Financial Decision Making Using Computational Intelligence
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| Author | : Michael Doumpos |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 336 |
| Release | : 2012-07-23 |
| Genre | : Business & Economics |
| ISBN | : 1461437733 |
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.
| Author | : Marina Resta |
| Publisher | : Springer |
| Total Pages | : 183 |
| Release | : 2015-10-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3319214403 |
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.
| Author | : Sergii Babichev |
| Publisher | : Springer Nature |
| Total Pages | : 805 |
| Release | : 2021-07-22 |
| Genre | : Technology & Engineering |
| ISBN | : 3030820149 |
This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis, and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning creates the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The book contains of 54 science papers which include the results of research concerning the current directions in the fields of data mining, machine learning, and decision making. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Complex Systems and Processes" contains of 26 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 13 papers. There are 15 papers in the third section "Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.
| Author | : Ildar Batyrshin |
| Publisher | : Springer |
| Total Pages | : 374 |
| Release | : 2007-04-05 |
| Genre | : Technology & Engineering |
| ISBN | : 3540362479 |
The primary goal of this book is to present to the scientific and management communities a selection of applications using more recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve the economics and financial problems. 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. Decision making in the present world is becoming more and more sophisticated, time consuming and difficult for human beings who require more and more computational support. This book addresses the significant increase on research and applications of Soft Computing and Computing with Words and Perceptions for decision making in Economics and Finance in recent years. Decision making is heavily based on information and knowledge usually extracted from the analysis of large amounts of data. Data mining techniques enabled with the capability to integrate human experience could be used for a more realistic business decision support. Computing with Words and Perceptions introduced by Lotfi Zadeh, can serve as a basis for such extension of traditional data mining and decision making systems. Fuzzy logic as a main constituent of CWP gives powerful tools for modeling and processing linguistic information defined on numerical domain.
| Author | : Ajay Agrawal |
| Publisher | : University of Chicago Press |
| Total Pages | : 172 |
| Release | : 2024-03-05 |
| Genre | : Business & Economics |
| ISBN | : 0226833127 |
A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
| Author | : Erricos John Kontoghiorghes |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 626 |
| Release | : 2013-11-11 |
| Genre | : Business & Economics |
| ISBN | : 1475736134 |
Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.
| Author | : Zhengxin Chen |
| Publisher | : CRC Press |
| Total Pages | : 408 |
| Release | : 1999-11-24 |
| Genre | : Computers |
| ISBN | : 9781420049145 |
Intelligent decision support relies on techniques from a variety of disciplines, including artificial intelligence and database management systems. Most of the existing literature neglects the relationship between these disciplines. By integrating AI and DBMS, Computational Intelligence for Decision Support produces what other texts don't: an explanation of how to use AI and DBMS together to achieve high-level decision making. Threading relevant disciplines from both science and industry, the author approaches computational intelligence as the science developed for decision support. The use of computational intelligence for reasoning and DBMS for retrieval brings about a more active role for computational intelligence in decision support, and merges computational intelligence and DBMS. The introductory chapter on technical aspects makes the material accessible, with or without a decision support background. The examples illustrate the large number of applications and an annotated bibliography allows you to easily delve into subjects of greater interest. The integrated perspective creates a book that is, all at once, technical, comprehensible, and usable. Now, more than ever, it is important for science and business workers to creatively combine their knowledge to generate effective, fruitful decision support. Computational Intelligence for Decision Support makes this task manageable.
| Author | : Constantin Zopounidis |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 230 |
| Release | : 2013-11-27 |
| Genre | : Computers |
| ISBN | : 146154663X |
This book provides a new point of view on the field of financial engineering, through the application of multicriteria intelligent decision aiding systems. The aim of the book is to provide a review of the research in the area and to explore the adequacy of the tools and systems developed according to this innovative approach in addressing complex financial decision problems, encountered within the field of financial engineering. Audience: Researchers and professionals such as financial managers, financial engineers, investors, operations research specialists, computer scientists, management scientists and economists.
| Author | : Christian L. Dunis |
| Publisher | : Springer |
| Total Pages | : 349 |
| Release | : 2016-11-21 |
| Genre | : Business & Economics |
| ISBN | : 1137488808 |
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
| Author | : Tankiso Moloi |
| Publisher | : Springer Nature |
| Total Pages | : 131 |
| Release | : 2020-05-07 |
| Genre | : Computers |
| ISBN | : 3030429628 |
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.
