Home eBooks Download › stochastic modelling of big data in finance

Stochastic Modelling Of Big Data In Finance

Download Stochastic Modelling Of Big Data In Finance PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Stochastic Modelling Of Big Data In Finance book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Stochastic Modelling Of Big Data In Finance

DOWNLOAD
Author : Anatoliy Swishchuk
language : en
Publisher: CRC Press
Release Date : 2022-11-08

Stochastic Modelling Of Big Data In Finance written by Anatoliy Swishchuk and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-08 with Business & Economics categories.

Stochastic Modelling of Big Data in Finance provides a rigorous overview and exploration of stochastic modelling of big data in finance (BDF). The book describes various stochastic models, including multivariate models, to deal with big data in finance. This includes data in high-frequency and algorithmic trading, specifically in limit order books (LOB), and shows how those models can be applied to different datasets to describe the dynamics of LOB, and to figure out which model is the best with respect to a specific data set. The results of the book may be used to also solve acquisition, liquidation and market making problems, and other optimization problems in finance. Features Self-contained book suitable for graduate students and post-doctoral fellows in financial mathematics and data science, as well as for practitioners working in the financial industry who deal with big data All results are presented visually to aid in understanding of concepts Dr. Anatoliy Swishchuk is a Professor in Mathematical Finance at the Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada. He got his B.Sc. and M.Sc. degrees from Kyiv State University, Kyiv, Ukraine. He earned two doctorate degrees in Mathematics and Physics (PhD and DSc) from the prestigious National Academy of Sciences of Ukraine (NASU), Kiev, Ukraine, and is a recipient of NASU award for young scientist with a gold medal for series of research publications in random evolutions and their applications. Dr. Swishchuk is a chair and organizer of finance and energy finance seminar ‘Lunch at the Lab’ at the Department of Mathematics and Statistics. Dr. Swishchuk is a Director of Mathematical and Computational Finance Laboratory at the University of Calgary. He was a steering committee member of the Professional Risk Managers International Association (PRMIA), Canada (2006-2015), and is a steering committee member of Global Association of Risk Professionals (GARP), Canada (since 2015). Dr. Swishchuk is a creator of mathematical finance program at the Department of Mathematics & Statistics. He is also a proponent for a new specialization “Financial and Energy Markets Data Modelling” in the Data Science and Analytics program. His research areas include financial mathematics, random evolutions and their applications, biomathematics, stochastic calculus, and he serves on editorial boards for four research journals. He is the author of more than 200 publications, including 15 books and more than 150 articles in peer-reviewed journals. In 2018 he received a Peak Scholar award.

Option Theory With Stochastic Analysis

DOWNLOAD
Author : Fred Espen Benth
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Option Theory With Stochastic Analysis written by Fred Espen Benth 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 2012-12-06 with Business & Economics categories.

This is a very basic and accessible introduction to option pricing, invoking a minimum of stochastic analysis and requiring only basic mathematical skills. It covers the theory essential to the statistical modeling of stocks, pricing of derivatives with martingale theory, and computational finance including both finite-difference and Monte Carlo methods.

Big Data Science In Finance

DOWNLOAD
Author : Irene Aldridge
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-27

Big Data Science In Finance written by Irene Aldridge 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 2021-01-27 with Computers categories.

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.

Stochastic Simulation And Applications In Finance With Matlab Programs

DOWNLOAD
Author : Huu Tue Huynh
language : en
Publisher: John Wiley & Sons
Release Date : 2008-12-22

Stochastic Simulation And Applications In Finance With Matlab Programs written by Huu Tue Huynh 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 2008-12-22 with Business & Economics categories.

