Applications Of Computational Intelligence In Data Driven Trading

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Applications of Computational Intelligence in Data-Driven Trading

Cris Doloc
Applications of Computational Intelligence in Data Driven Trading Book PDF

Author : Cris Doloc
Publisher : John Wiley & Sons
Page : 304 pages
File Size : 49,6 Mb
Release : 2019-10-29
Category : Business & Economics
ISBN : 9781119550501

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Applications of Computational Intelligence in Data-Driven Trading by Cris Doloc Pdf

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.

Computational Intelligence Techniques for Trading and Investment

Christian Dunis,Spiros Likothanassis,Andreas Karathanasopoulos,Georgios Sermpinis,Konstantinos Theofilatos
Computational Intelligence Techniques for Trading and Investment Book PDF

Author : Christian Dunis,Spiros Likothanassis,Andreas Karathanasopoulos,Georgios Sermpinis,Konstantinos Theofilatos
Publisher : Routledge
Page : 239 pages
File Size : 54,8 Mb
Release : 2014-03-26
Category : Business & Economics
ISBN : 9781136195112

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Computational Intelligence Techniques for Trading and Investment by Christian Dunis,Spiros Likothanassis,Andreas Karathanasopoulos,Georgios Sermpinis,Konstantinos Theofilatos Pdf

Computational intelligence, a sub-branch of artificial intelligence, is a field which draws on the natural world and adaptive mechanisms in order to study behaviour in changing complex environments. This book provides an interdisciplinary view of current technological advances and challenges concerning the application of computational intelligence techniques to financial time-series forecasting, trading and investment. The book is divided into five parts. The first part introduces the most important computational intelligence and financial trading concepts, while also presenting the most important methodologies from these different domains. The second part is devoted to the application of traditional computational intelligence techniques to the fields of financial forecasting and trading, and the third part explores the applications of artificial neural networks in these domains. The fourth part delves into novel evolutionary-based hybrid methodologies for trading and portfolio management, while the fifth part presents the applications of advanced computational intelligence modelling techniques in financial forecasting and trading. This volume will be useful for graduate and postgraduate students of finance, computational finance, financial engineering and computer science. Practitioners, traders and financial analysts will also benefit from this book.

Financial Data Resampling for Machine Learning Based Trading

Tomé Almeida Borges,Rui Neves
Financial Data Resampling for Machine Learning Based Trading Book PDF

Author : Tomé Almeida Borges,Rui Neves
Publisher : Springer Nature
Page : 93 pages
File Size : 46,9 Mb
Release : 2021-02-22
Category : Mathematics
ISBN : 9783030683795

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Financial Data Resampling for Machine Learning Based Trading by Tomé Almeida Borges,Rui Neves Pdf

This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, thus achieving higher returns without increased risk. The performance of the algorithm with the new resampling method and the classical time sampled data are compared and the advantages of using the system developed in this work are highlighted.

Artificial Intelligence and Society 5.0

Vikas Khullar,Vrajesh Sharma,Mohit Angurala,Nipun Chhabra
Artificial Intelligence and Society 5 0 Book PDF

Author : Vikas Khullar,Vrajesh Sharma,Mohit Angurala,Nipun Chhabra
Publisher : CRC Press
Page : 294 pages
File Size : 50,8 Mb
Release : 2024-01-22
Category : Computers
ISBN : 9781003825593

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Artificial Intelligence and Society 5.0 by Vikas Khullar,Vrajesh Sharma,Mohit Angurala,Nipun Chhabra Pdf

The artificial intelligence-based framework, algorithms, and applications presented in this book take the perspective of Society 5.0 – a social order supported by innovation in data, information, and knowledge. It showcases current case studies of Society 5.0 in diverse areas such as healthcare, smart cities, and infrastructure. Key Features: Elaborates on the use of big data, cyber-physical systems, robotics, augmented-virtual reality, and cybersecurity as pillars for Society 5.0. Showcases the use of artificial intelligence, architecture, frameworks, and distributed and federated learning structures in Society 5.0. Discusses speech recognition, image classification, robotic process automation, natural language generation, and decision support automation. Elucidates the application of machine learning, deep learning, fuzzy-based systems, and natural language processing. Includes case studies on the application of Society 5.0 aspects in educational, medical, infrastructure, and smart cities. The book is intendended especially for graduate and postgraduate students, and academic researchers in the fields of computer science and engineering, electrical engineering, and information technology.

Artificial Intelligence in Finance

Nydia Remolina,Aurelio Gurrea-Martinez
Artificial Intelligence in Finance Book PDF

Author : Nydia Remolina,Aurelio Gurrea-Martinez
Publisher : Edward Elgar Publishing
Page : 403 pages
File Size : 55,6 Mb
Release : 2023-01-20
Category : Law
ISBN : 9781803926179

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Artificial Intelligence in Finance by Nydia Remolina,Aurelio Gurrea-Martinez Pdf

This book provides a comprehensive analysis of the primary challenges, opportunities and regulatory developments associated with the use of artificial intelligence (AI) in the financial sector. It will show that, while AI has the potential to promote a more inclusive and competitive financial system, the increasing use of AI may bring certain risks and regulatory challenges that need to be addressed by regulators and policymakers.

