Financial Decision Making Using Computational Intelligence
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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.
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.
Perception Based Data Mining And Decision Making In Economics And Finance
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Author : Ildar Batyrshin
language : en
Publisher: Springer
Release Date : 2007-04-05
Perception Based Data Mining And Decision Making In Economics And Finance written by Ildar Batyrshin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-05 with Technology & Engineering categories.
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.
Intelligent Decision Aiding Systems Based On Multiple Criteria For Financial Engineering
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Author : Constantin Zopounidis
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-27
Intelligent Decision Aiding Systems Based On Multiple Criteria For Financial Engineering written by Constantin Zopounidis 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 2013-11-27 with Computers categories.
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.
Lecture Notes In Computational Intelligence And Decision Making
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Author : Sergii Babichev
language : en
Publisher: Springer Nature
Release Date : 2021-07-22
Lecture Notes In Computational Intelligence And Decision Making written by Sergii Babichev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-22 with Technology & Engineering categories.
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.
Computational Methods In Decision Making Economics And Finance
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Author : Erricos John Kontoghiorghes
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Computational Methods In Decision Making Economics And Finance written by Erricos John Kontoghiorghes 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 2013-11-11 with Business & Economics categories.
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.
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.
Artificial Intelligence Ai And Finance
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Author : Bahaaeddin A. M. Alareeni
language : en
Publisher: Springer Nature
Release Date : 2023-08-26
Artificial Intelligence Ai And Finance written by Bahaaeddin A. M. Alareeni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-26 with Technology & Engineering categories.
Artificial intelligence (AI) has the potential to significantly improve efficiency, reduce costs, and increase the speed and accuracy of financial decision-making, making it an increasingly important tool for financial professionals. One way that AI can improve efficiency in finance is by automating tasks and processes that are time-consuming and repetitive for humans. For example, AI algorithms can be used to analyze and process large amounts of data, such as financial statements and market data, in a fraction of the time that it would take a human to do so. This can allow financial professionals to focus on higher-value tasks, such as interpreting data and making strategic decisions, rather than being bogged down by mundane tasks. AI can also reduce costs in finance by increasing automation and eliminating the need for certain tasks to be performed manually. This can result in cost savings for financial institutions, which can then be passed on to customers in the form of lower fees or better services. AI can be used to identify unusual patterns of activity that may indicate fraudulent behavior. This can help financial institutions reduce losses from fraud and improve customer security. AI-powered chatbots and virtual assistants can help financial institutions provide faster, more efficient customer service, particularly when it comes to answering common questions and handling routine tasks. Some financial institutions are using AI to analyze market data and make trades in real-time. AI-powered trading algorithms can potentially make faster and more accurate trading decisions than humans. In terms of speed and accuracy, AI algorithms can analyze data and make decisions much faster than humans, and can do so with a high degree of accuracy. This can be particularly useful in fast-moving financial markets, where quick and accurate decision-making can be the difference between success and failure. This book highlights how AI in finance can improve efficiency, reduce costs, and increase the speed and accuracy of financial decision-making. Moreover, the book also focuses on how to ensure the responsible and ethical use of AI in finance. This book is a valuable resource for students, scholars, academicians, researchers, professionals, executives, government agencies, and policymakers interested in exploring the role of artificial intelligence (AI) in finance. Its goal is to provide a comprehensive overview of the latest research and knowledge in this area, and to stimulate further inquiry and exploration.
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.
Bio Inspired Credit Risk Analysis
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Author : Lean Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-24
Bio Inspired Credit Risk Analysis written by Lean Yu 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 2008-04-24 with Business & Economics categories.
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.