Mining Data For Financial Applications

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Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes

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Author : Cheng Few Lee
language : en
Publisher: World Scientific
Release Date : 2020-07-30

Handbook Of Financial Econometrics Mathematics Statistics And Machine Learning In 4 Volumes written by Cheng Few Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Business & Economics categories.

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.

Practical Applications Of Data Mining

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Author : Sang Suh
language : en
Publisher: Jones & Bartlett Publishers
Release Date : 2012

Practical Applications Of Data Mining written by Sang Suh and has been published by Jones & Bartlett Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.

Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.

Mining Data For Financial Applications

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Author : Valerio Bitetta
language : en
Publisher: Springer
Release Date : 2020-01-04

Mining Data For Financial Applications written by Valerio Bitetta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-04 with Computers categories.

This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held in conjunction with ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain.

Data Mining Applications With R

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Author : Yanchang Zhao
language : en
Publisher: Academic Press
Release Date : 2013-11-26

Data Mining Applications With R written by Yanchang Zhao and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-26 with Computers categories.

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. - Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries - Presents various case studies in real-world applications, which will help readers to apply the techniques in their work - Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

Data Mining For Business Applications

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Author : Carlos A. Mota Soares
language : en
Publisher: IOS Press
Release Date : 2010

Data Mining For Business Applications written by Carlos A. Mota Soares and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.

Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.

Optimization Based Data Mining Theory And Applications

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Author : Yong Shi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-16

Optimization Based Data Mining Theory And Applications written by Yong Shi 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 2011-05-16 with Computers categories.

Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.

Data Mining Methods And Applications

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Author : Kenneth D. Lawrence
language : en
Publisher: Auerbach Publications
Release Date : 2008

Data Mining Methods And Applications written by Kenneth D. Lawrence and has been published by Auerbach Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Business & Economics categories.

Addressing a variety of organizational issues, Data Mining Methods and Applications presents a compilation of recent research works on data mining and forecasting techniques, including multivariate, evolutionary, and neural net methods. This book focuses in particular on data mining techniques used for conducting marketing research. Written by a wide range of contributors from academia and industry, this text provides detailed descriptions of applications in numerous areas, such as finance, engineering, healthcare, economics, science, and management. Real-world case studies that are supported by theoretical chapters offer guidance on how to actually perform data mining methods.

Data Mining

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Author : Georg Zangl
language : en
Publisher:
Release Date : 2003

Data Mining written by Georg Zangl and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

Data Mining

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Author : Yong Yin
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-16

Data Mining written by Yong Yin 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 2011-03-16 with Computers categories.

Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems. Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including: • supply chain design, • product development, • manufacturing system design, • product quality control, and • preservation of privacy. Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.

Novel Financial Applications Of Machine Learning And Deep Learning

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Author : Mohammad Zoynul Abedin
language : en
Publisher: Springer Nature
Release Date : 2023-03-01

Novel Financial Applications Of Machine Learning And Deep Learning written by Mohammad Zoynul Abedin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Business & Economics categories.

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.