers five core themes: an introduction to gig work; classification issues; the role of technology; the experiences of gig workers; and the future of gig work. As an emerging and diverse research field, contributions stem from an array of perspectives including psychology, sociology, human resource management, legal studies, and technology management. The chapters synthesise the most prominent insights into this emerging field, key thinking on the complex relationships and conditions found in gig work, and the most significant issues to be addressed as the gig economy continues to develop. A critical introduction for students, scholars and reflective professionals and policymakers, this book provides much needed direction through the rapidly growing and expansive body of research on work in the gig economy.


Computational Probability

Computational Probability

Author: John H. Drew

Publisher: Springer Science & Business Media

Published: 2008-01-08

Total Pages: 220

ISBN-13: 0387746765

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This title organizes computational probability methods into a systematic treatment. The book examines two categories of problems. "Algorithms for Continuous Random Variables" covers data structures and algorithms, transformations of random variables, and products of independent random variables. "Algorithms for Discrete Random Variables" discusses data structures and algorithms, sums of independent random variables, and order statistics.


Event Mining

Event Mining

Author: Tao Li

Publisher: CRC Press

Published: 2015-10-15

Total Pages: 340

ISBN-13: 1466568593

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With a focus on computing system management, this book presents a variety of event mining approaches for improving the quality and efficiency of IT service and system management. It covers different components in the data-driven framework, from system monitoring and event generation to pattern discovery and summarization. The book explores recent developments in event mining, such as new clustering-based approaches, as well as various applications of event mining, including social media.


Evolutionary Algorithms in Management Applications

Evolutionary Algorithms in Management Applications

Author: Jörg Biethahn

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 384

ISBN-13: 3642612172

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Evolutionary Algorithms (EA) are powerful search and optimisation techniques inspired by the mechanisms of natural evolution. They imitate, on an abstract level, biological principles such as a population based approach, the inheritance of information, the variation of information via crossover/mutation, and the selection of individuals based on fitness. The most well-known class of EA are Genetic Algorithms (GA), which have received much attention not only in the scientific community lately. Other variants of EA, in particular Genetic Programming, Evolution Strategies, and Evolutionary Programming are less popular, though very powerful too. Traditionally, most practical applications of EA have appeared in the technical sector. Management problems, for a long time, have been a rather neglected field of EA-research. This is surprising, since the great potential of evolutionary approaches for the business and economics domain was recognised in pioneering publications quite a while ago. John Holland, for instance, in his seminal book Adaptation in Natural and Artificial Systems (The University of Michigan Press, 1975) identified economics as one of the prime targets for a theory of adaptation, as formalised in his reproductive plans (later called Genetic Algorithms).


The Logic of Logistics

The Logic of Logistics

Author: David Simchi-Levi

Publisher: Springer Science & Business Media

Published: 2007-07-03

Total Pages: 355

ISBN-13: 0387226192

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Fierce competition in today's global market provides a powerful motivation for developing ever more sophisticated logistics systems. This book, written for the logistics manager and researcher, presents a survey of the modern theory and application of logistics. The goal of the book is to present the state-of-the-art in the science of logistics management. As a result, the authors have written a timely and authoritative survey of this field that many practitioners and researchers will find makes an invaluable companion to their work.


Markov Chains: Models, Algorithms and Applications

Markov Chains: Models, Algorithms and Applications

Author: Wai-Ki Ching

Publisher: Springer Science & Business Media

Published: 2006-06-05

Total Pages: 212

ISBN-13: 038729337X

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Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.


Data Streams

Data Streams

Author: S. Muthukrishnan

Publisher: Now Publishers Inc

Published: 2005

Total Pages: 136

ISBN-13: 193301914X

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In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.


Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Author: Dash, Sujata

Publisher: IGI Global

Published: 2017-08-10

Total Pages: 567

ISBN-13: 152252858X

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The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.