MACHINE LEARNING FOR ALGORITHMIC TRADING

Jason Test,Mark Broker
MACHINE LEARNING FOR ALGORITHMIC TRADING Book PDF

Author : Jason Test,Mark Broker
Publisher : Unknown
Page : 424 pages
File Size : 49,9 Mb
Release : 2020-11-20
Category : Electronic
ISBN : 991860834X

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MACHINE LEARNING FOR ALGORITHMIC TRADING by Jason Test,Mark Broker Pdf

★ 55% OFF for Bookstores! LAST DAYS! ★ Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR BEGINNERS ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON DATA SCIENCE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHMIC TRADING and master its language, please click the BUY NOW button.

Machine Learning for Algorithmic Trading

Mark Broker,Jason Test
Machine Learning for Algorithmic Trading Book PDF

Author : Mark Broker,Jason Test
Publisher : Independently Published
Page : 422 pages
File Size : 51,9 Mb
Release : 2020-11-22
Category : Electronic
ISBN : 9798569390519

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Machine Learning for Algorithmic Trading by Mark Broker,Jason Test Pdf

Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR DATA SCIENCE ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON CRASH COURSE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHM TRADING and master its language, please click the BUY NOW button.

Machine Learning for Algorithm Trading

Mark Broker,Jason Test
Machine Learning for Algorithm Trading Book PDF

Author : Mark Broker,Jason Test
Publisher : Independently Published
Page : 424 pages
File Size : 50,9 Mb
Release : 2020-11-18
Category : Electronic
ISBN : 9798567144459

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Machine Learning for Algorithm Trading by Mark Broker,Jason Test Pdf

Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your trading thanks to the artificial intelligence? If so, keep reading: this bundle book is for you! Today, thanks to computer programming and PYTHON we can work with sophisticated machines that can study human behavior and identify underlying human behavioral patterns. Scientists can predict effectively what products and services consumers are interested in. You can also create various quantitative and algorithmic trading strategies using Python. It is getting increasingly challenging for traditional businesses to retain their customers without adopting one or more of the cutting-edge technology explained in this book. MACHINE LEARNING FOR ALGORITHM TRADING will introduce you many selected tips and breaking down the basics of coding applied to finance. You will discover as a beginner the world of data science, machine learning and artificial intelligence with step-by-step guides that will guide you during the code-writing learning process. The following list is just a tiny fraction of what you will learn in this bundle PYTHON FOR DATA SCIENCE ✅ Differences among programming languages: Vba, SQL, R, Python ✅ 3 reasons why Python is fundamental for Data Science ✅ Introduction to some Python libraries like NumPy, Pandas, Matplotlib, ✅ 3 step system why Python is fundamental for Data Science ✅Describe the steps required to develop and test an ML-driven trading strategy. PYTHON CRASH COURSE ✅ A Proven Method to Write your First Program in 7 Days ✅ 3 Common Mistakes to Avoid when You Start Coding ✅ Fit Python Data Analysis to your business ✅ 7 Most effective Machine Learning Algorithms ✅ Describe the methods used to optimize an ML-driven trading strategy. DAY AND SWING TRADING ✅ How Swing trading differs from Day trading in terms of risk-aversion ✅ How your money should be invested and which trade is more profitable ✅ Swing and Day trading proven indicators to learn investment timing ✅ The secret DAY trading strategies leading to a gain of $ 9,000 per month and more than $100,000 per year. OPTIONS TRADING FOR BEGINNERS ✅ Options Trading Strategies that guarantee real results in all market conditions ✅ Top 7 endorsed indicators of a successful investment ✅ The Bull & Bear Game ✅ Learn about the 3 best charts patterns to fluctuations of stock prices Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. Today is the best day to start programming like a pro. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer If you really wish to learn MACHINE LEARNING FOR ALGORITHM TRADING and master its language, please click the BUY NOW button.

Artificial Intelligence in Finance

Yves Hilpisch
Artificial Intelligence in Finance Book PDF

Author : Yves Hilpisch
Publisher : O'Reilly Media
Page : 477 pages
File Size : 48,5 Mb
Release : 2020-10-14
Category : Business & Economics
ISBN : 9781492055402

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Artificial Intelligence in Finance by Yves Hilpisch Pdf

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

Alpha Machines: Inside the AI-Driven Future of Finance

Gaurav Garg
Alpha Machines Inside the AI Driven Future of Finance Book PDF

Author : Gaurav Garg
Publisher : Gaurav Garg
Page : 84 pages
File Size : 52,6 Mb
Release : 2024-06-10
Category : Computers
ISBN : 8210379456XXX

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Alpha Machines: Inside the AI-Driven Future of Finance by Gaurav Garg Pdf

