Prediction Of Stock Market Index Movements With Machine Learning
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Prediction Of Stock Market Index Movements With Machine Learning
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Author : Nazif AYYILDIZ
language : en
Publisher: Özgür Publications
Release Date : 2023-12-16
Prediction Of Stock Market Index Movements With Machine Learning written by Nazif AYYILDIZ and has been published by Özgür Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-16 with Business & Economics categories.
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.
The Nature Of Statistical Learning Theory
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Author : Vladimir Vapnik
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
The Nature Of Statistical Learning Theory written by Vladimir Vapnik and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.
The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: * the setting of learning problems based on the model of minimizing the risk functional from empirical data * a comprehensive analysis of the empirical risk minimization principle including necessary and sufficient conditions for its consistency * non-asymptotic bounds for the risk achieved using the empirical risk minimization principle * principles for controlling the generalization ability of learning machines using small sample sizes based on these bounds * the Support Vector methods that control the generalization ability when estimating function using small sample size. The second edition of the book contains three new chapters devoted to further development of the learning theory and SVM techniques. These include: * the theory of direct method of learning based on solving multidimensional integral equations for density, conditional probability, and conditional density estimation * a new inductive principle of learning. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists. Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University. He is one of the founders of
Contemporary Research On Business And Management
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Author : Siska Noviaristanti
language : en
Publisher: CRC Press
Release Date : 2021-11-24
Contemporary Research On Business And Management written by Siska Noviaristanti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Technology & Engineering categories.
This book contains selected papers presented at the 4th International Seminar of Contemporary Research on Business and Management (ISCRBM 2020), which was organized by the Alliance of Indonesian Master of Management Program (APMMI) and held in Surubaya, Indonesia, 25-27 November 2020. It was hosted by the Master of Management Program Indonesia University and co-hosts Airlangga University, Sriwijaya University, Trunojoyo University of Madura, and Telkom University, and supported by Telkom Indonesia and Triputra. The seminar aimed to provide a forum for leading scholars, academics, researchers, and practitioners in business and management area to reflect on current issues, challenges and opportunities, and to share the latest innovative research and best practice. This seminar brought together participants to exchange ideas on the future development of management disciplines: human resources, marketing, operations, finance, strategic management and entrepreneurship.
Data Mining Algorithms
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Author : Pawel Cichosz
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-27
Data Mining Algorithms written by Pawel Cichosz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-27 with Mathematics categories.
Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.
Ict Innovations 2014
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Author : Ana Madevska Bogdanova
language : en
Publisher: Springer
Release Date : 2014-08-09
Ict Innovations 2014 written by Ana Madevska Bogdanova and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-09 with Technology & Engineering categories.
Data is a common ground, a starting point for each ICT system. Data needs processing, use of different technologies and state-of-the-art methods in order to obtain new knowledge, to develop new useful applications that not only ease, but also increase the quality of life. These applications use the exploration of Big Data, High throughput data, Data Warehouse, Data Mining, Bioinformatics, Robotics, with data coming from social media, sensors, scientific applications, surveillance, video and image archives, internet texts and documents, internet search indexing, medical records, business transactions, web logs, etc. Information and communication technologies have become the asset in everyday life enabling increased level of communication, processing and information exchange. This book offers a collection of selected papers presented at the Sixth International Conference on ICT Innovations held in September 2014, in Ohrid, Macedonia, with main topic World of data. The conference gathered academics, professionals and practitioners in developing solutions and systems in the industrial and business arena, especially innovative commercial implementations, novel applications of technology, and experience in applying recent ICT research advances to practical solutions.
Learning And Soft Computing
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Author : Vojislav Kecman
language : en
Publisher: MIT Press
Release Date : 2001
Learning And Soft Computing written by Vojislav Kecman and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.
11th International Conference On Theory And Application Of Soft Computing Computing With Words And Perceptions And Artificial Intelligence Icsccw 2021
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Author : Rafik A. Aliev
language : en
Publisher: Springer Nature
Release Date : 2022-01-04
11th International Conference On Theory And Application Of Soft Computing Computing With Words And Perceptions And Artificial Intelligence Icsccw 2021 written by Rafik A. Aliev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-04 with Technology & Engineering categories.
This book presents the proceedings of the 11th Conference on Theory and Applications of Soft Computing, Computing with Words and Perceptions and Artificial Intelligence, ICSCCW-2021, held in Antalya, Turkey, on August 23–24, 2021. The general scope of the book covers uncertain computation, decision making under imperfect information, neuro-fuzzy approaches, natural language processing, and other areas. The topics of the papers include theory and application of soft computing, computing with words, image processing with soft computing, intelligent control, machine learning, fuzzy logic in data mining, soft computing in business, economics, engineering, material sciences, biomedical engineering, and health care. This book is a useful guide for academics, practitioners, and graduates in fields of soft computing and computing with words. It allows for increasing of interest in development and applying of these paradigms in various real-life fields.
Applied Soft Computing And Communication Networks
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Author : Sabu M. Thampi
language : en
Publisher:
Release Date : 2021
Applied Soft Computing And Communication Networks written by Sabu M. Thampi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book constitutes thoroughly refereed post-conference proceedings of the International Applied Soft Computing and Communication Networks (ACN 2020) held in VIT, Chennai, India, during October 14-17, 2020. The research papers presented were carefully reviewed and selected from several initial submissions. The book is directed to the researchers and scientists engaged in various fields of intelligent systems.
Introduction To Artificial Neural Systems
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Author : Jacek M. Zurada
language : en
Publisher: Brooks/Cole
Release Date : 1995
Introduction To Artificial Neural Systems written by Jacek M. Zurada and has been published by Brooks/Cole this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Neural networks (Computer science) categories.
Deep Learning Tools For Predicting Stock Market Movements
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Author : Renuka Sharma
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-10
Deep Learning Tools For Predicting Stock Market Movements written by Renuka Sharma and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-10 with Computers categories.
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.