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portada Financial Econometrics, Mathematics and Statistics: Theory, Method and Application (in English)
Type
Physical Book
Publisher
Year
2019
Language
English
Pages
655
Format
Hardcover
ISBN13
9781493994274
Edition No.
1

Financial Econometrics, Mathematics and Statistics: Theory, Method and Application (in English)

Cheng-Few Lee; Hong-Yi Chen; John Lee (Author) · Springer · Hardcover

Financial Econometrics, Mathematics and Statistics: Theory, Method and Application (in English) - Cheng-Few Lee; Hong-Yi Chen; John Lee

Physical Book

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Synopsis "Financial Econometrics, Mathematics and Statistics: Theory, Method and Application (in English)"

This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research. Financial Econometrics, Mathematics, and Statistics introduces tools and methods important for both finance and accounting that assist with asset pricing, corporate finance, options and futures, and conducting financial accounting research.  Divided into four parts, the text begins with topics related to regression and financial econometrics. Subsequent sections describe time-series analyses; the role of binomial, multi-nomial, and log normal distributions in option pricing models; and the application of statistics analyses to risk management. The real-world applications and problems offer students a unique insight into such topics as heteroskedasticity, regression, simultaneous equation models, panel data analysis, time series analysis, and generalized method of moments.  Written by leading academics in the quantitative finance field, allows readers to implement the principles behind financial econometrics and statistics through real-world applications and problem sets.  This textbook will appeal to a less-served market of upper-undergraduate and graduate students in finance, economics, and statistics.  ​

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

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