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Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: good. This book is in good condition. The cover has minor creases or bends. The binding is tight and pages are intact. Some pages may have writing or highlighting.
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Tidy Finance with Python
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: New.
-
Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: As New. Unread book in perfect condition.
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Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: New. 1st edition NO-PA16APR2015-KAP.
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Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: New.
-
Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC 2024-07-15, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Paperback. Condition: New.
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Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Tidy Finance with Python
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 453.
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Paperback. Condition: Brand New. 272 pages. 10.00x7.00x10.00 inches. In Stock.
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Tidy Finance with Python
Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.
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Tidy Finance with Python
Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.
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Paperback. Condition: Brand New. 272 pages. 10.00x7.00x10.00 inches. In Stock.
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Condition: New. Christoph Frey is a Quantitative Researcher and Portfolio Manager at a family office in Hamburg and a Research Fellow at the Centre for Financial Econometrics, Asset Markets and Macroeconomic Policy at Lancaster University. Prior to this, he was t.
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Tidy Finance with Python
Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.
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Tidy Finance with Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Taschenbuch. Condition: Neu. Tidy Finance with Python | Christoph Scheuch (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9781032676418 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Tidy Finance with Python
Published by Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Paperback. Condition: New. This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques.Key Features:Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader's research or as a reference for courses on empirical finance.Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide.A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods.We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics.Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.
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Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
-
Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Condition: New.
-
Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Condition: New.
-
Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Condition: New. 1st edition NO-PA16APR2015-KAP.
-
Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Condition: As New. Unread book in perfect condition.
-
Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
-
Tidy Finance With Python
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
-
Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032684291 ISBN 13: 9781032684291
Language: English
Condition: New.
-
Hardcover. Condition: Brand New. 272 pages. 10.00x7.00x10.00 inches. In Stock.
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Tidy Finance with Python (Chapman & Hall/CRC The Python Series)
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Condition: New. PRINT ON DEMAND.
-
Tidy Finance with Python
Published by Chapman And Hall/CRC, 2024
ISBN 10: 1032676418 ISBN 13: 9781032676418
Language: English
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch.
