R In Finance And Economics: A Beginner's Guide
Publication details: New Jersey World Scientific 2021 Edition: 1Description: 245ISBN: 978-0000989048Subject(s): EconomicsDDC classification: 330.02855133 SIN.ALL Summary: This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using Studio and reproducible research examples. It will enable students to use R for data cleaning, data visualisation and quantitative model building using statistical methods like linear regression, econometrics (GARCH etc), copulas, etc. Moreover, the book demonstrates latest research methods with applications featuring linear regression, quantile regression, panel regression, econometrics, dependence modelling, etc. Using a range of data sets and examples.| Item type | Home library | Call number | Materials specified | Status | Date due | Barcode |
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Parvatibai Chowgule College of Arts and Science, Margao Economics | 330.02855133 SIN.ALL (Browse shelf(Opens below)) | Available | PCC-49051 |
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| 330 SHA/Eco Economics of social issues | 330.015195 STU/Pra A Practical Guide to Using Econometrics | 330.019 THA.SUN Nudge | 330.02855133 SIN.ALL R In Finance And Economics: A Beginner's Guide | 330.109 GID/RIS A HISTORY OF ECONOMIC DOCTRINES | 330.109 LOK/His History Of Economic Thought | 330.18 SYD.HAM Mathematics for Economic Analysis |
This book provides an introduction to the statistical software R and its application with an empirical approach in finance and economics. It is specifically targeted towards undergraduate and graduate students. It provides beginner-level introduction to R using Studio and reproducible research examples. It will enable students to use R for data cleaning, data visualisation and quantitative model building using statistical methods like linear regression, econometrics (GARCH etc), copulas, etc. Moreover, the book demonstrates latest research methods with applications featuring linear regression, quantile regression, panel regression, econometrics, dependence modelling, etc. Using a range of data sets and examples.
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