Computational Intelligence Paradigms In Economic And Financial Decision Making
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Computational Intelligence Paradigms In Economic And Financial Decision Making
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Author : Marina Resta
language : en
Publisher: Springer
Release Date : 2015-10-14
Computational Intelligence Paradigms In Economic And Financial Decision Making written by Marina Resta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-14 with Technology & Engineering categories.
The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.
Financial Decision Making Using Computational Intelligence
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Author : Michael Doumpos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-23
Financial Decision Making Using Computational Intelligence written by Michael Doumpos 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 2012-07-23 with Business & Economics categories.
The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.
Perception Based Data Mining And Decision Making In Economics And Finance
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Author : Ildar Batyrshin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-15
Perception Based Data Mining And Decision Making In Economics And Finance written by Ildar Batyrshin 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 2007-03-15 with Computers categories.
The primary goal of this book is to present to the scientific and management communities a selection of applications using recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve some economics and financial problems that are of utmost importance. The book starts with a coverage of data mining tools and techniques that may be of use and significance for economic and financial analyses and applications. Notably, fuzzy and natural language based approaches and solutions for a more human consistent dealing with decision support, time series analysis, forecasting, clustering, etc. are discussed. The second part deals with various decision making models, particularly under probabilistic and fuzzy uncertainty, and their applications in solving a wide array of problems including portfolio optimization, option pricing, financial engineering, risk analysis etc. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.
Complex Decision Making In Economy And Finance
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Author : Pierre Massotte
language : en
Publisher: John Wiley & Sons
Release Date : 2020-01-09
Complex Decision Making In Economy And Finance written by Pierre Massotte 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 2020-01-09 with Business & Economics categories.
Pertinent to modern industry, administration, finance and society, the most pressing issue for firms today is how to reapproach the way we think and work in business. With topics ranging from improving productivity and coaxing economic growth after periods of market inactivity, Complex Decision-Making in Economy and Finance offers pragmatic solutions for dealing with the critical levels of disorder and chaos that have developed throughout the modern age. This book examines how to design complex products and systems, the benefits of collective intelligence and self-organization, and the best methods for handling risks in problematic environments. It also analyzes crises and how to manage them. This book is of benefit to companies and public bodies with regards to saving assets, reviving fortunes and laying the groundwork for robust, sustainable societal dividends. Examples, case studies, practical hints and guidelines illustrate the topics, particularly in finance.
Artificial Intelligence In Economics And Finance Theories
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Author : Tankiso Moloi
language : en
Publisher: Springer Nature
Release Date : 2020-05-07
Artificial Intelligence In Economics And Finance Theories written by Tankiso Moloi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-07 with Computers categories.
As Artificial Intelligence (AI) seizes all aspects of human life, there is a fundamental shift in the way in which humans are thinking of and doing things. Ordinarily, humans have relied on economics and finance theories to make sense of, and predict concepts such as comparative advantage, long run economic growth, lack or distortion of information and failures, role of labour as a factor of production and the decision making process for the purpose of allocating resources among other theories. Of interest though is that literature has not attempted to utilize these advances in technology in order to modernize economic and finance theories that are fundamental in the decision making process for the purpose of allocating scarce resources among other things. With the simulated intelligence in machines, which allows machines to act like humans and to some extent even anticipate events better than humans, thanks to their ability to handle massive data sets, this book will use artificial intelligence to explain what these economic and finance theories mean in the context of the agent wanting to make a decision. The main feature of finance and economic theories is that they try to eliminate the effects of uncertainties by attempting to bring the future to the present. The fundamentals of this statement is deeply rooted in risk and risk management. In behavioural sciences, economics as a discipline has always provided a well-established foundation for understanding uncertainties and what this means for decision making. Finance and economics have done this through different models which attempt to predict the future. On its part, risk management attempts to hedge or mitigate these uncertainties in order for “the planner” to reach the favourable outcome. This book focuses on how AI is to redefine certain important economic and financial theories that are specifically used for the purpose of eliminating uncertainties so as to allow agents to make informed decisions. In effect, certain aspects of finance and economic theories cannot be understood in their entirety without the incorporation of AI.
Computational Intelligence In Economics And Finance
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Author : Paul P. Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-11
Computational Intelligence In Economics And Finance written by Paul P. Wang 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 2007-07-11 with Computers categories.
