Pattern Recognition Of Stochastic Processes In Market Data
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Pattern Recognition Of Stochastic Processes In Market Data
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Author : Silas Nyabwala Onyango
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2013
Pattern Recognition Of Stochastic Processes In Market Data written by Silas Nyabwala Onyango and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
This book introduces Stochastic Processes and its applications in Finance. It also combines Artificial Intelligence with Finance. The Hough Transformation is used to identify stochastic processes in dynamical systems. Mathematics of Wiener processes are treated in detail and their applications in different markets are shown. The Hough transform is used to locate market processes where transactions occur within the market.
Learning Representation For Multi View Data Analysis
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Author : Zhengming Ding
language : en
Publisher: Springer
Release Date : 2018-12-06
Learning Representation For Multi View Data Analysis written by Zhengming Ding and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-06 with Computers categories.
This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.
Data Science Learning By Latent Structures And Knowledge Discovery
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Author : Berthold Lausen
language : en
Publisher: Springer
Release Date : 2015-05-06
Data Science Learning By Latent Structures And Knowledge Discovery written by Berthold Lausen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-06 with Mathematics categories.
This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
Technical Analysis For Algorithmic Pattern Recognition
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Author : Prodromos E. Tsinaslanidis
language : en
Publisher: Springer
Release Date : 2015-10-31
Technical Analysis For Algorithmic Pattern Recognition written by Prodromos E. Tsinaslanidis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-31 with Business & Economics categories.
The main purpose of this book is to resolve deficiencies and limitations that currently exist when using Technical Analysis (TA). Particularly, TA is being used either by academics as an “economic test” of the weak-form Efficient Market Hypothesis (EMH) or by practitioners as a main or supplementary tool for deriving trading signals. This book approaches TA in a systematic way utilizing all the available estimation theory and tests. This is achieved through the developing of novel rule-based pattern recognizers, and the implementation of statistical tests for assessing the importance of realized returns. More emphasis is given to technical patterns where subjectivity in their identification process is apparent. Our proposed methodology is based on the algorithmic and thus unbiased pattern recognition. The unified methodological framework presented in this book can serve as a benchmark for both future academic studies that test the null hypothesis of the weak-form EMH and for practitioners that want to embed TA within their trading/investment decision making processes.
Structural Syntactic And Statistical Pattern Recognition
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Author : Antonio Robles-Kelly
language : en
Publisher: Springer
Release Date : 2016-11-04
Structural Syntactic And Statistical Pattern Recognition written by Antonio Robles-Kelly and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Computers categories.
This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The 51 full papers presented were carefully reviewed and selected from 68 submissions. They are organized in the following topical sections: dimensionality reduction, manifold learning and embedding methods; dissimilarity representations; graph-theoretic methods; model selection, classification and clustering; semi and fully supervised learning methods; shape analysis; spatio-temporal pattern recognition; structural matching; text and document analysis.
Marketing Research Methods
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Author : Mercedes Esteban-Bravo
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-28
Marketing Research Methods written by Mercedes Esteban-Bravo 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 2021-01-28 with Business & Economics categories.
Academically thorough and up-to-date quantitative and qualitative market research methods text for business and social science students.
Machine Learning And Data Mining In Pattern Recognition
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2014-07-17
Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-17 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Stochastic Processes And Financial Markets
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Author : Jitendra C. Parikh
language : en
Publisher: Alpha Science Int'l Ltd.
Release Date : 2003
Stochastic Processes And Financial Markets written by Jitendra C. Parikh and has been published by Alpha Science Int'l Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.
Aimed at providing an introduction to fundamental concepts and mathematical foundations essential for studying dynamics of financial markets, this volume focuses on stochastic processes and the manner in which they provide the basic framework for modeling the markets. Key Feautres: The book is mathematical in nature, but is not heavy on proofs Contains many examples Simulations and analysis of real data from different financial markets The overall objective is to make the presentation concrete and illustrate successes and limitations of models. In the process, readers are also made aware of a number of advances in the field.
Monetising Data
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Author : Andrea Ahlemeyer-Stubbe
language : en
Publisher: John Wiley & Sons
Release Date : 2018-02-01
Monetising Data written by Andrea Ahlemeyer-Stubbe 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 2018-02-01 with Mathematics categories.
Practical guide for deriving insight and commercial gain from data Monetising Data offers a practical guide for anyone working with commercial data but lacking deep knowledge of statistics or data mining. The authors — noted experts in the field — show how to generate extra benefit from data already collected and how to use it to solve business problems. In accessible terms, the book details ways to extract data to enhance business practices and offers information on important topics such as data handling and management, statistical methods, graphics and business issues. The text presents a wide range of illustrative case studies and examples to demonstrate how to adapt the ideas towards monetisation, no matter the size or type of organisation. The authors explain on a general level how data is cleaned and matched between data sets and how we learn from data analytics to address vital business issues. The book clearly shows how to analyse and organise data to identify people and follow and interact with them through the customer lifecycle. Monetising Data is an important resource: Focuses on different business scenarios and opportunities to turn data into value Gives an overview on how to store, manage and maintain data Presents mechanisms for using knowledge from data analytics to improve the business and increase profits Includes practical suggestions for identifying business issues from the data Written for everyone engaged in improving the performance of a company, including managers and students, Monetising Data is an essential guide for understanding and using data to enrich business practice.
Introduction To Stochastic Processes Using R
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Author : Sivaprasad Madhira
language : en
Publisher: Springer
Release Date : 2023-11-17
Introduction To Stochastic Processes Using R written by Sivaprasad Madhira and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-17 with Business & Economics categories.
This textbook presents some basic stochastic processes, mainly Markov processes. It begins with a brief introduction to the framework of stochastic processes followed by the thorough discussion on Markov chains, which is the simplest and the most important class of stochastic processes. The book then elaborates the theory of Markov chains in detail including classification of states, the first passage distribution, the concept of periodicity and the limiting behaviour of a Markov chain in terms of associated stationary and long run distributions. The book first illustrates the theory for some typical Markov chains, such as random walk, gambler's ruin problem, Ehrenfest model and Bienayme-Galton-Watson branching process; and then extends the discussion when time parameter is continuous. It presents some important examples of a continuous time Markov chain, which include Poisson process, birth process, death process, birth and death processes and their variations. These processes play a fundamental role in the theory and applications in queuing and inventory models, population growth, epidemiology and engineering systems. The book studies in detail the Poisson process, which is the most frequently applied stochastic process in a variety of fields, with its extension to a renewal process. The book also presents important basic concepts on Brownian motion process, a stochastic process of historic importance. It covers its few extensions and variations, such as Brownian bridge, geometric Brownian motion process, which have applications in finance, stock markets, inventory etc. The book is designed primarily to serve as a textbook for a one semester introductory course in stochastic processes, in a post-graduate program, such as Statistics, Mathematics, Data Science and Finance. It can also be used for relevant courses in other disciplines. Additionally, it provides sufficient background material for studying inference in stochastic processes. The book thus fulfils the need of a concise but clear and student-friendly introduction to various types of stochastic processes.