Datamining Und Computational Finance
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Datamining Und Computational Finance
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Author : Georg Bol
language : de
Publisher: Springer-Verlag
Release Date : 2013-03-07
Datamining Und Computational Finance written by Georg Bol and has been published by Springer-Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-07 with Computers categories.
Der Schwerpunkt des siebten Karlsruher Ökonometrie-Workshops lag auf der Anwendung Neuronaler Netze bei Finanzzeitreihen, dem Einsatz von Datamining und Maschinellen Lernverfahren bei Fragestellungen des Finanzbereichs und quantitativen Methoden zur Beurteilung von Markt- und Länderrisiken. Das Spektrum ausgewählter Referate in diesem Buch, u.a. auch von international renommierten Experten, reicht von allgemeinen Betrachtungen zur Prognose mit Neuronalen Netzen und empirischen Ergebnissen für Wechselkurse, Rentenmärkte und Absatzzahlen über die Beurteilung von Marktrisiken und die Kreditüberwachung mit Maschinellen Lernverfahren bis zur Ermittlung und Einschätzung von Länderrisiken. Dieser Band berichtet über die aktuelle Entwicklung in diesen Gebieten und bietet ein Forum für Diskussionen.
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.
Data Mining In Finance
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Author : Boris Kovalerchuk
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-11
Data Mining In Finance written by Boris Kovalerchuk 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 2005-12-11 with Computers categories.
Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book focuses specifically on relational data mining (RDM), which is a learning method able to learn more expressive rules than other symbolic approaches. RDM is thus better suited for financial mining, because it is able to make greater use of underlying domain knowledge. Relational data mining also has a better ability to explain the discovered rules - an ability critical for avoiding spurious patterns which inevitably arise when the number of variables examined is very large. The earlier algorithms for relational data mining, also known as inductive logic programming (ILP), suffer from a relative computational inefficiency and have rather limited tools for processing numerical data. Data Mining in Finance introduces a new approach, combining relational data mining with the analysis of statistical significance of discovered rules. This reduces the search space and speeds up the algorithms. The book also presents interactive and fuzzy-logic tools for `mining' the knowledge from the experts, further reducing the search space. Data Mining in Finance contains a number of practical examples of forecasting S&P 500, exchange rates, stock directions, and rating stocks for portfolio, allowing interested readers to start building their own models. This book is an excellent reference for researchers and professionals in the fields of artificial intelligence, machine learning, data mining, knowledge discovery, and applied mathematics.
Perception Based Data Mining And Decision Making In Economics And Finance
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Author : Ildar Batyrshin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-03-15
Perception Based Data Mining And Decision Making In Economics And Finance written by Ildar Batyrshin 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 2007-03-15 with Computers categories.
The primary goal of this book is to present to the scientific and management communities a selection of applications using recent Soft Computing (SC) and Computing with Words and Perceptions (CWP) models and techniques meant to solve some economics and financial problems that are of utmost importance. The book starts with a coverage of data mining tools and techniques that may be of use and significance for economic and financial analyses and applications. Notably, fuzzy and natural language based approaches and solutions for a more human consistent dealing with decision support, time series analysis, forecasting, clustering, etc. are discussed. The second part deals with various decision making models, particularly under probabilistic and fuzzy uncertainty, and their applications in solving a wide array of problems including portfolio optimization, option pricing, financial engineering, risk analysis etc. The selected examples could also serve as a starting point or as an opening out, in the SC and CWP techniques application to a wider range of problems in economics and finance.
Computational Finance And Its Applications Iii
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Author : M. Costantino
language : en
Publisher: WIT Press
Release Date : 2008
Computational Finance And Its Applications Iii 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.
Featuring papers from the Third International Conference on Computational Finance and its Applications, the text includes papers that encompass a wide range of topics such as modern financial services technologies, derivatives pricing, portfolio management and asset allocation, and intelligent trading agents.
Computational Finance 1999
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Author : Yaser S. Abu-Mostafa
language : en
Publisher: MIT Press
Release Date : 2000
Computational Finance 1999 written by Yaser S. Abu-Mostafa and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Business & Economics categories.
This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an exciting new cross-disciplinary research area, draws extensively on the tools and techniques of computer science, statistics, information systems, and financial economics. This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. These methods are applied to a wide range of problems in finance, including risk management, asset allocation, style analysis, dynamic trading and hedging, forecasting, and option pricing. The book is based on the sixth annual international conference Computational Finance 1999, held at New York University's Stern School of Business.
Contemporary Experimental Design Multivariate Analysis And Data Mining
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Author : Jianqing Fan
language : en
Publisher: Springer Nature
Release Date : 2020-05-22
Contemporary Experimental Design Multivariate Analysis And Data Mining written by Jianqing Fan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-22 with Mathematics categories.
The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features four review papers on Professor Fang’s numerous contributions to the fields of experimental design, multivariate analysis, data mining and education. It also contains twenty research articles contributed by prominent and active figures in their fields. The articles cover a wide range of important topics such as experimental design, multivariate analysis, data mining, hypothesis testing and statistical models.
Recent Advancements In Computational Finance And Business Analytics
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Author : Rangan Gupta
language : en
Publisher: Springer Nature
Release Date : 2023-10-29
Recent Advancements In Computational Finance And Business Analytics written by Rangan Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-29 with Technology & Engineering categories.
Recent Advancements of Computational Finance and Business Analytics provide a comprehensive overview of the cutting-edge advancements in this dynamic field. By embracing computational finance and business analytics, organizations can gain a competitive edge in an increasingly data-driven and complex business environment. This book has explored the latest developments and breakthroughs in this rapidly evolving domain, providing a comprehensive overview of the current state of computational finance and business analytics. It covers the following dimensions of this domains: Business Analytics Financial Analytics Human Resource Analytics Marketing Analytics
Handbook Of Computational Finance
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Author : Jin-Chuan Duan
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-10-25
Handbook Of Computational Finance written by Jin-Chuan Duan 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 2011-10-25 with Business & Economics categories.
Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.
Introduction To Data Mining And Its Applications
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Author : S. Sumathi
language : en
Publisher: Springer
Release Date : 2006-10-12
Introduction To Data Mining And Its Applications written by S. Sumathi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-12 with Computers categories.
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.