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Artificial Markets Modeling

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Artificial Markets Modeling

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Author : Andrea Consiglio
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-27

Artificial Markets Modeling written by Andrea Consiglio 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 2007-08-27 with Business & Economics categories.

This volume features contributions to agent-based computational modeling from the social sciences and computer sciences. It presents applications of methodologies and tools, focusing on the uses, requirements, and constraints of agent-based models used by social scientists. Topics include agent-based macroeconomics, the emergence of norms and conventions, the dynamics of social and economic networks, and behavioral models in financial markets.

Artificial Intelligence For Financial Markets

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Author : Thomas Barrau
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Artificial Intelligence For Financial Markets written by Thomas Barrau and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Mathematics categories.

This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach. The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is described which combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians.

Agent Based Modeling

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Author : Norman Ehrentreich
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-30

Agent Based Modeling written by Norman Ehrentreich 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 2007-10-30 with Business & Economics categories.

This book reconciles the existence of technical trading with the Efficient Market Hypothesis. By analyzing a well-known agent-based model, the Santa Fe Institute Artificial Stock Market (SFI-ASM), it finds that when selective forces are weak, financial evolution cannot guarantee that only the fittest trading rules will survive. Its main contribution lies in the application of standard results from population genetics which have widely been neglected in the agent-based community.

Agent Based Modeling

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Author : Norman Ehrentreich
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-25

Economic Modeling Using Artificial Intelligence Methods

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Author : Tshilidzi Marwala
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-02

Economic Modeling Using Artificial Intelligence Methods written by Tshilidzi Marwala 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 2013-04-02 with Computers categories.

Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.

Artificial Intelligence In Financial Markets

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Author : Christian L. Dunis
language : en
Publisher: Springer
Release Date : 2016-11-21

Artificial Intelligence In Financial Markets written by Christian L. Dunis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Business & Economics categories.

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.

Complexity And Artificial Markets

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Author : Klaus Schredelseker
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-30

Complexity And Artificial Markets written by Klaus Schredelseker 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 2008-07-30 with Business & Economics categories.

In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences.

Artificial Intelligence For Capital Markets

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Author : Syed Hasan Jafar
language : en
Publisher: CRC Press
Release Date : 2023-05-15

Artificial Intelligence For Capital Markets written by Syed Hasan Jafar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-15 with Computers categories.

Artificial Intelligence for Capital Market throws light on the application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book. Features: Showcases artificial intelligence in finance service industry Explains credit and risk analysis Elaborates on cryptocurrencies and blockchain technology Focuses on the optimal choice of asset pricing model Introduces testing of market efficiency and forecasting in the Indian stock market This book serves as a reference book for academicians, industry professionals, traders, finance managers and stock brokers. It may also be used as textbook for graduate level courses in financial services and financial analytics.

Imitation Market Modeling In Digital Economy Game Theoretic Approaches

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Author : Elena G. Popkova
language : en
Publisher: Springer Nature
Release Date : 2022-01-21

Imitation Market Modeling In Digital Economy Game Theoretic Approaches written by Elena G. Popkova and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-21 with Technology & Engineering categories.

This book includes the best studies on the results of the International Scientific and Practical Conference “New behaviors of market players in the digital economy,” which was held by the Institute of Scientific Communications on July 8, 2021, online, in YouTube format. This book is devoted to the study of digital economy markets from the standpoint of various market players—society (consumers), entrepreneurship, and the state—from the standpoint of various sciences—economic, managerial, social, and legal—which ensures the multidisciplinarity of the book. The uniqueness of the book lies in the application of a new scientific and methodological approach to the study of digital economy markets—simulation modeling. The advantages of a game-based scientific and methodological approach to reducing the uncertainty of economic processes and systems—a combination of quantitative and qualitative analytical methods, a systematic consideration of economic processes and systems from a socio-economic point of view—make it especially suitable for studying digital economy markets. The book identifies the impact of globalization and digitalization on the modern economy and industry markets. The trends and features of the use of advanced technologies in the digital economy markets are studied. The modern practices of business management and business integration in the digital economy are considered. The foundations of economic security and sustainable development of markets and enterprises in the digital economy are revealed. The book is suitable for scientists studying the markets of the digital economy, who will find in it scientific and methodological recommendations and developments on the application of game theory, as well as ready simulation models of the digital economy markets.

Realistic Simulation Of Financial Markets

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Author : Hajime Kita
language : en
Publisher: Springer
Release Date : 2016-07-06

Realistic Simulation Of Financial Markets written by Hajime Kita and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-06 with Business & Economics categories.

This book takes up unique agent-based approaches to solving problems related to stock and their derivative markets. Toward this end, the authors have worked for more than 15 years on the development of an artificial market simulator called U-Mart for use as a research and educational tool. A noteworthy feature of the U-Mart simulator compared to other artificial market simulators is that U-Mart is an ultra-realistic artificial stock and their derivative market simulator. For example, it can simulate “arrowhead,” a next-generation trading system used in the Tokyo Stock Exchange and other major markets, as it takes into consideration the institutional design of the entire market. Another interesting feature of the U-Mart simulator is that it permits both human and computer programs to participate simultaneously as traders in the artificial market. In this book, first the details of U-Mart are explained, enabling readers to install and run the simulator on their computers for research and educational purposes. The simulator thus can be used for gaming simulation of the artificial market and even for users as agents to implement their own trading strategies for agent-based simulation (ABS).The book also presents selected research cases using the U-Mart simulator. Here, topics include automated acquisition of trading strategy using artificial intelligence techniques, evaluation of a market maker system to treat thin markets such as those for small and regional businesses, systemic risk analysis of the financial market considering institutional design of the market, and analysis of how humans behave and learn in gaming simulation. New perspectives on artificial market research are provided, and the power, potential, and challenge of ABS are discussed. As explained in this important work, ABS is considered to be an effective tool as the third approach of social science, an alternative to traditional literary and mathematical approaches.

Artificial Markets Modeling

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