Nonlinear Dynamics and Economics
Nonlinear Dynamics and Economics

Author: William A. Barnett

Publisher: Cambridge University Press

Published: 1996-10-28

Total Pages: 426

ISBN-13: 9780521471411

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This 1997 book presents developments in nonlinear economic dynamics along with related research from other fields, including mathematics, statistics, biology, and physics.

Forecasting and Hedging in the Foreign Exchange Markets
Forecasting and Hedging in the Foreign Exchange Markets

Author: Christian Ullrich

Publisher: Springer Science & Business Media

Published: 2009-05-30

Total Pages: 206

ISBN-13: 3642004954

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Historical and recent developments at international ?nancial markets show that it is easy to loose money, while it is dif?cult to predict future developments and op- mize decision-making towards maximizing returns and minimizing risk. One of the reasons of our inability to make reliable predictions and to make optimal decisions is the growing complexity of the global economy. This is especially true for the f- eign exchange market (FX market) which is considered as one of the largest and most liquid ?nancial markets. Its grade of ef?ciencyand its complexityis one of the starting points of this volume. From the high complexity of the FX market, Christian Ullrich deduces the - cessity to use tools from machine learning and arti?cial intelligence, e.g., support vector machines, and to combine such methods with sophisticated ?nancial mod- ing techniques. The suitability of this combination of ideas is demonstrated by an empirical study and by simulation. I am pleased to introduce this book to its - dience, hoping that it will provide the reader with interesting ideas to support the understanding of FX markets and to help to improve risk management in dif?cult times. Moreover, I hope that its publication will stimulate further research to contribute to the solution of the many open questions in this area.

Nonlinear Dynamics, Chaos, and Instability
Nonlinear Dynamics, Chaos, and Instability

Author: William A. Brock

Publisher: MIT Press

Published: 1991

Total Pages: 362

ISBN-13: 9780262023290

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Brock, Hsieh, and LeBaron show how the principles of chaos theory can be applied to such areas of economics and finance as the changing structure of stock returns and nonlinearity in foreign exchange.

Anatomy of Global Stock Market Crashes
Anatomy of Global Stock Market Crashes

Author: Gagari Chakrabarti

Publisher: Springer Science & Business Media

Published: 2012-01-05

Total Pages: 69

ISBN-13: 813220462X

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This work is an exploration of the global market dynamics, their intrinsic natures, common trends and dynamic interlinkages during the stock market crises over the last twelve years. The study isolates different phases of crisis and differentiates between any crisis that remains confined to the region and those that take up a global dimension. The latent structure of the global stock market, the inter-regional and intra-regional stock market dynamics around the crises are analyzed to get a complete picture of the structure of the global stock market. The study further probing into the inherent nature of the global stock market in generating crisis finds the global market to be chaotic thus making the system intrinsically unstable or at best to follow knife-edge stability. The findings have significant bearing at theoretical level and on policy decisions.

Data Analytics for Management, Banking and Finance
Data Analytics for Management, Banking and Finance

Author: Foued Saâdaoui

Publisher: Springer Nature

Published: 2023-09-19

Total Pages: 338

ISBN-13: 3031365704

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This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance. It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies. The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks

Non-linear Time Series
Non-linear Time Series

Author: Howell Tong

Publisher: Oxford University Press, USA

Published: 1990

Total Pages: 592

ISBN-13:

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Written by an internationally recognized expert in the field, this book provides a valuable introduction to the rapidly growing area of non-linear time series. Because developments in the study of dynamical systems have motivated many of the advances discussed here, the author's coverage includes such fundamental concepts of dynamical systems theory as limit cycles, Lyapunov functions, thresholds, and stability, with detailed descriptions of their role in the analysis of non-linear time series data. As the first accessible and comprehensive account of these exciting new developments, this unique volume bridges the gap between linear and chaotic time series analysis. Both statisticians and dynamical systems theorists will value its survey of recent developments and the present state of research, as well as the discussion of a number of unsolved problems in the field.

Big Data, IoT, and Machine Learning
Big Data, IoT, and Machine Learning

Author: Rashmi Agrawal

Publisher: CRC Press

Published: 2020-07-29

Total Pages: 249

ISBN-13: 1000098303

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The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases