Found inside – Page iThis new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn ... Found insideThis book features a selection of articles from The 2019 International Conference on Information Technology & Systems (ICITS’19), held at the Universidad de Las Fuerzas Armadas, in Quito, Ecuador, on 6th to 8th February 2019. Found inside – Page 321AIM: Develop a machine learning method to Predict stock prices based on past price variation. Stock Price Prediction Predicting the trends in stock market ... This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and ... This book will show you how to take advantage of TensorFlow’s most appealing features - simplicity, efficiency, and flexibility - in various scenarios. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Found inside – Page 5There are lots of platforms that aim to help users make better stock trades. ... From a machine learning perspective, decisions are being made for you on ... Argues that post-crisis Wall Street continues to be controlled by large banks and explains how a small, diverse group of Wall Street men have banded together to reform the financial markets. Found inside(2018) examined the links among stock market volatility, market sentiment, macroeconomic indicators, and spread volatility over the persisting long-term ... The correct prediction of stock prices is a challenging task, as stock prices are affected by a large number of parameters. Found insideDrawing from his experience as a securities analyst, economist, and investor, the author explains the workings of Wall Street and offers advice on determining the value and potential of stocks In this book, we tackle the common misconception that the stock market cannot be predicted, and build a stock prediction algorithm to beat the stock market, using Deep Learning, Data Analysis, and Natural Language Processing techniques.If ... What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing) Discover the best practices to successfully implement AI by examining case studies including Uber ... Found inside – Page 88Lee, T.K., Cho, J.H., Kwon, D.S., Sohn, S.Y.: Global stock market investment strategies based on financial network indicators using machine learning ... Found inside – Page 267Trim Size: 6.625in x 9.625in Guida522195 c13.tex V1 - 10/26/2018 8:39pm Page 267 Deep Learning in Finance: Prediction of Stock Returns with Long Short-Term ... Found inside – Page 8In a comparative study, Gu, Kelly, & Xiu (2018) investigated the effectiveness of machine learning techniques in the context of asset pricing, creating forecasts for individual stock returns based on a variety of company and macro variables. Found insideThis book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. This book is your answer. While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. Found insideWhile Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to ... Found inside – Page iThis book constitutes the refereed proceedings of the 11th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2004, held in Varna, Bulgaria in September 2004. Found inside – Page iThis book constitutes the refereed proceedings of the 22 International Conference on Database and Expert Systems Applications, DEXA 2011, held in Toulouse, France, August 29 - September 2, 2011. The Complete Penny Stock Course is based on Timothy Sykes’, various training programs. His strategies have helped individuals like Tim Grittani, Michael Goode and Stephen Dux become millionaires within a couple of years. This book is your answer. While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Found inside – Page 346Stock market analysis has been one of the most actively pursued avenues of Machine Learning (ML) research and applications. The most recent literature in ... This book should be read and absorbed by every serious student of the field, academic and professional.” Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in ... The 2020 edition of the 100 Best Stocks series picks the top stocks for you to buy based on authors Peter Sander and Scott Bobo’s value-investing philosophy, the same philosophy followed by Warren Buffett. Found inside – Page 713It demonstrates that the multi-task learning idea can be successfully applied to the stock prediction problem, resulting in a significant improvement in the ... 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 ... Found insideStocks. A recent strand of literature has found that machine learning techniques have strong potential for generating a multifactor signal from a large set ... Found insideA limit order book contains all the information available on a specific market and it reflects the way the market moves under the influence of its participants. This book discusses several models of limit order books. Found inside – Page 221Put your machine learning concepts to the test by developing real-world smart ... Though there are countless financial instruments, including stocks, bonds, ... I want us to be clear on that point from the get-go. By the end of this book, you'll have a great understanding of what investing is, and you will know how the magic of compounding works too. The purpose of this paper is to benchmark a large set of eight contemporary machine learning algorithms in order to identify the best model for the selection of outperforming stocks in Switzerland. Found insideProject Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to ... Selecting high-performing stocks among a vast number of available securities is still one of the investor's prime concerns. Found inside – Page 115We apply the TIGER method to explore a stock price dataset collected from Yahoo! Finance (finance.yahoo.com). More specifically, the daily closing prices ... Found inside – Page 207Stock. Price. Motion. Prediction. Using. Technical. Analysis. Datasets. and. Machine. Learning. Apostolos Meliones and George Makrides Abstract The purpose ... Found inside – Page 347Stock. Market. Using. Machine. Learning–Based. Data. Analytics. Maheswari P. and Jaya A.* Department of Computer Applications, B.S Abdur Rahman Crescent ... The chapters in this book were originally published as a special issue of the Quantitative Finance journal. This book demonstrates a set of simple to complex problems you may encounter while building machine learning models. Found insideWhat you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement ... Found inside – Page 84Today an infinite number of factors affect the stock market. Only one aspect cannot guarantee to forecast. In Deep Learning ... This book will help you in Discover Value Investing, the approach taken by the best investors: Warren Buffett, Joel Greenblatt, Michael Burry, Peter Lynch, John Templeton, Charlie Munger Build your own AI! Have your own Value Investing ... Found insideToday ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Found inside – Page 409Stock markets support commodity economy through financial activities in terms of ... of machine learning have produced efficient results in long-term stock ... Found inside – Page 489A General Approach for Risk Controlled Trading Based on Machine Learning and ... which is in charge to forecast the return of each of the considered stocks. 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