Information Extraction In Finance
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Information Extraction In Finance
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Author : M. Costantino
language : en
Publisher: WIT Press
Release Date : 2008
Information Extraction In Finance written by M. Costantino and has been published by WIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.
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.
Data Science For Economics And Finance
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Author : Sergio Consoli
language : en
Publisher: Springer Nature
Release Date : 2021
Data Science For Economics And Finance written by Sergio Consoli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Application software categories.
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.
Handbook On Information Technology In Finance
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Author : Detlef Seese
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-05-27
Handbook On Information Technology In Finance written by Detlef Seese and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-27 with Business & Economics categories.
This handbook contains surveys of state-of-the-art concepts, systems, applications, best practices as well as contemporary research in the intersection between IT and finance. Included are recent trends and challenges, IT systems and architectures in finance, essential developments and case studies on management information systems, and service oriented architecture modeling. The book shows a broad range of applications, e.g. in banking, insurance, trading and in non-financial companies. Essentially, all aspects of IT in finance are covered.
The Book Of Alternative Data
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Author : Alexander Denev
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-21
The Book Of Alternative Data written by Alexander Denev and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-21 with Business & Economics categories.
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
Business Intelligence Techniques
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Author : Murugan Anandarajan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-02
Business Intelligence Techniques written by Murugan Anandarajan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-02 with Business & Economics categories.
Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.
Expert Systems In Finance
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Author : Noura Metawa
language : en
Publisher: Routledge
Release Date : 2019-05-10
Expert Systems In Finance written by Noura Metawa and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-10 with Business & Economics categories.
Throughout the industry, financial institutions seek to eliminate cumbersome authentication methods, such as PINs, passwords, and security questions, as these antiquated tactics prove increasingly weak. Thus, many organizations now aim to implement emerging technologies in an effort to validate identities with greater certainty. The near instantaneous nature of online banking, purchases, transactions, and payments puts tremendous pressure on banks to secure their operations and procedures. In order to reduce the risk of human error in financial domains, expert systems are seen to offer a great advantage in big data environments. Besides their efficiency in quantitative analysis such as profitability, banking management, and strategic financial planning, expert systems have successfully treated qualitative issues including financial analysis, investment advisories, and knowledge-based decision support systems. Due to the increase in financial applications’ size, complexity, and number of components, it is no longer practical to anticipate and model all possible interactions and data processing in these applications using the traditional data processing model. The emergence of new research areas is clear evidence of the rise of new demands and requirements of modern real-life applications to be more intelligent. This book provides an exhaustive review of the roles of expert systems within the financial sector, with particular reference to big data environments. In addition, it offers a collection of high-quality research that addresses broad challenges in both theoretical and application aspects of intelligent and expert systems in finance. The book serves to aid the continued efforts of the application of intelligent systems that respond to the problem of big data processing in a smart banking and financial environment.
Building A Data Culture In The Ministry Of Finance
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Author : Dody Dharma Hutabarat
language : en
Publisher: Central Transformation Office, Sekretariat Jenderal, Kementerian Keuangan
Release Date : 2022-03-02
Building A Data Culture In The Ministry Of Finance written by Dody Dharma Hutabarat and has been published by Central Transformation Office, Sekretariat Jenderal, Kementerian Keuangan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Computers categories.
The book is prepared as a general guide for stakeholders in the Ministry of Finance, especially the leaders, on how to lead their working units to be data-driven. In the Ministry of Finance, the volume of data grows massively. The data grow so rapidly that the Minister of Finance illustrates the condition by stating that “We, at the Ministry of Finance, are actually sitting on a large pile of data. This is a new type of mine. In digital era, the mine refers to the mine of data. However, of course they have to be the data we process and understand.” Ideally, the availability of data will encourage better formulation of policies and decision making. However, such effort is not an easy task, it is a challenging one instead. One of the main challenges in data utilization is that data culture has not been developed yet. The opportunity to optimize data utilization gets fresh air as awareness and understanding of data start to grow in some internal areas of the Ministry of Finance. Starting from the background, the book is compiled to become a guide for leaders and employees of the Ministry of Finance in building data culture in the Ministry of Finance. The book introduces cultural approach to develop and utilize data analytics skills in the Ministry of Finance. Hopefully, the book will keep being renewed in accordance with the development of science, technology, needs, and public discussion.
Detecting Regime Change In Computational Finance
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Author : Jun Chen
language : en
Publisher: CRC Press
Release Date : 2020-09-14
Detecting Regime Change In Computational Finance written by Jun Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-14 with Computers categories.
Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarising price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzags"). By sampling data in a different way, this book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning and data science. About the Authors Jun Chen received his PhD in computational finance from the Centre for Computational Finance and Economic Agents, University of Essex in 2019. Edward P K Tsang is an Emeritus Professor at the University of Essex, where he co-founded the Centre for Computational Finance and Economic Agents in 2002.
Machine Learning And Data Sciences For Financial Markets
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Author : Agostino Capponi
language : en
Publisher: Cambridge University Press
Release Date : 2023-04-30
Machine Learning And Data Sciences For Financial Markets written by Agostino Capponi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-30 with Mathematics categories.
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.
Financial Decision Making Using Computational Intelligence
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Author : Michael Doumpos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-23
Financial Decision Making Using Computational Intelligence written by Michael Doumpos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-23 with Business & Economics categories.
The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.