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A practical guide to static and dynamic econometric modelling = examples and analysis with Python code embedded /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A practical guide to static and dynamic econometric modelling/ by Sarit Maitra.
Reminder of title:	examples and analysis with Python code embedded /
Author:	Maitra, Sarit.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xiii, 201 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Introduction to Econometrics and Linear Regression -- Hypothesis(es) testing -- Dynamic modelling in Econometrics Foundational knowledge -- Theoretical overview: Capital Asset Pricing and Arbitrage Pricing Theory -- Model implementation and testing -- January effect -- Key takeaways.
Contained By:	Springer Nature eBook
Subject:	Econometric models. -
Online resource:	https://doi.org/10.1007/978-3-031-86862-7
ISBN:	9783031868627

A practical guide to static and dynamic econometric modelling = examples and analysis with Python code embedded /
Maitra, Sarit.

A practical guide to static and dynamic econometric modellingexamples and analysis with Python code embedded /[electronic resource] :by Sarit Maitra. - Cham :Springer Nature Switzerland :2025. - xiii, 201 p. :ill. (some col.), digital ;24 cm. - Contributions to econometrics and empirical economics,3059-4650. - Contributions to econometrics and empirical economics..

Introduction to Econometrics and Linear Regression -- Hypothesis(es) testing -- Dynamic modelling in Econometrics Foundational knowledge -- Theoretical overview: Capital Asset Pricing and Arbitrage Pricing Theory -- Model implementation and testing -- January effect -- Key takeaways.

This book provides a comprehensive guide to econometric modeling, combining theory with practical implementation using Python. It covers key econometric concepts, from data collection and model specification to estimation, inference, and prediction. Readers will explore linear regression, data transformations, and hypothesis testing, along with advanced topics like the Capital Asset Pricing Model and dynamic modeling techniques. With Python code examples, this book bridges theory and practice, making it an essential resource for students, finance professionals, economists, and data scientists seeking to apply econometrics in real-world scenarios.

ISBN: 9783031868627

Standard No.: 10.1007/978-3-031-86862-7doiSubjects--Topical Terms:

542933
Econometric models.

LC Class. No.: HB141

Dewey Class. No.: 330.015195

A practical guide to static and dynamic econometric modelling = examples and analysis with Python code embedded /
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100 1 $a Maitra, Sarit. $3 3786087
245 1 2 $a A practical guide to static and dynamic econometric modelling $h [electronic resource] : $b examples and analysis with Python code embedded / $c by Sarit Maitra.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xiii, 201 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Contributions to econometrics and empirical economics, $x 3059-4650
505 0 $a Introduction to Econometrics and Linear Regression -- Hypothesis(es) testing -- Dynamic modelling in Econometrics Foundational knowledge -- Theoretical overview: Capital Asset Pricing and Arbitrage Pricing Theory -- Model implementation and testing -- January effect -- Key takeaways.
520 $a This book provides a comprehensive guide to econometric modeling, combining theory with practical implementation using Python. It covers key econometric concepts, from data collection and model specification to estimation, inference, and prediction. Readers will explore linear regression, data transformations, and hypothesis testing, along with advanced topics like the Capital Asset Pricing Model and dynamic modeling techniques. With Python code examples, this book bridges theory and practice, making it an essential resource for students, finance professionals, economists, and data scientists seeking to apply econometrics in real-world scenarios.
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650 0 $a Python (Computer program language) $3 729789
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650 2 4 $a Quantitative Economics. $3 3538570
650 2 4 $a Statistics in Business, Management, Economics, Finance, Insurance. $3 3538572
650 2 4 $a Corporate Finance. $2 swd $3 1655050
710 2 $a SpringerLink (Online service) $3 836513
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830 0 $a Contributions to econometrics and empirical economics. $3 3786088
856 4 0 $u https://doi.org/10.1007/978-3-031-86862-7
950 $a Economics and Finance (SpringerNature-41170)