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Author:
Publisher:
ISBN:
Category : Canada
Languages : en
Pages : 1252
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Book Description
Author:
Publisher:
ISBN:
Category : Canada
Languages : en
Pages : 1252
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Book Description
Author: Library of Congress. Copyright Office
Publisher: Copyright Office, Library of Congress
ISBN:
Category : Copyright
Languages : en
Pages : 1406
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Book Description
Author: Library of Congress. Copyright Office
Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 1422
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Book Description
Author: David S. Bright
Publisher:
ISBN: 9781998109166
Category :
Languages : en
Pages : 0
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Book Description
Black & white print. Principles of Management is designed to meet the scope and sequence requirements of the introductory course on management. This is a traditional approach to management using the leading, planning, organizing, and controlling approach. Management is a broad business discipline, and the Principles of Management course covers many management areas such as human resource management and strategic management, as well as behavioral areas such as motivation. No one individual can be an expert in all areas of management, so an additional benefit of this text is that specialists in a variety of areas have authored individual chapters.
Author: Library of Congress. Copyright Office
Publisher:
ISBN:
Category : Copyright
Languages : en
Pages : 1406
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Book Description
The record of each copyright registration listed in the Catalog includes a description of the work copyrighted and data relating to the copyright claim (the name of the copyright claimant as given in the application for registration, the copyright date, the copyright registration number, etc.).
Author:
Publisher:
ISBN:
Category : Accounting
Languages : en
Pages : 474
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Book Description
Author: Douglas Allen Lauriston Auld
Publisher: New York : Harper & Row
ISBN: 9780060440527
Category : Economics
Languages : en
Pages : 324
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Book Description
Author:
Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 3054
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Book Description
Author: Library of Congress. Copyright Office
Publisher:
ISBN:
Category : American drama
Languages : en
Pages : 1512
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Book Description
Author: Matthew F. Dixon
Publisher: Springer Nature
ISBN: 3030410684
Category : Business & Economics
Languages : en
Pages : 565
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Book Description
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
