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Market Efficiency And Learning In An Artificial Stock Market
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Book Synopsis Agent-Based Modeling by : Norman Ehrentreich
Download or read book Agent-Based Modeling written by Norman Ehrentreich and published by Springer Science & Business Media. This book was released on 2007-10-30 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Issues in Finance, Business, and Economics Research: 2011 Edition by :
Download or read book Issues in Finance, Business, and Economics Research: 2011 Edition written by and published by ScholarlyEditions. This book was released on 2012-01-09 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Finance, Business, and Economics Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Finance, Business, and Economics Research. The editors have built Issues in Finance, Business, and Economics Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Finance, Business, and Economics Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Finance, Business, and Economics Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Book Synopsis Understanding Machine Learning by : Shai Shalev-Shwartz
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Book Synopsis Choosing Leadership by : Linda Ginzel
Download or read book Choosing Leadership written by Linda Ginzel and published by Agate Publishing. This book was released on 2018-10-16 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Choosing Leadership is a new take on executive development that gives everyone the tools to develop their leadership skills. In this workbook, Dr. Linda Ginzel, a clinical professor at the University of Chicago’s Booth School of Business and a social psychologist, debunks common myths about leaders and encourages you to follow a personalized path to decide when to manage and when to lead. Thoughtful exercises and activities help you mine your own experiences, learn to recognize behavior patterns, and make better choices so that you can create better futures. You’ll learn how to: Define leadership for yourself and move beyond stereotypes Distinguish between leadership and management and when to use each skill Recognize the gist of a situation and effectively communicate it with others Learn from the experience of others as well as your own Identify your “default settings” and become your own coach And much more Dr. Linda Ginzel is a clinical professor of managerial psychology at the University of Chicago’s Booth School of Business and the founder of its customized executive education program. For three decades, she has developed and taught MBA and executive education courses in negotiation, leadership capital, managerial psychology, and more. She has also taught MBA and PhD students at Northwestern and Stanford, as well as designed customized educational programs for a number of Fortune 500 companies. Ginzel has received numerous teaching awards for excellence in MBA education, as well as the President’s Service Award for her work with the nonprofit Kids In Danger. She lives in Chicago with her family.
Book Synopsis AI and Financial Markets by : Shigeyuki Hamori
Download or read book AI and Financial Markets written by Shigeyuki Hamori and published by MDPI. This book was released on 2020-07-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.
Book Synopsis Deep Learning Tools for Predicting Stock Market Movements by : Renuka Sharma
Download or read book Deep Learning Tools for Predicting Stock Market Movements written by Renuka Sharma and published by John Wiley & Sons. This book was released on 2024-04-10 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS The book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds. The book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. The book: details the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average; explains the rapid expansion of quantum computing technologies in financial systems; provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions; explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers. Audience The book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies.
Book Synopsis Artificial Intelligence for Capital Markets by : Syed Hasan Jafar
Download or read book Artificial Intelligence for Capital Markets written by Syed Hasan Jafar and published by CRC Press. This book was released on 2023-05-15 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance by : El Bachir Boukherouaa
Download or read book Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Prediction of Stock Market Index Movements with Machine Learning by : Nazif AYYILDIZ
Download or read book Prediction of Stock Market Index Movements with Machine Learning written by Nazif AYYILDIZ and published by Özgür Publications. This book was released on 2023-12-16 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book titled "Prediction of Stock Market Index Movements with Machine Learning" focuses on the performance of machine learning methods in forecasting the future movements of stock market indexes and identifying the most advantageous methods that can be used across different stock exchanges. In this context, applications have been conducted on both developed and emerging market stock exchanges. The stock market indexes of developed countries such as NYSE 100, NIKKEI 225, FTSE 100, CAC 40, DAX 30, FTSE MIB, TSX; and the stock market indexes of emerging countries such as SSE, BOVESPA, RTS, NIFTY 50, IDX, IPC, and BIST 100 were selected. The movement directions of these stock market indexes were predicted using decision trees, random forests, k-nearest neighbors, naive Bayes, logistic regression, support vector machines, and artificial neural networks methods. Daily dataset from 01.01.2012 to 31.12.2021, along with technical indicators, were used as input data for analysis. According to the results obtained, it was determined that artificial neural networks were the most effective method during the examined period. Alongside artificial neural networks, logistic regression and support vector machines methods were found to predict the movement direction of all indexes with an accuracy of over 70%. Additionally, it was noted that while artificial neural networks were identified as the best method, they did not necessarily achieve the highest accuracy for all indexes. In this context, it was established that the performance of the examined methods varied among countries and indexes but did not differ based on the development levels of the countries. As a conclusion, artificial neural networks, logistic regression, and support vector machines methods are recommended as the most advantageous approaches for predicting stock market index movements.
Book Synopsis Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network by : Joish Bosco
Download or read book Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network written by Joish Bosco and published by GRIN Verlag. This book was released on 2018-09-18 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.
Download or read book Adaptive Markets written by Andrew W. Lo and published by Princeton University Press. This book was released on 2019-05-14 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new, evolutionary explanation of markets and investor behavior Half of all Americans have money in the stock market, yet economists can’t agree on whether investors and markets are rational and efficient, as modern financial theory assumes, or irrational and inefficient, as behavioral economists believe. The debate is one of the biggest in economics, and the value or futility of investment management and financial regulation hangs on the answer. In this groundbreaking book, Andrew Lo transforms the debate with a powerful new framework in which rationality and irrationality coexist—the Adaptive Markets Hypothesis. Drawing on psychology, evolutionary biology, neuroscience, artificial intelligence, and other fields, Adaptive Markets shows that the theory of market efficiency is incomplete. When markets are unstable, investors react instinctively, creating inefficiencies for others to exploit. Lo’s new paradigm explains how financial evolution shapes behavior and markets at the speed of thought—a fact revealed by swings between stability and crisis, profit and loss, and innovation and regulation. An ambitious new answer to fundamental questions about economics and investing, Adaptive Markets is essential reading for anyone who wants to understand how markets really work.