Stochastic Simulation and Applications in Finance with MATLAB Programs explains the fundamentals of Monte Carlo simulation techniques, their use in the numerical resolution of stochastic differential equations and their current applications in finance. Building on an integrated approach, it provides a pedagogical treatment of the need-to-know materials in risk management and financial engineering. The book takes readers through the basic concepts, covering the most recent research and problems in the area, including: the quadratic re-sampling technique, the Least Squared Method, the dynamic programming and Stratified State Aggregation technique to price American options, the extreme value simulation technique to price exotic options and the retrieval of volatility method to estimate Greeks. The authors also present modern term structure of interest rate models and pricing swaptions with the BGM market model, and give a full explanation of corporate securities valuation and credit risk based on the structural approach of Merton. Case studies on financial guarantees illustrate how to implement the simulation techniques in pricing and hedging. NOTE TO READER: The CD has been converted to URL. Go to the following website www.wiley.com/go/huyhnstochastic which provides MATLAB programs for the practical examples and case studies, which will give the reader confidence in using and adapting specific ways to solve problems involving stochastic processes in finance.

An Introduction To Stochastic Modeling

DOWNLOAD
Author : Howard M. Taylor
language : en
Publisher: Academic Press
Release Date : 2014-05-10

An Introduction To Stochastic Modeling written by Howard M. Taylor and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Mathematics categories.

An Introduction to Stochastic Modeling, Revised Edition provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Big Data Science In Finance

DOWNLOAD
Author : Irene Aldridge
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-08

Macroeconomic Forecasting In The Era Of Big Data

DOWNLOAD
Author : Peter Fuleky
language : en
Publisher: Springer Nature
Release Date : 2019-11-28

Macroeconomic Forecasting In The Era Of Big Data written by Peter Fuleky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Business & Economics categories.

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Handbook Of Big Data Technologies

DOWNLOAD
Author : Albert Y. Zomaya
language : en
Publisher: Springer
Release Date : 2017-02-25

Handbook Of Big Data Technologies written by Albert Y. Zomaya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-25 with Computers categories.

This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalable graph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains. Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.

Optimization And Control For Systems In The Big Data Era

DOWNLOAD
Author : Tsan-Ming Choi
language : en
Publisher: Springer
Release Date : 2017-05-04

Optimization And Control For Systems In The Big Data Era written by Tsan-Ming Choi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-04 with Business & Economics categories.

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Proceedings Of The 5th International Conference On Economic Management And Big Data Application Icembda 2024

DOWNLOAD
Author : Kun Zhang
language : en
Publisher: Springer Nature
Release Date : 2024-12-29

Proceedings Of The 5th International Conference On Economic Management And Big Data Application Icembda 2024 written by Kun Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-29 with Business & Economics categories.

This is an open access book. The 5th International Conference on Economic Management and Big Data Applications (ICEMBDA 2024) is scheduled to be held in Tianjin, China on October 25–27, 2024. The 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024) is an essential forum for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of economic management and big data analytics. Scheduled to be held in an era marked by rapidly evolving digital technologies, ICEMBDA 2024 aims to bridge the gap between big data technologies and their practical implementation in economic management. Background The integration of big data analytics into economic management has revolutionized decision-making processes by enabling more precise, evidence-based strategies that potentially lead to superior outcomes. As big data continues to grow in volume, variety, and velocity, the necessity for its application in economic strategies and policies has never been more critical. ICEMBDA 2024 addresses this urgency, acting as a pivotal platform for academic and industry professionals to synergize knowledge and foster advancements. Conference Themes ICEMBDA 2024 will center around a wide range of themes pertinent to the intersection of economics, management, and big data: Big Data Analytics and Economic Forecasting - Utilizing big data in predictive analytics to forecast economic trends and inform policy making. Data-Driven Decision Making in Business and Economics - Methods and technologies that support data-driven strategies in businesses and economic institutions. Ethics and Privacy in Big Data - Addressing the ethical considerations and privacy concerns arising from extensive big data utilization in economic management. Technological Innovations in Big Data - Exploring advancements in data processing, AI, and machine learning that enhance economic data analysis. Impact of Big Data on Economic Policy and Management - Examining how big data has transformed public and private sector economics, focusing on efficiency, accuracy, and compliance. Case Studies on Big Data Applications in Various Economic Sectors - Success stories and lessons learned from applying big data solutions across different branches of economics.

Stochastic Modelling Of Big Data In Finance

Recent Posts