Artificial Markets Modeling
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Agent Based Modeling
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Author : Norman Ehrentreich
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-25
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 2007-10-25 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.
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 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.
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.
Explainable Artificial Intelligence Based On Neuro Fuzzy Modeling With Applications In Finance
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Author : Tom Rutkowski
language : en
Publisher: Springer Nature
Release Date : 2021-06-07
Explainable Artificial Intelligence Based On Neuro Fuzzy Modeling With Applications In Finance written by Tom Rutkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-07 with Technology & Engineering categories.
The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules. The main part of the book is devoted to a very challenging problem of stock market recommendations. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers.
Artificial Economics
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Author : Ruben Mercado
language : en
Publisher: Cambridge University Press
Release Date : 2021-11-04
Artificial Economics written by Ruben Mercado and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-04 with Business & Economics categories.
An introductory overview of the methods, models and interdisciplinary links of artificial economics. Addresses the differences between the assumptions and methods of artificial economics and those of mainstream economics. This is one of the first books to fully address, in an intuitive and conceptual form, this new way of doing economics.
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.
The Economics Of Artificial Intelligence
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Author : Ajay Agrawal
language : en
Publisher: University of Chicago Press
Release Date : 2024-03-14
The Economics Of Artificial Intelligence written by Ajay Agrawal and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-14 with Business & Economics categories.
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.
Foreign Exchange Rate Forecasting With Artificial Neural Networks
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Author : Lean Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-02
Foreign Exchange Rate Forecasting With Artificial Neural Networks 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 2007-08-02 with Business & Economics categories.
The book focuses on forecasting foreign exchange rates via artificial neural networks. It creates and applies the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange-rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges. Foreign Exchange Rate Forecasting with Artificial Neural Networks is targeted at both the academic and practitioner audiences. Managers, analysts and technical practitioners in financial institutions across the world will have considerable interest in the book, and scholars and graduate students studying financial markets and business forecast will also have considerable interest in the book. The book discusses the most important advances in foreign-exchange-rate forecasting and then systematically develops a number of new, innovative, and creatively crafted neural network models that reduce the volatility and speculative risk in the forecasting of foreign exchange rates. The book discusses and illustrates three general types of ANN models. Each of these model types reflect the following innovative and effective characteristics: (1) The first model type is a three-layer, feed-forward neural network with instantaneous learning rates and adaptive momentum factors that produce learning algorithms (both online and offline algorithms) to predict foreign exchange rates. (2) The second model type is the three innovative hybrid learning algorithms that have been created by combining ANNs with exponential smoothing, generalized linear auto-regression, and genetic algorithms. Each of these three hybrid algorithms has been crafted to forecast various aspects synergetic performance. (3) The third model type is the three innovative ensemble learning algorithms that combining multiple neural networks into an ensemble output. Empirical results reveal that these creative models can produce better performance with high accuracy or high efficiency.
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.