Practical Applications Of Evolutionary Computation To Financial Engineering
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Practical Applications Of Evolutionary Computation To Financial Engineering
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Author : Hitoshi Iba
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-15
Practical Applications Of Evolutionary Computation To Financial Engineering written by Hitoshi Iba and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Technology & Engineering categories.
“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.
Financial Engineering
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Author : Tanya S. Beder
language : en
Publisher: John Wiley & Sons
Release Date : 2011-06-07
Financial Engineering written by Tanya S. Beder and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-07 with Business & Economics categories.
FINANCIAL ENGINEERING Financial engineering is poised for a great shift in the years ahead. Everyone from investors and borrowers to regulators and legislators will need to determine what works, what doesn't, and where to go from here. Financial Engineering—part of the Robert W. Kolb Series in Finance—has been designed to help you do just this. Comprised of contributed chapters by distinguished experts from industry and academia, this reliable resource will help you focus on established activities in the field, developing trends and changes, as well as areas of opportunity. Divided into five comprehensive parts, Financial Engineering begins with an informative overview of the discipline, chronicling its complete history and profiling potential career paths. From here, Part II quickly moves on to discuss the evolution of financial engineering in major markets—fixed income, foreign exchange, equities, commodities and credit—and offers important commentary on what has worked and what will change. Part III then examines a number of recent innovative applications of financial engineering that have made news over the past decade—such as the advent of securitized and structured products and highly quantitative trading strategies for both equities and fixed income. Thoughts on how risk management might be retooled to reflect what has been learned as a result of the recent financial crisis are also included. Part IV of the book is devoted entirely to case studies that present valuable lessons for active practitioners and academics. Several of the cases explore the risk that has instigated losses across multiple markets, including the global credit crisis. You'll gain in-depth insights from cases such as Countrywide, Société Générale, Barings, Long-Term Capital Management, the Florida Local Government Investment Pool, AIG, Merrill Lynch, and many more. The demand for specific and enterprise risk managers who can think outside the box will be substantial during this decade. Much of Part V presents new ways to be successful in an era that demands innovation on both sides of the balance sheet. Chapters that touch upon this essential topic include Musings About Hedging; Operational Risk; and The No-Arbitrage Condition in Financial Engineering: Its Use and Mis-Use. This book is complemented by a companion website that includes details from the editors' survey of financial engineering programs around the globe, along with a glossary of key terms from the book. This practical guide puts financial engineering in perspective, and will give you a better idea of how it can be effectively utilized in real- world situations.
Natural Computing In Computational Finance
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Author : Anthony Brabazon
language : en
Publisher: Springer
Release Date : 2009-01-30
Natural Computing In Computational Finance written by Anthony Brabazon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-30 with Business & Economics categories.
Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems. This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer’s Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.
Natural Computing In Computational Finance
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Author : Anthony Brabazon
language : en
Publisher: Springer
Release Date : 2010-07-11
Natural Computing In Computational Finance written by Anthony Brabazon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-11 with Technology & Engineering categories.
The chapters in this book illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. The eleven chapters were selected following a rigorous, peer-reviewed, selection process.
Natural Computing In Computational Finance
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Author : Anthony Brabazon
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-05-09
Natural Computing In Computational Finance written by Anthony Brabazon and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-09 with Mathematics categories.
Natural Computing in Computational Finance is a innovative volume containing fifteen chapters which illustrate cutting-edge applications of natural computing or agent-based modeling in modern computational finance. Following an introductory chapter the book is organized into three sections. The first section deals with optimization applications of natural computing demonstrating the application of a broad range of algorithms including, genetic algorithms, differential evolution, evolution strategies, quantum-inspired evolutionary algorithms and bacterial foraging algorithms to multiple financial applications including portfolio optimization, fund allocation and asset pricing. The second section explores the use of natural computing methodologies such as genetic programming, neural network hybrids and fuzzy-evolutionary hybrids for model induction in order to construct market trading, credit scoring and market prediction systems. The final section illustrates a range of agent-based applications including the modeling of payment card and financial markets. Each chapter provides an introduction to the relevant natural computing methodology as well as providing a clear description of the financial application addressed. The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, in the fields of both natural computing and finance.
Natural Computing In Computational Finance
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Author : Anthony Brabazon
language : en
Publisher: Springer
Release Date : 2011-10-14
Natural Computing In Computational Finance written by Anthony Brabazon and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-14 with Technology & Engineering categories.
This book follows on from Natural Computing in Computational Finance Volumes I, II and III. As in the previous volumes of this series, the book consists of a series of chapters each of which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. which was selected following a rigorous, peer-reviewed, selection process. The chapters illustrate the application of a range of cutting-edge natural computing and agent-based methodologies in computational finance and economics. The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. The applications explored include option model calibration, financial trend reversal detection, enhanced indexation, algorithmic trading, corporate payout determination and agent-based modeling of liquidity costs, and trade strategy adaptation. While describing cutting edge applications, the chapters are written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics. written so that they are accessible to a wide audience. Hence, they should be of interest to academics, students and practitioners in the fields of computational finance and economics.
Evolutionary Algorithms For Solving Multi Objective Problems
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Author : Carlos A. Coello Coello
language : en
Publisher: Springer Science & Business Media
Release Date : 2002
Evolutionary Algorithms For Solving Multi Objective Problems written by Carlos A. Coello Coello and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.
The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and deterministic and stochastic techniques for solving these large dimensional optimization problems have risen out of operations research, decision science, engineering, computer science and other related disciplines. The explosion in computing power continues to arouse extraordinary interest in stochastic search algorithms that require high computational speed and very large memories. A generic stochastic approach is that of evolutionary algorithms (EA). Such algorithms have been demonstrated to be very powerful and generally applicable for solving different single objective problems. Their fundamental algorithmic structures can also be applied to solving many multi-objective problems. In this book, the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and unique fashion, with detailed customized forms suggested for a variety of applications. Also, extensive MOEA discussion questions and possible research directions are presented at the end of each chapter. For additional information and supplementary teaching materials, please visit the authors' website at http://www.cs.cinvestav.mx/~EVOCINV/bookinfo.html.
Evolutionary Computation In Economics And Finance
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Author : S. H. Chen
language : en
Publisher:
Release Date : 2000
Evolutionary Computation In Economics And Finance written by S. H. Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Evolutionary Computation In Economics And Finance
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Author : Shu-Heng Chen
language : en
Publisher: Physica
Release Date : 2013-11-11
Evolutionary Computation In Economics And Finance written by Shu-Heng Chen and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.
After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.
Applications Of Computational Intelligence In Data Driven Trading
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Author : Cris Doloc
language : en
Publisher: John Wiley & Sons
Release Date : 2019-11-05
Applications Of Computational Intelligence In Data Driven Trading written by Cris Doloc and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-05 with Business & Economics categories.
“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.