Download or read book Advanced Financial Modeling for Stock Price Prediction written by Azhar ul Haque Sario and published by Azhar Sario Authorship and Publishing. This book was released on 2024-09-10 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This third edition in the "Stock Predictions" series builds upon its predecessors, offering a deep dive into the quantitative methods used in stock price prediction. It presents a comprehensive guide to advanced financial models, ranging from the foundational Brownian Motion to cutting-edge machine learning techniques. The book explores key concepts like Geometric Brownian Motion for modeling exponential growth, Mean Reversion Models for capturing price reversion tendencies, and GARCH models for understanding volatility. It also delves into the world of machine learning, showcasing how Support Vector Machines, Neural Networks, and LSTMs can enhance prediction accuracy. Monte Carlo simulations and Copula Models are further discussed for their roles in risk assessment and portfolio management. Throughout the book, mathematical formulations, parameter estimation techniques, and practical applications are presented with clarity. The strengths and limitations of each model are highlighted, enabling readers to make informed choices. This edition is an invaluable resource for anyone in finance and investments seeking to master the quantitative tools used in stock price prediction. Whether a student, researcher, or practitioner, this book empowers you to leverage advanced models and navigate the complexities of today's markets.

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.

Download or read book INFORMATION TECHNOLOGY BIOINFORMATICS INTERNATIONAL CONFERENCE ON ADVANCE IT ENGINEERING AND MANAGEMENT SACAIM 2023 VOLUME 1 written by Dr. Hemalatha N. and published by REDSHINE Publication. This book was released on 2024-08-25 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whiteflies pose a significant threat to agricultural productivity worldwide, causing damage to crops and economic losses. In this study, we present an Android-based whiteflies detection system utilizing deep learning techniques, specifically leveraging the YOLOv5 algorithm. The objective is to create a robust and efficient solution capable of real-time whitefly detection in agricultural fields. The proposed system capitalizes on the powerful capabilities of YOLOv5, a state-of-the-art object detection algorithm, known for its accuracy and speed.

Download or read book Anticipating Future Business Trends Navigating Artificial Intelligence Innovations written by Rim El Khoury and published by Springer Nature. This book was released on with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Download or read book Advanced Data Mining and Applications written by Shuigeng Zhou and published by Springer Science & Business Media. This book was released on 2012-12-09 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.

Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Download or read book Mathematical Finance with Applications written by Wing-Keung Wong and published by . This book was released on 2020 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.

Download or read book Emerging Technologies in Data Mining and Information Security written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2021-06-28 with total page 1014 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of things (IoT) and information security.

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Download or read book Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics ICAMIDA 2022 written by Sharvari Tamane and published by Springer Nature. This book was released on 2023-05-01 with total page 1027 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. As on date, huge volumes of data are being generated through sensors, satellites, and simulators. Modern research on data analytics and its applications reveal that several algorithms are being designed and developed to process these datasets, either through the use of sequential and parallel processes. In the current scenario of Industry 4.0, data analytics, artificial intelligence and machine learning are being used to support decisions in space and time. Further, the availability of Graphical Processing Units (GPUs) and Tensor Processing Units (TPUs) have enabled to processing of these datasets. Some of the applications of Artificial Intelligence, Machine Learning and Data Analytics are in the domains of Agriculture, Climate Change, Disaster Prediction, Automation in Manufacturing, Intelligent Transportation Systems, Health Care, Retail, Stock Market, Fashion Design, etc. The international conference on Applications of Machine Intelligence and Data Analytics aims to bring together faculty members, researchers, scientists, and industry people on a common platform to exchange ideas, algorithms, knowledge based on processing hardware and their respective application programming interfaces (APIs).

Download or read book The Feasibility of Predicting Financial Crises using Machine Learning written by Julia Markhovski and published by GRIN Verlag. This book was released on 2024-03-26 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2024 in the subject Computer Science - Commercial Information Technology, grade: 1.0, Frankfurt School of Finance & Management, language: English, abstract: In a world characterized by increasingly complex financial markets, the prediction of financial crises is a constant challenge. This bachelor thesis investigates the use of machine learning, in particular regression algorithms, to analyze and predict financial crises based on macroeconomic data. By building six different regression models and optimizing them using cross-validation and GridSearch, the feasibility of using these technologies for accurate predictions is discussed. Although traditional models show limited effectiveness, the integration of machine learning, especially kNN algorithms, reveals significant potential for improving prediction accuracy. The paper highlights the importance of classification algorithms and provides crucial insights for application in real-world scenarios to provide valuable tools for policy and business decision makers.

Download or read book Neural Networks in Finance written by Paul D. McNelis and published by Academic Press. This book was released on 2005-01-05 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website

Download or read book Computational Methods in Decision Making Economics and Finance written by Erricos John Kontoghiorghes and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria.

Download or read book How can I get started Investing in the Stock Market written by Lokesh Badolia and published by Educreation Publishing. This book was released on 2016-10-27 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is well-researched by the author, in which he has shared the experience and knowledge of some very much experienced and renowned entities from stock market. We want that everybody should have the knowledge regarding the different aspects of stock market, which would encourage people to invest and earn without any fear. This book is just a step forward toward the knowledge of market.

Download or read book 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 published by Springer Nature. This book was released on 2022-01-04 with total page 803 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Financial Forecasting Analysis and Modelling written by Michael Samonas and published by John Wiley & Sons. This book was released on 2015-01-20 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework of long-term financial forecasts in a practical and accessible way, helping finance professionals include uncertainty in their planning and budgeting process. With thorough coverage of financial statement simulation models and clear, concise implementation instruction, this book guides readers step-by-step through the entire projection plan development process. Readers learn the tools, techniques, and special considerations that increase accuracy and smooth the workflow, and develop a more robust analysis process that improves financial strategy. The companion website provides a complete operational model that can be customised to develop financial projections or a range of other key financial measures, giving readers an immediately-applicable tool to facilitate effective decision-making. In the aftermath of the recent financial crisis, the need for experienced financial modelling professionals has steadily increased as organisations rush to adjust to economic volatility and uncertainty. This book provides the deeper level of understanding needed to develop stronger financial planning, with techniques tailored to real-life situations. Develop long-term projection plans using Excel Use appropriate models to develop a more proactive strategy Apply risk and uncertainty projections more accurately Master the Excel Scenario Manager, Sensitivity Analysis, Monte Carlo Simulation, and more Risk plays a larger role in financial planning than ever before, and possible outcomes must be measured before decisions are made. Uncertainty has become a critical component in financial planning, and accuracy demands it be used appropriately. With special focus on uncertainty in modelling and planning, Financial Forecasting, Analysis and Modelling is a comprehensive guide to the mechanics of modern finance.