Artificial Intelligence Learning And Computation In Economics And Finance

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Artificial Intelligence, Learning and Computation in Economics and Finance

Author : Ragupathy Venkatachalam
Publisher : Springer Nature
ISBN 13 : 3031152948
Total Pages : 331 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Artificial Intelligence, Learning and Computation in Economics and Finance by : Ragupathy Venkatachalam

Download or read book Artificial Intelligence, Learning and Computation in Economics and Finance written by Ragupathy Venkatachalam and published by Springer Nature. This book was released on 2023-02-15 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded. Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools. The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.

Computational Intelligence in Economics and Finance

Author : Paul P. Wang
Publisher : Springer Science & Business Media
ISBN 13 : 354072821X
Total Pages : 232 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Computational Intelligence in Economics and Finance by : Paul P. Wang

Download or read book Computational Intelligence in Economics and Finance written by Paul P. Wang and published by Springer Science & Business Media. This book was released on 2007-07-11 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readers will find, in this highly relevant and groundbreaking book, research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.

Machine Learning for Economics and Finance in TensorFlow 2

Author : Isaiah Hull
Publisher : Apress
ISBN 13 : 9781484263723
Total Pages : 368 pages
Book Rating : 4.2/5 (637 download)

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Book Synopsis Machine Learning for Economics and Finance in TensorFlow 2 by : Isaiah Hull

Download or read book Machine Learning for Economics and Finance in TensorFlow 2 written by Isaiah Hull and published by Apress. This book was released on 2020-11-26 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work in economics is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction and is generally uninterested in either causality or parsimony. That leaves a gap for both students and professionals in the economics industry without a standard reference. This book focuses on economic problems with an empirical dimension, where machine learning methods may offer something of value. This includes coverage of a variety of discriminative deep learning models (DNNs, CNNs, RNNs, LSTMs, the Transformer Model, etc.), generative machine learning models, random forests, gradient boosting, clustering, and feature extraction. You'll also learn about the intersection of empirical methods in economics and machine learning, including regression analysis, text analysis, and dimensionality reduction methods, such as principal components analysis. TensorFlow offers a toolset that can be used to setup and solve any mathematical model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each framed in terms of a specific economic problem of interest or topic. Otherwise complicated content is then distilled into accessible examples, so you can use TensorFlow to solve workhorse models in economics and finance. What You'll Learn Define, train, and evaluate machine learning models in TensorFlow 2 Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems Solve workhorse models in economics and finance Who This Book Is For Students and data scientists working in the economics industry. Academic economists and social scientists who have an interest in machine learning are also likely to find this book useful.

The Essentials of Machine Learning in Finance and Accounting

Author : Mohammad Zoynul Abedin
Publisher : Routledge
ISBN 13 : 1000394123
Total Pages : 275 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis The Essentials of Machine Learning in Finance and Accounting by : Mohammad Zoynul Abedin

Download or read book The Essentials of Machine Learning in Finance and Accounting written by Mohammad Zoynul Abedin and published by Routledge. This book was released on 2021-06-20 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

Artificial Intelligence in Economics and Finance Theories

Author : Tankiso Moloi
Publisher : Springer Nature
ISBN 13 : 3030429628
Total Pages : 131 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Artificial Intelligence in Economics and Finance Theories by : Tankiso Moloi

Download or read book Artificial Intelligence in Economics and Finance Theories written by Tankiso Moloi and published by Springer Nature. This book was released on 2020-05-07 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and Economic Theory: Skynet in the Market

Author : Tshilidzi Marwala
Publisher : Springer
ISBN 13 : 3319661043
Total Pages : 204 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Artificial Intelligence and Economic Theory: Skynet in the Market by : Tshilidzi Marwala

Download or read book Artificial Intelligence and Economic Theory: Skynet in the Market written by Tshilidzi Marwala and published by Springer. This book was released on 2017-09-18 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Author : El Bachir Boukherouaa
Publisher : International Monetary Fund
ISBN 13 : 1589063953
Total Pages : 35 pages
Book Rating : 4.5/5 (89 download)

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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.

Artificial Intelligence in Finance

Author : Yves Hilpisch
Publisher : O'Reilly Media
ISBN 13 : 1492055409
Total Pages : 477 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Artificial Intelligence in Finance by : Yves Hilpisch

Download or read book Artificial Intelligence in Finance written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-10-14 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about

Computational Intelligence in Economics and Finance

Author : Paul P. Wang
Publisher : Springer Science & Business Media
ISBN 13 : 3662063735
Total Pages : 489 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Computational Intelligence in Economics and Finance by : Paul P. Wang

Download or read book Computational Intelligence in Economics and Finance written by Paul P. Wang and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.

Computational Economics: A Perspective from Computational Intelligence

Author : Chen, Shu-Heng
Publisher : IGI Global
ISBN 13 : 159140651X
Total Pages : 318 pages
Book Rating : 4.5/5 (914 download)

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Book Synopsis Computational Economics: A Perspective from Computational Intelligence by : Chen, Shu-Heng

Download or read book Computational Economics: A Perspective from Computational Intelligence written by Chen, Shu-Heng and published by IGI Global. This book was released on 2005-11-30 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book identifies the economic as well as financial problems that may be solved efficiently with computational methods and explains why those problems should best be solved with computational methods"--Provided by publisher.