Book Synopsis Handbook of Research on Theory and Practice of Global Islamic Finance by : Rafay, Abdul
Download or read book Handbook of Research on Theory and Practice of Global Islamic Finance written by Rafay, Abdul and published by IGI Global. This book was released on 2019-12-27 with total page 888 pages. Available in PDF, EPUB and Kindle. Book excerpt: As an emerging global phenomenon, Islamic economics and the financial system has expanded exponentially in recent decades. Many components of the industry are still unknown, but hopefully, the lack of awareness will soon be stilled. The Handbook of Research on Theory and Practice of Global Islamic Finance provides emerging research on the latest global Islamic economic practices. The content within this publication examines risk management, economic justice, and stock market analysis. It is designed for financiers, banking professionals, economists, policymakers, researchers, academicians, and students interested in ideas centered on the development and practice of Islamic finance.
Book Synopsis Complex Systems in Finance and Econometrics by : Robert A. Meyers
Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.
Book Synopsis Rational Machines and Artificial Intelligence by : Tshilidzi Marwala
Download or read book Rational Machines and Artificial Intelligence written by Tshilidzi Marwala and published by Academic Press. This book was released on 2021-03-31 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. - Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? - Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions - Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets - Discusses the application of Moore's Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality
Book Synopsis Meeting the Challenge of Social Problems via Agent-Based Simulation by : T. Terano
Download or read book Meeting the Challenge of Social Problems via Agent-Based Simulation written by T. Terano and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series of international workshops on Agent-Based Approaches in Economic and Social Complex Systems (AESCS) is part of the worldwide activities on computational social and organizational sciences. The second workshop, AESCS ’02, focusing on progress of agent-based simulation was held in Tokyo in August 2002. AESCS ’02 explored the frontiers of the field. The importance of cumulative progress was emphasized in discussions of common tasks, standard computational models, replication and validation issues, and evaluation and verification criteria. Promoting multidisciplinary work in computational economics, organizational science, social dynamics, and complex systems, AESCS ’02 brought together researchers from diverse fields. This book contains the invited papers by Robert Axtell, Shu-Heng Chen, and Takao Terano, along with selected papers collected in three major sections: Economic Systems, Marketing and Management, and Social Systems and Methodology.
Book Synopsis Agent-Based Computational Economics by : Shu-Heng Chen
Download or read book Agent-Based Computational Economics written by Shu-Heng Chen and published by Routledge. This book was released on 2017-09-19 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to answer two questions that are fundamental to the study of agent-based economic models: what is agent-based computational economics and why do we need agent-based economic modelling of economy? This book provides a review of the development of agent-based computational economics (ACE) from a perspective on how artificial economic agents are designed under the influences of complex sciences, experimental economics, artificial intelligence, evolutionary biology, psychology, anthropology and neuroscience. This book begins with a historical review of ACE by tracing its origins. From a modelling viewpoint, ACE brings truly decentralized procedures into market analysis, from a single market to the whole economy. This book also reviews how experimental economics and artificial intelligence have shaped the development of ACE. For the former, the book discusses how ACE models can be used to analyse the economic consequences of cognitive capacity, personality and cultural inheritance. For the latter, the book covers the various tools used to construct artificial adaptive agents, including reinforcement learning, fuzzy decision rules, neural networks, and evolutionary computation. This book will be of interest to graduate students researching computational economics, experimental economics, behavioural economics, and research methodology.
Book Synopsis Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) by : Jerome Yen
Download or read book Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) written by Jerome Yen and published by Springer Nature. This book was released on 2023-07-25 with total page 1595 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book.With the rapid development of modern economy and Internet technology, the traditional financial industry has to develop Internet finance to provide better services and meet the needs of the times. It is against this background that the blockchain, relying on its special advantages (collective maintenance, reliable databases, and decentralization), provides the reliability to solve the credit risk of Internet finance, has an impact on institutions, trust mechanisms, risk control, etc. in the Internet finance industry, and has derived more new application scenarios, thus paving the way for the development of finance in the Internet era. Applying blockchain technology to the financial field can promote data information sharing, improve value transmission efficiency, and enhance database security. The financial market based on the decentralized system of blockchain technology can reduce the operating costs of financial institutions, improve economic efficiency, and solve problems such as information asymmetry. The new financial business model of "blockchain+finance" is conducive to improving the Internet credit reporting system, preventing and controlling Internet financial risks, and further realizing "financial disintermediation". At present, in China's financial field, blockchain technology has been applied and innovated in supply chain finance, cross-border payment, trade finance, asset securitization and other scenarios. To promote the exchange and development of blockchain, information technology and financial experts and scholars. The 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023) will be held in Hangzhou from February 17 to 19, 2023. This conference mainly focuses on the latest research on "blockchain, information technology and smart finance". This conference brings together experts, scholars, researchers and relevant practitioners in this field from all over the world to share research results, discuss hot issues, and provide participants with cutting-edge scientific and technological information, so that you can timely understand the development trends of the industry and master the latest technologies, broaden research horizons and promote academic progress.
