A Practical Guide to Static and Dynamic Econometric Modelling: Examples and Analysis With Python Code Embedded - Rilegato

Maitra, Sarit

 
9783031868610: A Practical Guide to Static and Dynamic Econometric Modelling: Examples and Analysis With Python Code Embedded
Rilegato
ISBN 10: 3031868617 ISBN 13: 9783031868610
Casa editrice: Springer Nature, 2025

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Dr. Sarit Maitra is a seasoned business leader and academic with over 25 years of experience in the industry and academia, specializing in business analytics, data science, and information technology. With a PhD and MS in Information Technology from Universiti Teknologi PETRONAS, Malaysia, he has held pivotal roles in various global organizations. Currently, as a Professor at Alliance University in Bengaluru, India, Dr. Maitra leverages his extensive industry experience to deliver courses in operations analytics, business analytics, and Big data Analytics. He is passionate about data-driven business, and his research spans business analytics (simulation, stochastic modeling), econometric modeling, predictive modeling, and optimization techniques.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Nature
Data di pubblicazione
2025
Lingua
Inglese
ISBN 10 
3031868617
ISBN 13 
9783031868610
Rilegatura
Copertina rigida
Numero di pagine
216
Contatto del produttore
ProductSafety@springernature.com
ProductSafety@springernature.com

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