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Author: M. Costantino Publisher: WIT Press ISBN: 1845641469 Category : Business & Economics Languages : en Pages : 193
Book Description
Professional financial traders are currently overwhelmed with news and extracting relevant information is a long and hard task, whilst trading decisions require immediate actions. Primarily intended for financial organizations and business analysts, this book provides an introduction to the algorithmic solutions to automatically extract the desired information from Internet news and obtain it in a well structured form. It places emphasis on the principles of the method rather than its numerical implementation, omitting the mathematical details that might otherwise obscure the text, and focuses on the advantages and on the problems of each method. The authors also include many practical examples with complete references and algorithms for similar problems, which may be useful in the financial field, and basic techniques applied in other information extraction fields which may be imported into the financial news analysis.
Author: M. Costantino Publisher: WIT Press ISBN: 1845641469 Category : Business & Economics Languages : en Pages : 193
Book Description
Professional financial traders are currently overwhelmed with news and extracting relevant information is a long and hard task, whilst trading decisions require immediate actions. Primarily intended for financial organizations and business analysts, this book provides an introduction to the algorithmic solutions to automatically extract the desired information from Internet news and obtain it in a well structured form. It places emphasis on the principles of the method rather than its numerical implementation, omitting the mathematical details that might otherwise obscure the text, and focuses on the advantages and on the problems of each method. The authors also include many practical examples with complete references and algorithms for similar problems, which may be useful in the financial field, and basic techniques applied in other information extraction fields which may be imported into the financial news analysis.
Author: Sergio Consoli Publisher: Springer Nature ISBN: 3030668916 Category : Application software Languages : en Pages : 357
Book Description
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Author: Matthew F. Dixon Publisher: Springer Nature ISBN: 3030410684 Category : Business & Economics Languages : en Pages : 565
Book Description
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.
Author: Dhananjay Kumar Publisher: Springer Nature ISBN: 9464632305 Category : Education Languages : en Pages : 1409
Book Description
This is an open access book. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28–30, 2023 at the Xiamen, China. With the development of science and technology, information technology and information resources should be actively developed and fully applied in all fields of education and teaching, so as to promote the modernization of education and cultivate talents to meet the needs of society. From the technical point of view, the basic characteristics of educational informatization are digitalization, networking, intelligentization and multi-media. From the perspective of education, the basic characteristics of educational information are openness, sharing, interaction and cooperation. With the advantage of the network, it can provide students with a large amount of information and knowledge by combining different knowledge and information from various aspects in a high frequency. Therefore, we have intensified efforts to reform the traditional teaching methods and set up a new teaching concept, from the interaction between teachers and students in the past to the sharing between students. In short, it forms a sharing learning mode. For all students, strive to achieve students' learning independence, initiative and creativity. To sum up, we will provide a quick exchange platform between education and information technology, so that more scholars in related fields can share and exchange new ideas. The 3rd International Conference on Internet, Education and Information Technology (IEIT 2023) was held on April 28-30, 2023 in Xiamen, China. IEIT 2023 is to bring together innovative academics and industrial experts in the field of Internet, Education and Information Technology to a common forum. The primary goal of the conference is to promote research and developmental activities in Internet, Education and Information Technology and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in international conference on Internet, Education and Information Technology and related areas.
Author: Seán O'Riain Publisher: Seán O'Riain ISBN: Category : Languages : en Pages : 195
Book Description
Supporting competitive business analysis of financial reports through the automated analysis and interpretation of their natural language sections, presents specific challenges including information that can be ambiguous, camouflaged, or tacitly hidden within the narrative. These sections present terminology and structural challenges for information extraction that require the application of linguistic and heuristic based domain modelling to identify the information requirement. This thesis investigates a modelling approach that incrementally builds the business analysts information requirement as a series of Semantic Paths grounded in domain linguistic and user heuristics. A Competitive Analysis Ontology (CAO) is defined to provide semantic representation of the information requirement necessary to drive linguistic analysis and information extraction. The evaluation of the CAO within the financial sub-domain of competitive analysis is investigated, through the development of the Analyst Work Bench (AWB), is presented. The AWB linguistically analyses a Form 10-Q’s disclosure sections, automatically populates the CAO and provides the analyst’s information requirement. The AWB leverages the CAO Semantic Paths for information search and extraction capability, to support an analyst perform a competitive analysis, with reduced manual effort. Evaluation based on design-science principles, use methods from information retrieval and information system success to determine CAO performance and usability. A controlled experiment that compares competitive analysis performance using the AWB, against its manual performed equivalent, reported a 37% performance increase using the AWB to identify relevant information. Usability evaluation further found that CAO use contributed to task structuring, and structured information provision in a manner that directly supported task performance.
Author: El Bachir Boukherouaa Publisher: International Monetary Fund ISBN: 1589063953 Category : Business & Economics Languages : en Pages : 35
Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Author: Agostino Capponi Publisher: Cambridge University Press ISBN: 1316516199 Category : Mathematics Languages : en Pages : 742
Book Description
Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory.
Author: Max Bramer Publisher: Springer ISBN: 3319471759 Category : Computers Languages : en Pages : 381
Book Description
The papers in this volume are the refereed papers presented at AI-2016, the Thirty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2016 in both the technical and the application streams. They present new and innovative developments and applications, divided into technical stream sections on Knowledge Discovery and Data Mining, Sentiment Analysis and Recommendation, Machine Learning, AI Techniques, and Natural Language Processing, followed by application stream sections on AI for Medicine and Disability, Legal Liability and Finance, Telecoms and eLearning, and Genetic Algorithms in Action. The volume also includes the text of short papers presented as posters at the conference. This is the thirty-third volume in the Research and Development in Intelligent Systems series, which also incorporates the twenty-fourth volume in the Applications and Innovations in Intelligent Systems series. These series are essential reading for those who wish to keep up to date with developments in this important field.
Author: A. Zanasi Publisher: WIT Press ISBN: 1845641841 Category : Computers Languages : en Pages : 209
Book Description
Since the end of the Cold War, the threat of large-scale wars has been substituted by new threats: terrorism, organised crime, trafficking, smuggling, proliferation of weapons of mass destruction. To react to them, a security strategy is necessary, but in order to be effective it requires several instruments, including technological tools. Consequently, research and development in the field of security is proving to be an ever-expanding field all over the world. Data mining is seen more and more not only as a key technology in business, engineering and science but as one of the key features in security. To stress that all these technologies must be seen as a way to improve not only the security of citizens but also their freedom, special attention will be given to data protection research issues. The 10th International Conference on Data Mining is part of the successful series and the topics include: Text mining and text analytics; Data mining applications; Data mining methods.
Author: M. Costantino
Author: M. Costantino
Author: Sergio Consoli
Author: Matthew F. Dixon
Author: Ran Tao
Author: Dhananjay Kumar
Author: Seán O'Riain
Author: El Bachir Boukherouaa
Author: Agostino Capponi
Author: Max Bramer
Author: A. Zanasi