Readers will find, in this highly relevant and groundbreaking book, research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Artificial Intelligence And Economic Theory Skynet In The Market
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Author : Tshilidzi Marwala
language : en
Publisher: Springer
Release Date : 2017-09-18
Artificial Intelligence And Economic Theory Skynet In The Market written by Tshilidzi Marwala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Computers categories.
This book theoretically and practically updates major economic ideas such as demand and supply, rational choice and expectations, bounded rationality, behavioral economics, information asymmetry, pricing, efficient market hypothesis, game theory, mechanism design, portfolio theory, causality and financial engineering in the age of significant advances in man-machine systems. The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence concepts such as the swarming of birds, the working of the brain and the pathfinding of the ants. Artificial Intelligence and Economic Theory: Skynet in the Market analyses the impact of artificial intelligence on economic theories, a subject that has not been studied. It also introduces new economic theories and these are rational counterfactuals and rational opportunity costs. These ideas are applied to diverse areas such as modelling of the stock market, credit scoring, HIV and interstate conflict. Artificial intelligence ideas used in this book include neural networks, particle swarm optimization, simulated annealing, fuzzy logic and genetic algorithms. It, furthermore, explores ideas in causality including Granger as well as the Pearl causality models.
Soft Computing In Economics And Finance
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Author : Ludmila Dymowa
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-21
Soft Computing In Economics And Finance written by Ludmila Dymowa 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 2011-01-21 with Technology & Engineering categories.
Currently the methods of Soft Computing are successfully used for risk analysis in: budgeting, e-commerce development, portfolio selection, Black-Scholes option pricing models, corporate acquisition systems, evaluating investments in advanced manufacturing technology, interactive fuzzy interval reasoning for smart web shopping, fuzzy scheduling and logistic. An essential feature of economic and financial problems it that there are always at least two criteria to be taken into account: profit maximization and risk minimization. Therefore, the economic and financial problems are multiple criteria ones. In this book, a new systematization of the problems of multiple criteria decision making is proposed which allows the author to reveal unsolved problems. The solutions of them are presented as well and implemented to deal with some important real-world problems such as investment project’s evaluation, tool steel material selection problem, stock screening and fuzzy logistic. It is well known that the best results in real -world applications can be obtained using the synthesis of modern methods of soft computing. Therefore, the developed by the author new approach to building effective stock trading systems, based on the synthesis of fuzzy logic and the Dempster-Shafer theory, seems to be a considerable contribution to the application of soft computing method in economics and finance. An important problem of capital budgeting is the fuzzy evaluation of the Internal Rate of Return. In this book, this problem is solved using a new method which makes it possible to solve linear and nonlinear interval and fuzzy equations and systems of them. The developed new method allows the author to obtain an effective solution of the Leontjev’s input-output problem in the interval setting.
Shifting Paradigms
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Author : Zia Qureshi
language : en
Publisher: Brookings Institution Press
Release Date : 2022-01-11
Shifting Paradigms written by Zia Qureshi and has been published by Brookings Institution Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-11 with Business & Economics categories.
Addressing the big questions about how technological change is transforming economies and societies Rapid technological change—likely to accelerate as a consequence of the COVID-19 pandemic—is reshaping economies and how they grow. But change also causes disruption, creates winners and losers, and produces social stress. This book examines the challenges of digital transformation and suggests how creative policies can make it more productive and inclusive. Shifting Paradigms is the second book on technological change produced by a joint research project of the Brookings Institution and the Korea Development Institute. Contributors are experts from the United States, Europe, and Korea. The first volume, Growth in a Time of Change, was published by Brookings in February 2020. The book's underlying thesis is that the future is arriving faster than expected. Long-accepted paradigms about economic growth are changing as digital technologies transform markets and nearly every aspect of business and work. Change will only intensify with advances in artificial intelligence and other innovations. Investors, business leaders, workers, and public officials face many questions. Is rising market concentration inevitable with the new technologies or can their benefits be more widely shared? How can the promise of FinTech be captured while managing risks? Should workers fear the new automation? Are technology-driven shifts in business and work causing income inequality to rise? How should public policy respond? Shifting Paradigms addresses these questions in an engaging manner for anyone interested in understanding how the economic and social agenda is being transformed by today's winds of change.
Applications Of Computational Intelligence In Data Driven Trading
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Author : Cris Doloc
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-29
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 2019-10-29 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.