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 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 Forecasting Stock Prices written by Luna Tjung and published by Lulu.com. This book was released on with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book McWhirter Theory of Stock Market Forecasting written by Louise McWhirter and published by American Federation of Astr. This book was released on 2008-11 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Included in this volume are Louise McWhirter's theories and numerous, fully-explained and detailed examples for: Forecasting business cycles and stock market trends, forecasting trends of individual stocks, and forecasting monthly and daily trends on the New York stock exchange.
Download or read book Head First Python written by Paul Barry and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.
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 Technical Analysis and Stock Market Profits written by R. Schabacker and published by Harriman House Limited. This book was released on 2021-02-15 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Richard W. Schabacker's great work, Technical Analysis and Stock Market Profits, is a worthy addition to any technical analyst's personal library or any market library. His "pioneering research" represents one of the finest works ever produced on technical analysis, and this book remains an example of the highest order of analytical quality and incisive trading wisdom. Originally devised as a practical course for investors, it is as alive, vital and instructional today as the day it was written. It paved the way for Robert Edwards and John Magee's best-selling Technical Analysis of Stock Trends - a debt which is acknowledged in their foreword: 'Part One is based in large part on the pioneer researches and writings of the late Richard Schabacker.'Schabacker presents technical analysis as a totally organized subject and comprehensively lays out the various important patterns, formations, trends, support and resistance areas, and associated supporting technical detail. He presents factors that can be confidently relied on, and gives equal attention to the blemishes and weaknesses that can upset the best of analytical forecasts: Factors which investors would do well to absorb and apply when undertaking the fascinating game of price, time and volume analysis.
Download or read book Deep Learning for Time Series Forecasting written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-08-30 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.
Download or read book Least Squares Support Vector Machines written by Johan A. K. Suykens and published by World Scientific. This book was released on 2002 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is discussed, together with methods for imposing spareness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LS-SVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LS-SVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.
Download or read book 2019 IEEE 43rd Annual Computer Software and Applications Conference COMPSAC written by IEEE Staff and published by . This book was released on 2019-07-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: COMPSAC is the IEEE Computer Society s signature Conference on Computers, Software and Applications It is one of the major international forums for academia, industry, and government to discuss research results, advancements and future trends in computer and software technologies and applications The technical program includes keynote addresses, research papers, industrial case studies, panel discussions, fast abstracts, doctoral symposium, poster sessions, and a number of workshops on emerging important topics
Download or read book Trend Forecasting with Intermarket Analysis written by Louis B. Mendelsohn and published by John Wiley & Sons. This book was released on 2012-10-15 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this groundbreaking new edition, Mendelsohn gives you the weapon to conquer the limitations of traditional technical trading-intermarket analysis. To compete in today's rapidly changing economy, you need a method that can identify reoccurring patterns within individual financial markets and between related global markets. You need tools that lead, not lag. Step by step, Mendelsohn shows how combining technical, fundamental, and intermarket analysis into one powerful framework can give you an early edge to accurately forecasting trends. Inside, you'll discover: Precise trading strategies that can be used by both day traders and position traders. The limitations of traditional technical analysis methods-and how to overcome them. How neural network computational modeling can create leading, not lagging, moving averages for more accurate forecasting. Innovative, quantitative trend forecasting indicators at the cutting edge of market analysis. PLUS-an introduction to VantagePoint Software, which makes Mendelsohn's "new economy" trading methods work simply-and effectively. This software applies the pattern recognition capabilities of advanced neural networks to analyze intermarket data on literally hundreds of global financial markets each day.
Download or read book First International Conference on Sustainable Technologies for Computational Intelligence written by Ashish Kumar Luhach and published by Springer Nature. This book was released on 2019-11-01 with total page 847 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers high-quality papers presented at the First International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI 2019), which was organized by Sri Balaji College of Engineering and Technology, Jaipur, Rajasthan, India, on March 29–30, 2019. It covers emerging topics in computational intelligence and effective strategies for its implementation in engineering applications.
