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Author: Norman Ehrentreich
Publisher: Springer Science & Business Media
ISBN: 3540738789
Category : Business & Economics
Languages : en
Pages : 238
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Book Description
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.
Author: Norman Ehrentreich
Publisher: Springer Science & Business Media
ISBN: 3540738789
Category : Business & Economics
Languages : en
Pages : 238
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Book Description
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.
Author: Shu-Heng Chen
Publisher: Oxford University Press
ISBN: 0190877502
Category : Business & Economics
Languages : en
Pages : 785
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Book Description
The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.
Author: Tshilidzi Marwala
Publisher: Springer Science & Business Media
ISBN: 1447150104
Category : Computers
Languages : en
Pages : 271
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Book Description
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.
Author: Christian L. Dunis
Publisher: Springer
ISBN: 1137488808
Category : Business & Economics
Languages : en
Pages : 349
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Book Description
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: Sjoukje Osinga
Publisher: Springer Science & Business Media
ISBN: 3642211089
Category : Business & Economics
Languages : en
Pages : 226
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Book Description
Artificial economics is a computational approach that aims to explain economic systems by modeling them as societies of intelligent software agents. The individual agents make autonomous decisions, but their actual behaviors are constrained by available resources, other individuals' behaviors, and institutions. Intelligent software agents have communicative skills that enable simulation of negotiation, trade, reputation, and other forms of knowledge transfer that are at the basis of economic life. Incorporated learning mechanisms may adapt the agents' behaviors. In artificial economics, all system behavior is generated from the individual agents' simulated decisions; no system level laws are a priori imposed. For instance, price convergence and market clearing may emerge, but not necessarily. Thus, artificial economics facilitates the study of the mechanisms that make the economy function. This book presents a selection of peer-reviewed papers addressing recent developments in this field between economics and computer science.
Author: Klaus Schredelseker
Publisher: Springer Science & Business Media
ISBN: 3540705562
Category : Business & Economics
Languages : en
Pages : 235
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Book Description
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.
Author: Ruben Mercado
Publisher: Cambridge University Press
ISBN: 1316517098
Category : Business & Economics
Languages : en
Pages : 197
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Book Description
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.
Author: Ondrej Martinsky
Publisher: Harriman House Limited
ISBN: 1906659532
Category : Business & Economics
Languages : en
Pages : 212
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Book Description
This work deals with the issue of problematic market price prediction in the context of crowd behavior. "Intelligent Trading Systems" describes technical analysis methods used to predict price movements.
Author: Ajay Agrawal
Publisher: University of Chicago Press
ISBN: 0226833127
Category : Business & Economics
Languages : en
Pages : 172
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Book Description
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: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35
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Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