The world of finance has been transformed by the emergence of artificial intelligence and machine learning. Advanced algorithms are now routinely applied across the industry for everything from high frequency trading to credit risk modeling. Yet despite its widespread impact, AI trading remains an often misunderstood field full of misconceptions. This book aims to serve as an accessible introduction and guide to the real-world practices, opportunities, and challenges associated with applying artificial intelligence to financial markets. Across different chapters, we explore major applications of AI in algorithmic trading, common technologies and techniques, practical implementation considerations, and case studies of successes and failures. Key topics covered include data analysis, feature engineering, major machine learning models, neural networks and deep learning, natural language processing, reinforcement learning, portfolio optimization, algorithmic trading strategies, backtesting methods, and risk management best practices when deploying AI trading systems. Each chapter provides sufficient technical detail for readers new to computer science and machine learning while emphasizing practical aspects relevant to practitioners. Code snippets and mathematical derivations illustrate key concepts. Significant attention is dedicated to real-world challenges, risks, regulatory constraints, and procedures required to operationalize AI in live trading. The goal is to provide readers with an accurate picture of current best practices that avoids overstating capabilities or ignoring pitfalls. Ethics and responsible AI development are highlighted given societal impacts. Ultimately this book aims to dispel myths, ground discussions in data-driven evidence, and present a balanced perspective on leveraging AI safely and effectively in trading. Whether an experienced practitioner looking to enhance trading strategies with machine learning or a curious student interested in exploring this intriguing field, readers across backgrounds will find an accessible synthesis of core topics and emerging developments in AI-powered finance. The book distills decades of research and industry lessons into a compact guide. Complimented by references for further reading, it serves as a valuable launchpad for readers seeking to gain a holistic understanding of this future-oriented domain at the nexus of computing and financial markets.

Machine Learning for Algorithmic Trading

Stefan Jansen
Machine Learning for Algorithmic Trading Book PDF

Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Page : 822 pages
File Size : 40,5 Mb
Release : 2020-07-31
Category : Business & Economics
ISBN : 9781839216787

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Machine Learning for Algorithmic Trading by Stefan Jansen Pdf

Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

Artificial Intelligence in Asset Management

Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Artificial Intelligence in Asset Management Book PDF

Author : Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Publisher : CFA Institute Research Foundation
Page : 95 pages
File Size : 45,6 Mb
Release : 2020-08-28
Category : Business & Economics
ISBN : 9781952927034

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Artificial Intelligence in Asset Management by Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari Pdf

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Artificial Intelligence Applications on Wall Street

Stephen Slade
Artificial Intelligence Applications on Wall Street Book PDF

Author : Stephen Slade
Publisher : Routledge
Page : 162 pages
File Size : 50,8 Mb
Release : 2017-11-30
Category : Business & Economics
ISBN : 9781351335379

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Artificial Intelligence Applications on Wall Street by Stephen Slade Pdf

Originally published in 1996 as a special issue journal, Artificial Intelligence Applications on Wall Street, presents a series of articles derived from papers at the Third International Conference on Artificial Intelligence Applications on Wall Street. The volume addresses how Artificial Intelligence can be used to address the variety of issues in that arise in the world of investments, such as synthetic instruments, forecasting and surveillance. It examines the potential problems surrounding economic assumption of rationality in a global market, and how artificial intelligence can push the bounds of rationality.

Computational Intelligence in Economics and Finance

Paul P. Wang,Tzu-Wen Kuo
Computational Intelligence in Economics and Finance Book PDF

Author : Paul P. Wang,Tzu-Wen Kuo
Publisher : Springer Science & Business Media
Page : 232 pages
File Size : 51,5 Mb
Release : 2007-07-11
Category : Computers
ISBN : 9783540728214

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Computational Intelligence in Economics and Finance by Paul P. Wang,Tzu-Wen Kuo Pdf

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.

Genetic Algorithms and Applications for Stock Trading Optimization

Kapoor, Vivek,Dey, Shubhamoy
Genetic Algorithms and Applications for Stock Trading Optimization Book PDF

Author : Kapoor, Vivek,Dey, Shubhamoy
Publisher : IGI Global
Page : 262 pages
File Size : 54,7 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781799841067

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Genetic Algorithms and Applications for Stock Trading Optimization by Kapoor, Vivek,Dey, Shubhamoy Pdf

Genetic algorithms (GAs) are based on Darwin’s theory of natural selection and survival of the fittest. They are designed to competently look for solutions to big and multifaceted problems. Genetic algorithms are wide groups of interrelated events with divided steps. Each step has dissimilarities, which leads to a broad range of connected actions. Genetic algorithms are used to improve trading systems, such as to optimize a trading rule or parameters of a predefined multiple indicator market trading system. Genetic Algorithms and Applications for Stock Trading Optimization is a complete reference source to genetic algorithms that explains how they might be used to find trading strategies, as well as their use in search and optimization. It covers the functions of genetic algorithms internally, computer implementation of pseudo-code of genetic algorithms in C++, technical analysis for stock market forecasting, and research outcomes that apply in the stock trading system. This book is ideal for computer scientists, IT specialists, data scientists, managers, executives, professionals, academicians, researchers, graduate-level programs, research programs, and post-graduate students of engineering and science.