Download or read book TIME SERIES ANALYSIS FORECASTING STOCK PRICE USING MACHINE LEARNING WITH PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-07-02 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock trading and financial instrument markets offer significant opportunities for wealth creation. The ability to predict stock price movements has long intrigued researchers and investors alike. While some theories, like the Efficient Market Hypothesis, suggest that consistently beating the market is nearly impossible, others contest this viewpoint. Stock price prediction involves forecasting the future value of a given stock. In this project, we focus on the S&P 500 Index, which consists of 500 stocks from various sectors of the US economy and serves as a key indicator of US equities. To tackle this task, we utilize the Yahoo stock price history dataset, which contains 1825 rows and 7 columns including Date, High, Low, Open, Close, Volume, and Adj Close. To enhance our predictions, we incorporate technical indicators such as daily returns, Moving Average Convergence-Divergence (MACD), Relative Strength Index (RSI), Simple Moving Average (SMA), lower and upper bands, and standard deviation. In this book, for the forecasting task, we employ various regression algorithms including Linear Regression, Random Forest Regression, Decision Tree Regression, Support Vector Regression, Naïve Bayes Regression, K-Nearest Neighbor Regression, Adaboost Regression, Gradient Boosting Regression, Extreme Gradient Boosting Regression, Light Gradient Boosting Regression, Catboost Regression, MLP Regression, Lasso Regression, and Ridge Regression. These models aim to predict the future Adj Close price of the stock based on historical data. In addition to stock price prediction, we also delve into predicting stock daily returns using machine learning models. We utilize K-Nearest Neighbor Classifier, Random Forest Classifier, Naive Bayes Classifier, Logistic Regression Classifier, Decision Tree Classifier, Support Vector Machine Classifier, LGBM Classifier, Gradient Boosting Classifier, XGB Classifier, MLP Classifier, and Extra Trees Classifier. These models are trained to predict the direction of daily stock returns (positive or negative) based on various features and technical indicators. To assess the performance of these machine learning models, we evaluate several important metrics. Accuracy measures the overall correctness of the predictions, while recall quantifies the ability to correctly identify positive cases (upward daily returns). Precision evaluates the precision of positive predictions, and the F1 score provides a balanced measure of precision and recall. Additionally, we consider macro average, which calculates the average metric value across all classes, and weighted average, which provides a balanced representation considering class imbalances. To enhance the user experience and facilitate data exploration, we develop a graphical user interface (GUI). The GUI is built using PyQt and offers an interactive platform for users to visualize and interact with the data. It provides features such as plotting boundary decisions, visualizing feature distributions and importance, comparing predicted values with true values, displaying confusion matrices, learning curves, model performance, and scalability analysis. The GUI allows users to customize the analysis by selecting different models, time periods, or variables of interest, making it accessible and user-friendly for individuals without extensive programming knowledge. The combination of exploring the dataset, forecasting stock prices, predicting daily returns, and developing a GUI creates a comprehensive framework for analyzing and understanding stock market trends. By leveraging machine learning algorithms and evaluating performance metrics, we gain valuable insights into the accuracy and effectiveness of our predictions. The GUI further enhances the accessibility and usability of the analysis, enabling users to make data-driven decisions and explore the stock market with ease.
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 Paul Wilmott on Quantitative Finance written by Paul Wilmott and published by Wiley. This book was released on 2000-06-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only comprehensive reference encompassing both traditional and new derivatives and financial engineering techniques Based on the author's hugely successful Derivatives: The Theory and Practice of Financial Engineering, Paul Wilmott on Quantitative Finance is the definitive guide to derivatives and related financial products. In addition to fully updated and expanded coverage of all the topics covered in the first book, this two-volume set also includes sixteen entirely new chapters covering such crucial areas as stochastic control and derivatives, utility theory, stochastic volatility and utility, mortgages, real options, power derivatives, weather derivatives, insurance derivatives, and more. Wilmott has also added clear, detailed explanations of all the mathematical procedures readers need to know in order to use the techniques he describes. Paul Wilmott, Dphil (Oxford, UK), is one of Europe's leading writers and consultants in the area of financial mathematics. He is also head of Wilmott Associates, a leading international financial consulting firm whose clients include Citibank, IBM, Bank of Montreal, Momura, Daiwa, Maxima, Dresdner Klienwort Benson, Origenes, and Siembra.
Download or read book Data Science and Intelligent Systems written by Radek Silhavy and published by Springer Nature. This book was released on 2021-11-16 with total page 1073 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the second part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021) proceedings. The real-world problems related to data science and algorithm design related to systems and software engineering are presented in this papers. Furthermore, the basic research’ papers that describe novel approaches in the data science, algorithm design and in systems and software engineering are included. The CoMeSySo 2021 conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results
