Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2020-11-23 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 12th International Conference on Computational Collective Intelligence, ICCCI 2020, held in Da Nang, Vietnam, in November 2020.* The 70 full papers presented were carefully reviewed and selected from 314 submissions. The papers are grouped in topical sections on: knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; applications of collective intelligence; data mining methods and applications; machine learning methods; deep learning and applications for industry 4.0; computer vision techniques; biosensors and biometric techniques; innovations in intelligent systems; natural language processing; low resource languages processing; computational collective intelligence and natural language processing; computational intelligence for multimedia understanding; and intelligent processing of multimedia in web systems. *The conference was held virtually due to the COVID-19 pandemic.

Download or read book Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

Download or read book Environmental Social and Governance Perspectives on Economic Development in Asia written by William A. Barnett and published by Emerald Group Publishing. This book was released on 2021-11-08 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume of the International Symposia in Economic Theory and Econometrics explores the latest economic and financial developments in Asia.

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 The Quant Investor s Almanac 2011 written by Irene Aldridge and published by John Wiley & Sons. This book was released on 2010-08-26 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only book that examines the economic events relevant to economic indicators Economic indicators are often the primary drivers of value in various financial securities, from equities and fixed income to foreign exchange, commodities, and various derivative instruments. Most indicators are released on a fixed schedule, known well in advance. However, aggregating the schedules of all the announcements is a lot of work. That's where The Quant Investor's Almanac 2011comes in handy. This reliable guide identifies the release dates of data used by leading indicators, which are widely used by traders, and then puts this information in perspective – all while organizing this valuable information into an easy to use calendar format. Highlights the latest research related to each economic indicator Includes an online application where you can find daily updates to economic events and expanded references Provides a ready reference for properly anticipating changes in securities given various economic announcements The right information can make all the difference in your trading or investing endeavors. This book will show you exactly what you need to know in order to enhance your financial performance.

Download or read book AI and Financial Markets written by Shigeyuki Hamori and published by MDPI. This book was released on 2020-07-01 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.

Download or read book The ECB s Monetary Analysis Revisited written by Helge Berger and published by International Monetary Fund. This book was released on 2008-07 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monetary aggregates continue to play an important role in the ECB's policy strategy. This paper revisits the case for money, surveying the ongoing theoretical and empirical debate. The key conclusion is that an exclusive focus on non-monetary factors alone may leave the ECB with an incomplete picture of the economy. However, treating monetary factors as a separate matter is a second-best solution. Instead, a general-equilibrium inspired analytical framework that merges the economic and monetary "pillars" of the ECB's policy strategy appears the most promising way forward. The role played by monetary aggregates in such unified framework may be rather limited. However, an integrated framework would facilitate the presentation of policy decisions by providing a clearer narrative of the relative role of money in the interaction with other economic and financial sector variables, including asset prices, and their impact on consumer prices.

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Download or read book Machine Learning in Asset Pricing written by Stefan Nagel and published by Princeton University Press. This book was released on 2021-05-11 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

Download or read book Monetary Economics written by Steven Durlauf and published by Springer. This book was released on 2016-04-30 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.

Download or read book Monetary Economics written by Keith Bain and published by Bloomsbury Publishing. This book was released on 2017-09-16 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully revised second edition of Bain and Howells' Monetary Economics provides an up-to-date examination of monetary policy as it is practised and the theory underlying it. The authors link the conduct of monetary policy to the IS/PC/MR model and extend this further through the addition of a simple model of the banking sector. They demonstrate why monetary policy is central to the management of a modern economy, showing how it might have lasting effects on real variables, and look at how the current economic crisis has weakened the ability of policymakers to influence aggregate demand through the structure of interest rates. The second edition: features a realistic account of the conduct of monetary policy when the money supply is endogenous provides a detailed and up-to-date account of the conduct of monetary policy and links this explicitly to a framework for teaching macroeconomics includes recent changes in money market operations and an examination of the problems posed for monetary policy by the recent financial crisis Monetary Economics is an ideal core textbook for advanced undergraduate modules in monetary economics and monetary theory and policy.

Download or read book Social Media written by Ashlee Humphreys and published by Oxford University Press. This book was released on 2016 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social Media: Enduring Principles offers a comprehensive overview of topics in social media, from interpersonal communication to the role of social media in culture and society. It covers not only cultural issues like online identity and community, but also tackles more analytical topics like social media measurement, network analysis, and social media economics at an introductory level. Each chapter is based on a set of core social science theories and concepts rather than platform-specific frameworks and findings. Rather than providing the final word or predictions, it aims to open a well-structured, well-grounded conversation about media transition and its effects. Filling the need for a standard academic text in the field, Social Media: Enduring Principles summarizes both foundational and state-of-the-art research and also presents a coherent framework for future research. It draws from longstanding theories in communication, journalism, sociology, and marketing, but also includes a number of contemporary case examples, making it a foundational text in the area.

Download or read book A Modern Guide to Macroeconomics written by Brian Snowdon and published by Edward Elgar Publishing. This book was released on 1994 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work provides up-to-date discussions of recent developments in modern macroeconomics; it also features interviews with leading economists that aim to shed new light on the major intellectual and policy issues of the 1990s.

Download or read book Machine Learning Techniques for Space Weather written by Enrico Camporeale and published by Elsevier. This book was released on 2018-05-31 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book is a unique and important resource for space physicists, space weather professionals and computer scientists in related fields. - Collects many representative non-traditional approaches to space weather into a single volume - Covers, in an accessible way, the mathematical background that is not often explained in detail for space scientists - Includes free software in the form of simple MATLAB® scripts that allow for replication of results in the book, also familiarizing readers with algorithms

Download or read book Sustainable Development in AI Blockchain and E Governance Applications written by Kumar, Rajeev and published by IGI Global. This book was released on 2024-02-09 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of immediate technical expansion, our world faces a multifaceted challenge: ensuring the sustainability of our digital transformation. Governments and organizations have wholeheartedly embraced innovative technologies such as artificial intelligence, blockchain, and e-governance, but in doing so, they have encountered a complex web of issues. These range from cybersecurity concerns in an increasingly digitalized world to the need for intelligent systems capable of managing automation infrastructure and interconnected environments. Sustainable Development in AI, Blockchain, and E-Governance Applications offers a forward-thinking approach that harnesses the synergy between intelligent systems, machine learning, deep learning, and blockchain methods. It explores data-driven decision-making, automation infrastructure, autonomous transportation, and the creation of connected buildings, all aimed at crafting a sustainable digital future. By delving into topics like machine learning for smart parking, disease classification through neural networks, and the Internet of Things (IoT) for smarter cities, this book equips academic scholars with the tools they need to navigate the complex terrain of technology and governance. Academic scholars and researchers in technology, governance, and sustainability will find this book to be an indispensable resource. It caters to those seeking a comprehensive understanding of current and future trends in the integration of intelligent systems with cybersecurity applications.

Download or read book Modern Money Theory written by L. Randall Wray and published by Springer. This book was released on 2015-09-22 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition explores how money 'works' in the modern economy and synthesises the key principles of Modern Money Theory, exploring macro accounting, currency regimes and exchange rates in both the USA and developing nations.

Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.