Applications of Computational Intelligence in Data-Driven Trading - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Computational Intelligence in Data-Driven Trading write by Cris Doloc. This book was released on 2019-11-05. Applications of Computational Intelligence in Data-Driven Trading available in PDF, EPUB and Kindle. “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.
Applications of Computational Intelligence in Data-Driven Trading
Applications of Computational Intelligence in Data-Driven Trading - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Computational Intelligence in Data-Driven Trading write by Cris Doloc. This book was released on 2019-10-31. Applications of Computational Intelligence in Data-Driven Trading available in PDF, EPUB and Kindle. “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
Computational Intelligence Techniques for Trading and Investment - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligence Techniques for Trading and Investment write by Christian Dunis. This book was released on 2014-03-26. Computational Intelligence Techniques for Trading and Investment available in PDF, EPUB and Kindle. 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.
Artificial Intelligence and Society 5.0
Artificial Intelligence and Society 5.0 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence and Society 5.0 write by Vikas Khullar. This book was released on 2024-01-22. Artificial Intelligence and Society 5.0 available in PDF, EPUB and Kindle. 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.
Financial Data Resampling for Machine Learning Based Trading
Financial Data Resampling for Machine Learning Based Trading - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Financial Data Resampling for Machine Learning Based Trading write by Tomé Almeida Borges. This book was released on 2021-02-22. Financial Data Resampling for Machine Learning Based Trading available in PDF, EPUB and Kindle. 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.