Advances in Artificial Intelligence in Economics, Finance, and Management

Author : John D. Johnson
Publisher :
ISBN 13 : 9781559381277
Total Pages : 202 pages
Book Rating : 4.3/5 (812 download)

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Book Synopsis Advances in Artificial Intelligence in Economics, Finance, and Management by : John D. Johnson

Download or read book Advances in Artificial Intelligence in Economics, Finance, and Management written by John D. Johnson and published by . This book was released on 1994 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part of a series on advances in artificial intelligence in economics, finance and management, this first volume discusses such topics as: artificial neural systems; the economic theory foundation for neural computing systems; and neural network of managerial judgement; among other topics.

The Economics of Artificial Intelligence

Author : Ajay Agrawal
Publisher : University of Chicago Press
ISBN 13 : 022661333X
Total Pages : 643 pages
Book Rating : 4.2/5 (266 download)

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Book Synopsis The Economics of Artificial Intelligence by : Ajay Agrawal

Download or read book The Economics of Artificial Intelligence written by Ajay Agrawal and published by University of Chicago Press. This book was released on 2019-05-22 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors: Daron Acemoglu, Massachusetts Institute of Technology Philippe Aghion, Collège de France Ajay Agrawal, University of Toronto Susan Athey, Stanford University James Bessen, Boston University School of Law Erik Brynjolfsson, MIT Sloan School of Management Colin F. Camerer, California Institute of Technology Judith Chevalier, Yale School of Management Iain M. Cockburn, Boston University Tyler Cowen, George Mason University Jason Furman, Harvard Kennedy School Patrick Francois, University of British Columbia Alberto Galasso, University of Toronto Joshua Gans, University of Toronto Avi Goldfarb, University of Toronto Austan Goolsbee, University of Chicago Booth School of Business Rebecca Henderson, Harvard Business School Ginger Zhe Jin, University of Maryland Benjamin F. Jones, Northwestern University Charles I. Jones, Stanford University Daniel Kahneman, Princeton University Anton Korinek, Johns Hopkins University Mara Lederman, University of Toronto Hong Luo, Harvard Business School John McHale, National University of Ireland Paul R. Milgrom, Stanford University Matthew Mitchell, University of Toronto Alexander Oettl, Georgia Institute of Technology Andrea Prat, Columbia Business School Manav Raj, New York University Pascual Restrepo, Boston University Daniel Rock, MIT Sloan School of Management Jeffrey D. Sachs, Columbia University Robert Seamans, New York University Scott Stern, MIT Sloan School of Management Betsey Stevenson, University of Michigan Joseph E. Stiglitz. Columbia University Chad Syverson, University of Chicago Booth School of Business Matt Taddy, University of Chicago Booth School of Business Steven Tadelis, University of California, Berkeley Manuel Trajtenberg, Tel Aviv University Daniel Trefler, University of Toronto Catherine Tucker, MIT Sloan School of Management Hal Varian, University of California, Berkeley

Computational Economics

Author : Shu-Heng Chen
Publisher : IGI Global
ISBN 13 : 1591406498
Total Pages : 339 pages
Book Rating : 4.5/5 (914 download)

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Book Synopsis Computational Economics by : Shu-Heng Chen

Download or read book Computational Economics written by Shu-Heng Chen and published by IGI Global. This book was released on 2006-01-01 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book identifies the economic as well as financial problems that may be solved efficiently with computational methods and explains why those problems should best be solved with computational methods"--Provided by publisher.

Artificial Intelligence in Financial Markets

Author : Christian L. Dunis
Publisher : Springer
ISBN 13 : 1137488808
Total Pages : 349 pages
Book Rating : 4.1/5 (374 download)

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Book Synopsis Artificial Intelligence in Financial Markets by : Christian L. Dunis

Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Intelligence and Financial Behaviour

Author : Riccardo Viale
Publisher : Edward Elgar Publishing
ISBN 13 : 1803923156
Total Pages : 267 pages
Book Rating : 4.8/5 (39 download)

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Book Synopsis Artificial Intelligence and Financial Behaviour by : Riccardo Viale

Download or read book Artificial Intelligence and Financial Behaviour written by Riccardo Viale and published by Edward Elgar Publishing. This book was released on 2023-06-01 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following rapid technological advancements that have taken place throughout the late twentieth and early twenty-first centuries, this intriguing book provides a dynamic agenda for the study of artificial intelligence (AI) within finance. Through an in-depth consideration of the use of AI, it utilizes case study examples to investigate AI’s effectiveness within investment and banking.

Finance & Development, December 2023

Author : International Monetary Fund. Communications Department
Publisher : International Monetary Fund
ISBN 13 :
Total Pages : 81 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Finance & Development, December 2023 by : International Monetary Fund. Communications Department

Download or read book Finance & Development, December 2023 written by International Monetary Fund. Communications Department and published by International Monetary Fund. This book was released on 2023-11-30 with total page 81 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI has introduced tantalizing new possibilities. Yet the initial excitement surrounding AI has given way to genuine concerns. This issue is an early attempt to understand AI’s implications for growth, jobs, inequality, and finance.

Evolutionary Computation in Economics and Finance

Author : Shu-Heng Chen
Publisher : Physica
ISBN 13 : 3790817848
Total Pages : 459 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Evolutionary Computation in Economics and Finance by : Shu-Heng Chen

Download or read book Evolutionary Computation in Economics and Finance written by Shu-Heng Chen and published by Physica. This book was released on 2013-11-11 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.